Datasets:

cy0307
/

ropedia-xperience-10m-task-suite-artifacts

@@ -1,6 +1,6 @@
 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
-  "generated_at_utc": "2026-06-18T22:26:00+00:00",
   "status": "pass",
   "artifact_count": 214,
   "missing": [],
@@ -610,7 +610,7 @@
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
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     },
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       "id": "source_alignment_validator",
@@ -730,8 +730,8 @@
       "surface": "website_hf",
       "shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings, branch-card caveats, and explicit scoreless status records.",
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       "id": "single_episode_task_model_radar_json",
@@ -742,7 +742,7 @@
       "shows": "Machine-readable split radar for the one-episode Minimal and Neural MLP baselines, both scored on all 20 task contracts.",
       "exists": true,
       "bytes": 51064,
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       "id": "episode128_task_model_radar_json",
@@ -752,8 +752,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable split radar for selected 128-episode metadata/raw baselines and verified Qwen3/Cosmos branches, preserving explicit scoreless cells.",
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       "id": "task_method_20_result_matrix_json",
@@ -763,8 +763,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable 9-method by 20-task matrix where every method has 20 records and scoreless cells carry unsupported/not-evaluated reasons.",
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       "id": "task_method_20_result_matrix",
@@ -774,8 +774,8 @@
       "surface": "repo_hf",
       "shows": "Reader-facing table that separates 20 records per method from numeric scored axes, documented raw128 proxy scores, unsupported metadata targets, and model targets not evaluated in verified packages.",
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     {
       "id": "task_method_20_gap_audit_json",
@@ -785,8 +785,8 @@
       "surface": "website_hf",
       "shows": "Machine-readable 180-record gap ledger with numeric scores, scoreless cells, explicit status reasons, and next evidence needed before new scores can be published.",
       "exists": true,
-      "bytes": 29788,
-      "sha256": "143e03828559e706ab083b3824731d652bcb5a915cfb441caa4a3e6447a982f2"
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       "id": "task_method_20_gap_audit",
@@ -796,8 +796,8 @@
       "surface": "repo_hf",
       "shows": "Reader-facing ledger that lists every scoreless method-task cell and the concrete target or model-output evidence required before it can become numeric.",
       "exists": true,
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-      "sha256": "8fd8555f75cd96c31346618ab622e24655027cea5c52e8a09a7a53793ef7b72b"
     },
     {
       "id": "unified_task_model_radar_chart",
@@ -807,8 +807,8 @@
       "surface": "website_hf",
       "shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
       "exists": true,
-      "bytes": 54717,
-      "sha256": "8fb6de7004e8463c28d6ada669c475d19986a1a3689778c691717cff39a7531a"
     },
     {
       "id": "single_episode_task_model_radar_chart",
@@ -829,8 +829,8 @@
       "surface": "website_hf",
       "shows": "Separates the selected 128-episode methods: raw-feature simple/NN as complete 20/20 scored polygons and metadata/Qwen/Cosmos as task-aligned overlays.",
       "exists": true,
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-      "sha256": "45f8a79dc764ddbf0182ab7994fbfa5002b52b075951ab42831ecbfb3fd0405c"
     },
     {
       "id": "unified_task_model_radar_builder",
@@ -840,8 +840,8 @@
       "surface": "repo_hf",
       "shows": "Regenerates the direction-aware radar chart and machine-readable metric overlay JSON.",
       "exists": true,
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-      "sha256": "237ef6a08dd81b9fcb0256f6f6b54394f74c14daea0cbba8f1726fdbbb7feff0"
     },
     {
       "id": "task_method_20_gap_audit_builder",
@@ -873,8 +873,8 @@
       "surface": "repo_hf",
       "shows": "Checks whether Qwen3/Cosmos branches have train, validation, and test prediction files before extending model overlays to all 20 task contracts.",
       "exists": true,
-      "bytes": 5144,
-      "sha256": "86835a291c659d335ab5b51d09ea3f36710c14d23466a72d9c2a23137dc9ae8a"
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       "id": "model_output_probe_script",
@@ -895,8 +895,8 @@
       "surface": "repo_hf",
       "shows": "Scores task-specific Qwen3/Cosmos overlays only where verified held-out prediction JSON or compact target maps already contain the required targets.",
       "exists": true,
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-      "sha256": "4a27f39807e8ac13771e2109584a8b0265961bcea88445058cbfe87265457d7f"
     },
     {
       "id": "existing_model_output_task_probe_script",
@@ -906,8 +906,8 @@
       "surface": "repo_hf",
       "shows": "Derives task-specific scores from committed verified model outputs without running new inference or backfilling absent targets.",
       "exists": true,
-      "bytes": 57470,
-      "sha256": "9a0708885c1a22addc0bec199488021e277c7a7b7e23d6a37344fbbb3e5f1b96"
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       "id": "a100_128_metadata_task_baselines",
@@ -1116,7 +1116,7 @@
       "shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
       "exists": true,
       "bytes": 8100,
-      "sha256": "12cec90cfb4bd783f397852f04ffba5b9d0ae9316667bdee4719cbd6f2d3579a"
     },
     {
       "id": "public_surface_qa",
@@ -1321,7 +1321,7 @@
       "volatile": true,
       "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
       "exists": true,
-      "bytes": 938745,
       "hash_policy": "existence_and_size_only"
     },
     {

 {
   "title": "Ropedia Xperience-10M Task Suite Artifact Index",
+  "generated_at_utc": "2026-06-18T22:57:14+00:00",
   "status": "pass",
   "artifact_count": 214,
   "missing": [],
       "shows": "Machine-readable source-alignment pass/fail check for repo, website, and HF surfaces.",
       "exists": true,
       "bytes": 4432,
+      "sha256": "1df30908392b455cc7263154126d55709cf97c60ff4213f0eee9ce17d92fb234"
     },
     {
       "id": "source_alignment_validator",
       "surface": "website_hf",
       "shows": "Stores normalized 20-axis radar values, raw task metrics, Qwen3/Cosmos overlay mappings, branch-card caveats, and explicit scoreless status records.",
       "exists": true,
+      "bytes": 229168,
+      "sha256": "64c7c10f3ce663178f2eea4740bb45de0f94b1246448f14f5521d293be916e77"
     },
     {
       "id": "single_episode_task_model_radar_json",
       "shows": "Machine-readable split radar for the one-episode Minimal and Neural MLP baselines, both scored on all 20 task contracts.",
       "exists": true,
       "bytes": 51064,
+      "sha256": "9d42b045d833e50a2bfa8905203150af1f28ea4736d22edb0fe27e39eedf4574"
     },
     {
       "id": "episode128_task_model_radar_json",
       "surface": "website_hf",
       "shows": "Machine-readable split radar for selected 128-episode metadata/raw baselines and verified Qwen3/Cosmos branches, preserving explicit scoreless cells.",
       "exists": true,
+      "bytes": 185314,
+      "sha256": "5c61c8f9a4a9a7b6bdc65e39ef5fda6117df48412afe260c0be4da501bd7e8db"
     },
     {
       "id": "task_method_20_result_matrix_json",
       "surface": "website_hf",
       "shows": "Machine-readable 9-method by 20-task matrix where every method has 20 records and scoreless cells carry unsupported/not-evaluated reasons.",
       "exists": true,
+      "bytes": 128805,
+      "sha256": "d5572768c6fb671eadf87870d20c8645dfae384f862aa63e929b2db50a5cc51a"
     },
     {
       "id": "task_method_20_result_matrix",
       "surface": "repo_hf",
       "shows": "Reader-facing table that separates 20 records per method from numeric scored axes, documented raw128 proxy scores, unsupported metadata targets, and model targets not evaluated in verified packages.",
       "exists": true,
+      "bytes": 3876,
+      "sha256": "a9ce23a452ca73b6d08219ffaac1782d5baad11f9e3662138b62cb4cd5ff206f"
     },
     {
       "id": "task_method_20_gap_audit_json",
       "surface": "website_hf",
       "shows": "Machine-readable 180-record gap ledger with numeric scores, scoreless cells, explicit status reasons, and next evidence needed before new scores can be published.",
       "exists": true,
+      "bytes": 28259,
+      "sha256": "860dea3d3ce2f2c2146c97918a5deca05ae315238b584c10e53f74a9d2c26dcd"
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     {
       "id": "task_method_20_gap_audit",
       "surface": "repo_hf",
       "shows": "Reader-facing ledger that lists every scoreless method-task cell and the concrete target or model-output evidence required before it can become numeric.",
       "exists": true,
+      "bytes": 8428,
+      "sha256": "b33c7f91565a2603b138eb4ec1c6df32d823225b16563eba279f416b0fe2a964"
     },
     {
       "id": "unified_task_model_radar_chart",
       "surface": "website_hf",
       "shows": "Compares minimal and neural MLP baselines across all 20 tasks, with Qwen3/Cosmos task-aligned model overlays.",
       "exists": true,
+      "bytes": 54936,
+      "sha256": "f29db4099d60c093ebd092bee37a2fc1338bbff17d7e52b8a1b27ae6fc06727a"
     },
     {
       "id": "single_episode_task_model_radar_chart",
       "surface": "website_hf",
       "shows": "Separates the selected 128-episode methods: raw-feature simple/NN as complete 20/20 scored polygons and metadata/Qwen/Cosmos as task-aligned overlays.",
       "exists": true,
+      "bytes": 48923,
+      "sha256": "75c389122a413548bdc26fd05cbbad2a85015ebd222ba1a23571f3ff4f0eddcf"
     },
     {
       "id": "unified_task_model_radar_builder",
       "surface": "repo_hf",
       "shows": "Regenerates the direction-aware radar chart and machine-readable metric overlay JSON.",
       "exists": true,
+      "bytes": 57104,
+      "sha256": "805cfce89529fec73edd3e436c1a76afae46cebe31ba5e441b6dfb5cc142c935"
     },
     {
       "id": "task_method_20_gap_audit_builder",
       "surface": "repo_hf",
       "shows": "Checks whether Qwen3/Cosmos branches have train, validation, and test prediction files before extending model overlays to all 20 task contracts.",
       "exists": true,
+      "bytes": 4977,
+      "sha256": "b9caf6d32bb801d845b57b4450b92c10a4c3f9d14890f6a209e5a52aede92568"
     },
     {
       "id": "model_output_probe_script",
       "surface": "repo_hf",
       "shows": "Scores task-specific Qwen3/Cosmos overlays only where verified held-out prediction JSON or compact target maps already contain the required targets.",
       "exists": true,
+      "bytes": 5951,
+      "sha256": "910477d2fba648605dda128d0ecd2a2c13cfa460573e350dc850014ac91c6c2b"
     },
     {
       "id": "existing_model_output_task_probe_script",
       "surface": "repo_hf",
       "shows": "Derives task-specific scores from committed verified model outputs without running new inference or backfilling absent targets.",
       "exists": true,
+      "bytes": 69411,
+      "sha256": "a78889e5225405fcbb0156aa8c63cbbe79022a12283d0b398c5f2bb015175fe7"
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     {
       "id": "a100_128_metadata_task_baselines",
       "shows": "Machine-readable release-check summary for validators, mirrors, and public project surfaces.",
       "exists": true,
       "bytes": 8100,
+      "sha256": "b88b46bd9b16d4afaf4836d0acff208b46559a493cfcffa881f1528fa282292c"
     },
     {
       "id": "public_surface_qa",
       "volatile": true,
       "shows": "Confirms prepared GitHub/HF Space/artifact/model mirrors share the same critical data, figure, website HTML, and validator files.",
       "exists": true,
+      "bytes": 1015184,
       "hash_policy": "existence_and_size_only"
     },
     {

data/episode128_task_model_radar.json CHANGED Viewed

@@ -1,12 +1,12 @@
 {
   "title": "128-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-18T22:25:59+00:00",
   "description": "Selected 128-episode metadata/raw baselines plus verified Qwen3/Cosmos branches. Every method has 20 records; numeric scores appear only where the public artifact produced that task target.",
   "task_count": 20,
   "method_count": 7,
   "method_task_record_count": 140,
-  "scored_method_task_count": 111,
   "normalization_policy": {
     "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
@@ -147,20 +147,20 @@
       "kind": "partial_128_episode_foundation_model_overlay",
       "scope": "128 selected episodes, held-out test",
       "stroke_dasharray": "4 7",
-      "method_detail": "Verified Cosmos3-Super base-weight Reasoner JSON-task evaluation, plus task 16 and a derived task-20 action-boundary timing probe scored from existing verified JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
-      "scored_task_count": 9,
-      "covered_task_count": 9,
       "proxy_scored_task_count": 0,
-      "scoreless_task_count": 11,
       "unsupported_task_count": 0,
-      "not_evaluated_task_count": 11,
       "status_counts": {
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-        "scored": 9
       },
-      "coverage_fraction": 0.45,
       "result_record_fraction": 1.0
     },
     {
@@ -171,20 +171,20 @@
       "kind": "partial_128_episode_world_model_overlay",
       "scope": "128 selected episodes, held-out test",
       "stroke_dasharray": "2 7",
-      "method_detail": "Verified Cosmos3-Nano future-window compatibility metrics, plus tasks 10/13/14/17 and a derived task-20 boundary timing probe scored from existing held-out future-window artifacts.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
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     }
   ],
@@ -894,15 +894,15 @@
           "status_label": "scored"
         },
         "cosmos3_super_reasoner": {
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-          "metric_key": "mrr",
-          "source": null,
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
         },
         "cosmos3_nano_future_window": {
           "raw": null,
@@ -1633,15 +1633,15 @@
           "status_label": "scored"
         },
         "cosmos3_nano_future_window": {
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-          "metric_key": "macro_f1",
-          "source": null,
           "scope": "multi_episode_128_partial_model_overlay",
-          "status": "not_evaluated_in_verified_package",
-          "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-          "normalized_score": null,
-          "raw_text": "n/a",
-          "status_label": "not evaluated"
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@@ -2989,17 +2989,17 @@
       "task_label": "Language Grounding",
       "series_id": "cosmos3_super_reasoner",
       "method": "Cosmos3-Super Reasoner",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
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-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "mrr",
-      "source": null,
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
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     {
       "task_number": 8,
@@ -4015,17 +4015,17 @@
       "task_label": "Action-Object Relation Prediction",
       "series_id": "cosmos3_nano_future_window",
       "method": "Cosmos3-Nano Future Window",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
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-      "raw": null,
-      "raw_text": "n/a",
-      "normalized_score": null,
-      "metric_key": "macro_f1",
-      "source": null,
       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
     },
     {
       "task_number": 17,

 {
   "title": "128-Episode 20-Task Radar",
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:55:01+00:00",
   "description": "Selected 128-episode metadata/raw baselines plus verified Qwen3/Cosmos branches. Every method has 20 records; numeric scores appear only where the public artifact produced that task target.",
   "task_count": 20,
   "method_count": 7,
   "method_task_record_count": 140,
+  "scored_method_task_count": 113,
   "normalization_policy": {
     "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
       "kind": "partial_128_episode_foundation_model_overlay",
       "scope": "128 selected episodes, held-out test",
       "stroke_dasharray": "4 7",
+      "method_detail": "Verified Cosmos3-Super base-weight Reasoner JSON-task evaluation, plus task 8/16 and a derived task-20 action-boundary timing probe scored from existing verified JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
+      "scoreless_task_count": 10,
       "unsupported_task_count": 0,
+      "not_evaluated_task_count": 10,
       "status_counts": {
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+        "scored": 10
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       "result_record_fraction": 1.0
     },
     {
       "kind": "partial_128_episode_world_model_overlay",
       "scope": "128 selected episodes, held-out test",
       "stroke_dasharray": "2 7",
+      "method_detail": "Verified Cosmos3-Nano future-window compatibility metrics, plus tasks 10/13/14/16/17 and a derived task-20 boundary timing probe scored from existing held-out future-window artifacts.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
+      "scored_task_count": 11,
+      "covered_task_count": 11,
       "proxy_scored_task_count": 0,
+      "scoreless_task_count": 9,
       "unsupported_task_count": 0,
+      "not_evaluated_task_count": 9,
       "status_counts": {
+        "not_evaluated_in_verified_package": 9,
+        "scored": 11
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+      "coverage_fraction": 0.55,
       "result_record_fraction": 1.0
     }
   ],
           "status_label": "scored"
         },
         "cosmos3_super_reasoner": {
+          "raw": 0.30639899644580487,
+          "metric_key": "caption_grounding_iou",
+          "source": "results/omni_finetune/model_output_task_probes_20260616/caption_grounding/cosmos3_super_reasoner/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.30639899644580487,
+          "raw_text": "0.3064",
+          "status_label": "scored"
         },
         "cosmos3_nano_future_window": {
           "raw": null,
           "status_label": "scored"
         },
         "cosmos3_nano_future_window": {
+          "raw": 0.002794157670325683,
+          "metric_key": "action_object_relation_macro_f1",
+          "source": "results/omni_finetune/model_output_task_probes_20260616/action_object_relation/cosmos3_nano_future_window/metrics.json",
           "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.002794157670325683,
+          "raw_text": "0.0028",
+          "status_label": "scored"
         }
       }
     },
       "task_label": "Language Grounding",
       "series_id": "cosmos3_super_reasoner",
       "method": "Cosmos3-Super Reasoner",
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
+      "raw": 0.30639899644580487,
+      "raw_text": "0.3064",
+      "normalized_score": 0.30639899644580487,
+      "metric_key": "caption_grounding_iou",
+      "source": "results/omni_finetune/model_output_task_probes_20260616/caption_grounding/cosmos3_super_reasoner/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
+      "reason": null
     },
     {
       "task_number": 8,
       "task_label": "Action-Object Relation Prediction",
       "series_id": "cosmos3_nano_future_window",
       "method": "Cosmos3-Nano Future Window",
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
+      "raw": 0.002794157670325683,
+      "raw_text": "0.0028",
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   "title": "Ropedia Xperience-10M Release Checks",
   "status": "pass",
-  "generated_at_utc": "2026-06-18T22:26:00+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
     {

 {
   "title": "Ropedia Xperience-10M Release Checks",
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:57:13+00:00",
   "rule": "A release is current when the automated reports pass and the live GitHub/Hugging Face mirrors are verified after publishing.",
   "automated_gates": [
     {

data/single_episode_task_model_radar.json CHANGED Viewed

@@ -1,7 +1,7 @@
 {
   "title": "Single-Episode 20-Task Radar",
   "status": "pass",
-  "generated_at_utc": "2026-06-18T22:25:59+00:00",
   "description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
   "task_count": 20,
   "method_count": 2,

 {
   "title": "Single-Episode 20-Task Radar",
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:55:01+00:00",
   "description": "Minimal and Neural MLP baselines on the one public sample episode, both scored on all 20 task contracts.",
   "task_count": 20,
   "method_count": 2,

data/source_alignment_audit.json CHANGED Viewed

@@ -1,7 +1,7 @@
 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
-  "generated_at_utc": "2026-06-18T22:27:40+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

 {
   "title": "Ropedia Xperience-10M Source Alignment Note",
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:57:59+00:00",
   "alignment_json": "docs/data/xperience10m_dataset_card_alignment.json",
   "alignment_summary": {
     "full_dataset_repo": "ropedia-ai/xperience-10m",

data/task_method_20_gap_audit.json CHANGED Viewed

@@ -1,10 +1,10 @@
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-  "generated_at_utc": "2026-06-18T22:25:59+00:00",
   "immediate_actions": [
     {
       "artifact": "docs/data/task_method_20_gap_audit.json",
       "id": "gap_audit",
-      "purpose": "Keep the 29 scoreless cells visible and reproducible."
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     {
       "artifact": "scripts/omni/score_model_output_probes.py",
@@ -24,11 +24,11 @@
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     "cosmos3_super_reasoner": {
@@ -37,11 +37,11 @@
       "proxy_scored_task_count": 0,
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     },
     "metadata128_neural_mlp": {
@@ -135,14 +135,14 @@
     }
   },
   "missing_by_method": {
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     "metadata128_neural_mlp": 2,
     "metadata128_simple": 2,
     "qwen3_omni_v6_lora": 4
   },
   "missing_by_status": {
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     "unsupported_without_required_target": 2
   },
@@ -159,8 +159,7 @@
       "cosmos3_nano_future_window"
     ],
     "08 Language Grounding": [
-      "cosmos3_nano_future_window",
-      "cosmos3_super_reasoner"
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     "09 Cross-Modal Retrieval": [
       "cosmos3_super_reasoner"
@@ -187,9 +186,6 @@
       "metadata128_simple",
       "qwen3_omni_v6_lora"
     ],
-    "16 Action-Object Relation Prediction": [
-      "cosmos3_nano_future_window"
-    ],
     "17 Future Object-Set Forecasting": [
       "cosmos3_super_reasoner"
     ],
@@ -271,19 +267,6 @@
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       "task_number": 7
     },
-    {
-      "method": "Cosmos3-Super Reasoner",
-      "metric_key": "mrr",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "cosmos3_super_reasoner",
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-      "status_label": "not evaluated",
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-      "task_label": "Language Grounding",
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-    },
     {
       "method": "Cosmos3-Nano Future Window",
       "metric_key": "mrr",
@@ -466,19 +449,6 @@
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       "task_number": 15
     },
-    {
-      "method": "Cosmos3-Nano Future Window",
-      "metric_key": "macro_f1",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score",
-      "recommended_next_step": "Generate verified model outputs for this task contract and score them against the held-out labels.",
-      "scope": "multi_episode_128_partial_model_overlay",
-      "series_id": "cosmos3_nano_future_window",
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-      "status_label": "not evaluated",
-      "task_id": "action_object_relation",
-      "task_label": "Action-Object Relation Prediction",
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-    },
     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "micro_f1",
@@ -630,8 +600,8 @@
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     "proxy_scored_method_task_count": 4,
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-    "scoreless_method_task_count": 29,
     "task_count": 20
   },
   "source_matrix": "docs/data/task_method_20_result_matrix.json",

 {
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   "immediate_actions": [
     {
       "artifact": "docs/data/task_method_20_gap_audit.json",
       "id": "gap_audit",
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     },
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       "artifact": "scripts/omni/score_model_output_probes.py",
       "proxy_scored_task_count": 0,
       "result_record_count": 20,
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     "cosmos3_super_reasoner": {
       "proxy_scored_task_count": 0,
       "result_record_count": 20,
       "scope": "128 selected episodes, held-out test",
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       "status_counts": {
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+        "scored": 10
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     },
     "metadata128_neural_mlp": {
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   },
   "missing_by_method": {
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+    "cosmos3_super_reasoner": 10,
     "metadata128_neural_mlp": 2,
     "metadata128_simple": 2,
     "qwen3_omni_v6_lora": 4
   },
   "missing_by_status": {
+    "not_evaluated_in_verified_package": 23,
     "not_supported_by_metadata_only_package": 2,
     "unsupported_without_required_target": 2
   },
       "cosmos3_nano_future_window"
     ],
     "08 Language Grounding": [
+      "cosmos3_nano_future_window"
     ],
     "09 Cross-Modal Retrieval": [
       "cosmos3_super_reasoner"
       "metadata128_simple",
       "qwen3_omni_v6_lora"
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       "cosmos3_super_reasoner"
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       "task_label": "Object Relevance Prediction",
       "task_number": 7
     },
     {
       "method": "Cosmos3-Nano Future Window",
       "metric_key": "mrr",
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       "task_number": 15
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     {
       "method": "Cosmos3-Super Reasoner",
       "metric_key": "micro_f1",
     "method_count": 9,
     "method_task_record_count": 180,
     "proxy_scored_method_task_count": 4,
+    "scored_method_task_count": 153,
+    "scoreless_method_task_count": 27,
     "task_count": 20
   },
   "source_matrix": "docs/data/task_method_20_result_matrix.json",

data/task_method_20_result_matrix.json CHANGED Viewed

@@ -1,11 +1,11 @@
 {
   "title": "Task Method 20-Result Matrix",
   "status": "pass",
-  "generated_at_utc": "2026-06-18T22:25:59+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
-  "scored_method_task_count": 151,
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@@ -181,20 +181,20 @@
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       "stroke_dasharray": "4 7",
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@@ -205,20 +205,20 @@
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       "plotted_as": "colored point overlay",
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@@ -1489,17 +1489,17 @@
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     {
       "task_number": 8,
@@ -2803,17 +2803,17 @@
       "task_label": "Action-Object Relation Prediction",
       "series_id": "cosmos3_nano_future_window",
       "method": "Cosmos3-Nano Future Window",
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-      "metric_key": "macro_f1",
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       "scope": "multi_episode_128_partial_model_overlay",
-      "reason": "the verified public model package did not ask this branch to emit that task target; a new task-specific evaluation package is required for a numeric score"
     },
     {
       "task_number": 17,

 {
   "title": "Task Method 20-Result Matrix",
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:55:01+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
+  "scored_method_task_count": 153,
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     {
       "id": "minimal",
       "kind": "partial_128_episode_foundation_model_overlay",
       "scope": "128 selected episodes, held-out test",
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       "plotted_as": "colored point overlay",
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     {
       "kind": "partial_128_episode_world_model_overlay",
       "scope": "128 selected episodes, held-out test",
       "stroke_dasharray": "2 7",
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       "plotted_as": "colored point overlay",
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   ],
       "task_label": "Language Grounding",
       "series_id": "cosmos3_super_reasoner",
       "method": "Cosmos3-Super Reasoner",
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
+      "raw": 0.30639899644580487,
+      "raw_text": "0.3064",
+      "normalized_score": 0.30639899644580487,
+      "metric_key": "caption_grounding_iou",
+      "source": "results/omni_finetune/model_output_task_probes_20260616/caption_grounding/cosmos3_super_reasoner/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
+      "reason": null
     },
     {
       "task_number": 8,
       "task_label": "Action-Object Relation Prediction",
       "series_id": "cosmos3_nano_future_window",
       "method": "Cosmos3-Nano Future Window",
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
+      "raw": 0.002794157670325683,
+      "raw_text": "0.0028",
+      "normalized_score": 0.002794157670325683,
+      "metric_key": "action_object_relation_macro_f1",
+      "source": "results/omni_finetune/model_output_task_probes_20260616/action_object_relation/cosmos3_nano_future_window/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
+      "reason": null
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     {
       "task_number": 17,

data/task_surface_integrity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-18T22:27:40+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:57:59+00:00",
   "summary": {
     "task_count": 12,
     "expected_task_count": 12,

data/unified_task_model_radar.json CHANGED Viewed

@@ -1,11 +1,11 @@
 {
   "title": "Unified 20-Task Model Radar",
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   "normalization_policy": {
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     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
@@ -190,20 +190,20 @@
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       "stroke_dasharray": "4 7",
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@@ -214,20 +214,20 @@
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@@ -1041,6 +1041,17 @@
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         "qwen3_omni_v6_lora": {
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@@ -1096,17 +1107,6 @@
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-          "status_label": "not evaluated"
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         "cosmos3_nano_future_window": {
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@@ -1951,6 +1951,17 @@
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         "metadata128_simple": {
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@@ -1994,17 +2005,6 @@
           "normalized_score": 0.0,
           "raw_text": "0.0000",
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-          "status_label": "not evaluated"
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@@ -2499,7 +2499,7 @@
       "id": "cosmos3_super_reasoner",
       "title": "Cosmos3-Super Reasoner",
       "status": "verified_base_weight_eval",
-      "coverage": "20 records / 9 scored task-aligned axes",
       "headline": "JSON validity 0.5112; action macro-F1 0.0008",
       "source": "results/omni_finetune/verified_public/xperience10m_cosmos3_super_reasoner_128ep_test_full_20260607/eval/metrics.json"
     },
@@ -2507,7 +2507,7 @@
       "id": "cosmos3_nano_future_window",
       "title": "Cosmos3-Nano Future Window",
       "status": "verified_compatibility_eval",
-      "coverage": "20 records / 10 scored task-aligned axes",
       "headline": "future retrieval MRR 0.0221; transition accuracy 0.9683",
       "source": "results/omni_finetune/verified_public/xperience10m_cosmos3_nano_128ep_future_window_h5_compat_adapter_eval_test_full/eval/metrics.json"
     },
@@ -3787,17 +3787,17 @@
       "task_label": "Language Grounding",
       "series_id": "cosmos3_super_reasoner",
       "method": "Cosmos3-Super Reasoner",
-      "status": "not_evaluated_in_verified_package",
-      "status_label": "not evaluated",
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     {
       "task_number": 8,
@@ -5101,17 +5101,17 @@
       "task_label": "Action-Object Relation Prediction",
       "series_id": "cosmos3_nano_future_window",
       "method": "Cosmos3-Nano Future Window",
-      "status": "not_evaluated_in_verified_package",
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-      "raw_text": "n/a",
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-      "metric_key": "macro_f1",
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     },
     {
       "task_number": 17,

 {
   "title": "Unified 20-Task Model Radar",
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:55:01+00:00",
   "task_count": 20,
   "method_count": 9,
   "method_task_record_count": 180,
+  "scored_method_task_count": 153,
   "normalization_policy": {
     "higher_is_better": "bounded metrics are plotted directly on 0-1 axes after clipping to [0, 1]",
     "lower_is_better": "lower-error metrics are converted to best_observed_value / raw_value within the same task",
       "kind": "partial_128_episode_foundation_model_overlay",
       "scope": "128 selected episodes, held-out test",
       "stroke_dasharray": "4 7",
+      "method_detail": "Verified Cosmos3-Super base-weight Reasoner JSON-task evaluation, plus task 8/16 and a derived task-20 action-boundary timing probe scored from existing verified JSON.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
+      "scored_task_count": 10,
+      "covered_task_count": 10,
       "proxy_scored_task_count": 0,
+      "scoreless_task_count": 10,
       "unsupported_task_count": 0,
+      "not_evaluated_task_count": 10,
       "status_counts": {
+        "not_evaluated_in_verified_package": 10,
+        "scored": 10
       },
+      "coverage_fraction": 0.5,
       "result_record_fraction": 1.0
     },
     {
       "kind": "partial_128_episode_world_model_overlay",
       "scope": "128 selected episodes, held-out test",
       "stroke_dasharray": "2 7",
+      "method_detail": "Verified Cosmos3-Nano future-window compatibility metrics, plus tasks 10/13/14/16/17 and a derived task-20 boundary timing probe scored from existing held-out future-window artifacts.",
       "plotted_as": "colored point overlay",
       "result_record_count": 20,
+      "scored_task_count": 11,
+      "covered_task_count": 11,
       "proxy_scored_task_count": 0,
+      "scoreless_task_count": 9,
       "unsupported_task_count": 0,
+      "not_evaluated_task_count": 9,
       "status_counts": {
+        "not_evaluated_in_verified_package": 9,
+        "scored": 11
       },
+      "coverage_fraction": 0.55,
       "result_record_fraction": 1.0
     }
   ],
           "raw_text": "0.0168",
           "status_label": "scored"
         },
+        "cosmos3_super_reasoner": {
+          "raw": 0.30639899644580487,
+          "metric_key": "caption_grounding_iou",
+          "source": "results/omni_finetune/model_output_task_probes_20260616/caption_grounding/cosmos3_super_reasoner/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.30639899644580487,
+          "raw_text": "0.3064",
+          "status_label": "scored"
+        },
         "qwen3_omni_v6_lora": {
           "raw": 0.8764467592592605,
           "metric_key": "caption_grounding_mrr",
           "raw_text": "0.0063",
           "status_label": "scored"
         },
         "cosmos3_nano_future_window": {
           "raw": null,
           "metric_key": "mrr",
           "raw_text": "0.0000",
           "status_label": "scored"
         },
+        "cosmos3_nano_future_window": {
+          "raw": 0.002794157670325683,
+          "metric_key": "action_object_relation_macro_f1",
+          "source": "results/omni_finetune/model_output_task_probes_20260616/action_object_relation/cosmos3_nano_future_window/metrics.json",
+          "scope": "multi_episode_128_partial_model_overlay",
+          "status": "scored",
+          "reason": null,
+          "normalized_score": 0.002794157670325683,
+          "raw_text": "0.0028",
+          "status_label": "scored"
+        },
         "metadata128_simple": {
           "raw": 0.0,
           "metric_key": "macro_f1",
           "normalized_score": 0.0,
           "raw_text": "0.0000",
           "status_label": "scored"
         }
       }
     },
       "id": "cosmos3_super_reasoner",
       "title": "Cosmos3-Super Reasoner",
       "status": "verified_base_weight_eval",
+      "coverage": "20 records / 10 scored task-aligned axes",
       "headline": "JSON validity 0.5112; action macro-F1 0.0008",
       "source": "results/omni_finetune/verified_public/xperience10m_cosmos3_super_reasoner_128ep_test_full_20260607/eval/metrics.json"
     },
       "id": "cosmos3_nano_future_window",
       "title": "Cosmos3-Nano Future Window",
       "status": "verified_compatibility_eval",
+      "coverage": "20 records / 11 scored task-aligned axes",
       "headline": "future retrieval MRR 0.0221; transition accuracy 0.9683",
       "source": "results/omni_finetune/verified_public/xperience10m_cosmos3_nano_128ep_future_window_h5_compat_adapter_eval_test_full/eval/metrics.json"
     },
       "task_label": "Language Grounding",
       "series_id": "cosmos3_super_reasoner",
       "method": "Cosmos3-Super Reasoner",
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
+      "raw": 0.30639899644580487,
+      "raw_text": "0.3064",
+      "normalized_score": 0.30639899644580487,
+      "metric_key": "caption_grounding_iou",
+      "source": "results/omni_finetune/model_output_task_probes_20260616/caption_grounding/cosmos3_super_reasoner/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
+      "reason": null
     },
     {
       "task_number": 8,
       "task_label": "Action-Object Relation Prediction",
       "series_id": "cosmos3_nano_future_window",
       "method": "Cosmos3-Nano Future Window",
+      "status": "scored",
+      "status_label": "scored",
+      "scored": true,
       "proxy_scored": false,
+      "raw": 0.002794157670325683,
+      "raw_text": "0.0028",
+      "normalized_score": 0.002794157670325683,
+      "metric_key": "action_object_relation_macro_f1",
+      "source": "results/omni_finetune/model_output_task_probes_20260616/action_object_relation/cosmos3_nano_future_window/metrics.json",
       "scope": "multi_episode_128_partial_model_overlay",
+      "reason": null
     },
     {
       "task_number": 17,

data/website_integrity.json CHANGED Viewed

@@ -1,6 +1,6 @@
 {
   "status": "pass",
-  "generated_at_utc": "2026-06-18T22:27:45+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
@@ -301,7 +301,7 @@
     },
     {
       "path": "data/artifact_index.json",
-      "bytes": 116643,
       "top_level_type": "dict"
     },
     {
@@ -316,7 +316,7 @@
     },
     {
       "path": "data/episode128_task_model_radar.json",
-      "bytes": 185391,
       "top_level_type": "dict"
     },
     {
@@ -351,7 +351,7 @@
     },
     {
       "path": "data/mirror_parity.json",
-      "bytes": 938745,
       "top_level_type": "dict"
     },
     {
@@ -486,12 +486,12 @@
     },
     {
       "path": "data/task_method_20_gap_audit.json",
-      "bytes": 29788,
       "top_level_type": "dict"
     },
     {
       "path": "data/task_method_20_result_matrix.json",
-      "bytes": 128842,
       "top_level_type": "dict"
     },
     {
@@ -526,7 +526,7 @@
     },
     {
       "path": "data/unified_task_model_radar.json",
-      "bytes": 229244,
       "top_level_type": "dict"
     },
     {
@@ -571,7 +571,7 @@
     {
       "path": "assets/charts/episode128_task_model_radar.svg",
       "exists": true,
-      "bytes": 48704,
       "format": "SVG",
       "has_viewbox": true
     },
@@ -641,7 +641,7 @@
     {
       "path": "assets/charts/unified_task_model_radar.svg",
       "exists": true,
-      "bytes": 54717,
       "format": "SVG",
       "has_viewbox": true
     },

 {
   "status": "pass",
+  "generated_at_utc": "2026-06-18T22:58:01+00:00",
   "docs_root": "docs",
   "site_base": "/ropedia-xperience-10m-task-suite/",
   "summary": {
     },
     {
       "path": "data/artifact_index.json",
+      "bytes": 116644,
       "top_level_type": "dict"
     },
     {
     },
     {
       "path": "data/episode128_task_model_radar.json",
+      "bytes": 185314,
       "top_level_type": "dict"
     },
     {
     },
     {
       "path": "data/mirror_parity.json",
+      "bytes": 1015184,
       "top_level_type": "dict"
     },
     {
     },
     {
       "path": "data/task_method_20_gap_audit.json",
+      "bytes": 28259,
       "top_level_type": "dict"
     },
     {
       "path": "data/task_method_20_result_matrix.json",
+      "bytes": 128805,
       "top_level_type": "dict"
     },
     {
     },
     {
       "path": "data/unified_task_model_radar.json",
+      "bytes": 229168,
       "top_level_type": "dict"
     },
     {
     {
       "path": "assets/charts/episode128_task_model_radar.svg",
       "exists": true,
+      "bytes": 48923,
       "format": "SVG",
       "has_viewbox": true
     },
     {
       "path": "assets/charts/unified_task_model_radar.svg",
       "exists": true,
+      "bytes": 54936,
       "format": "SVG",
       "has_viewbox": true
     },

results/omni_finetune/model_output_probe_readiness/RUN_REPORT.md CHANGED Viewed

@@ -1,6 +1,6 @@
 # Model Output Probe Readiness
-Generated: `2026-06-18T18:10:07+00:00`
 This report checks whether verified model branches have the prediction files
 needed to extend them to every 20-task contract. It is readiness evidence only;
@@ -8,6 +8,6 @@ it does not assign new task scores.
 | Method | ID | Matrix scores | Status | Split files | Next step |
 | --- | --- | --- | --- | --- | --- |
-| Cosmos3-Nano Future Window | cosmos3_nano_future_window | 7/20 | missing_required_model_outputs | train: missing; validation: missing; test: missing | Collect or generate train, validation, and test prediction JSONL files first. |
-| Cosmos3-Super Reasoner | cosmos3_super_reasoner | 8/20 | missing_required_model_outputs | train: missing; validation: missing; test: present | Collect or generate train, validation, and test prediction JSONL files first. |
-| Qwen3-Omni v6 LoRA | qwen3_omni_v6_lora | 15/20 | missing_required_model_outputs | train: missing; validation: missing; test: present | Collect or generate train, validation, and test prediction JSONL files first. |

 # Model Output Probe Readiness
+Generated: `2026-06-18T22:44:42+00:00`
 This report checks whether verified model branches have the prediction files
 needed to extend them to every 20-task contract. It is readiness evidence only;
 | Method | ID | Matrix scores | Status | Split files | Next step |
 | --- | --- | --- | --- | --- | --- |
+| Cosmos3-Nano Future Window | cosmos3_nano_future_window | 10/20 | missing_required_model_outputs | train: missing; validation: missing; test: missing | Collect or generate train, validation, and test prediction JSONL files first. |
+| Cosmos3-Super Reasoner | cosmos3_super_reasoner | 9/20 | missing_required_model_outputs | train: missing; validation: missing; test: present | Collect or generate train, validation, and test prediction JSONL files first. |
+| Qwen3-Omni v6 LoRA | qwen3_omni_v6_lora | 16/20 | missing_required_model_outputs | train: missing; validation: missing; test: present | Collect or generate train, validation, and test prediction JSONL files first. |

results/omni_finetune/model_output_probe_readiness/model_output_probe_readiness.json CHANGED Viewed

@@ -1,10 +1,10 @@
 {
-  "generated_at_utc": "2026-06-18T18:10:07+00:00",
   "methods": {
     "cosmos3_nano_future_window": {
       "label": "Cosmos3-Nano Future Window",
-      "matrix_scored_task_count": 7,
-      "matrix_scoreless_task_count": 13,
       "next_step": "Collect or generate train, validation, and test prediction JSONL files first.",
       "ready_for_all_task_probe": false,
       "required_splits": [
@@ -19,13 +19,10 @@
         "caption_grounding",
         "temporal_order",
         "misalignment_detection",
-        "next_subtask_forecast",
         "interaction_text_prediction",
         "action_object_relation",
-        "object_set_forecast",
         "imu_to_hand_pose",
-        "camera_view_sync_retrieval",
-        "time_to_transition"
       ],
       "split_status": {
         "test": {
@@ -54,8 +51,8 @@
     },
     "cosmos3_super_reasoner": {
       "label": "Cosmos3-Super Reasoner",
-      "matrix_scored_task_count": 8,
-      "matrix_scoreless_task_count": 12,
       "next_step": "Collect or generate train, validation, and test prediction JSONL files first.",
       "ready_for_all_task_probe": false,
       "required_splits": [
@@ -70,7 +67,6 @@
         "modality_reconstruction",
         "temporal_order",
         "misalignment_detection",
-        "long_horizon_next_action",
         "next_subtask_forecast",
         "interaction_text_prediction",
         "object_set_forecast",
@@ -103,8 +99,8 @@
     },
     "qwen3_omni_v6_lora": {
       "label": "Qwen3-Omni v6 LoRA",
-      "matrix_scored_task_count": 15,
-      "matrix_scoreless_task_count": 5,
       "next_step": "Collect or generate train, validation, and test prediction JSONL files first.",
       "ready_for_all_task_probe": false,
       "required_splits": [
@@ -116,8 +112,7 @@
         "hand_trajectory_forecast",
         "modality_reconstruction",
         "interaction_text_prediction",
-        "imu_to_hand_pose",
-        "camera_view_sync_retrieval"
       ],
       "split_status": {
         "test": {

 {
+  "generated_at_utc": "2026-06-18T22:44:42+00:00",
   "methods": {
     "cosmos3_nano_future_window": {
       "label": "Cosmos3-Nano Future Window",
+      "matrix_scored_task_count": 10,
+      "matrix_scoreless_task_count": 10,
       "next_step": "Collect or generate train, validation, and test prediction JSONL files first.",
       "ready_for_all_task_probe": false,
       "required_splits": [
         "caption_grounding",
         "temporal_order",
         "misalignment_detection",
         "interaction_text_prediction",
         "action_object_relation",
         "imu_to_hand_pose",
+        "camera_view_sync_retrieval"
       ],
       "split_status": {
         "test": {
     },
     "cosmos3_super_reasoner": {
       "label": "Cosmos3-Super Reasoner",
+      "matrix_scored_task_count": 9,
+      "matrix_scoreless_task_count": 11,
       "next_step": "Collect or generate train, validation, and test prediction JSONL files first.",
       "ready_for_all_task_probe": false,
       "required_splits": [
         "modality_reconstruction",
         "temporal_order",
         "misalignment_detection",
         "next_subtask_forecast",
         "interaction_text_prediction",
         "object_set_forecast",
     },
     "qwen3_omni_v6_lora": {
       "label": "Qwen3-Omni v6 LoRA",
+      "matrix_scored_task_count": 16,
+      "matrix_scoreless_task_count": 4,
       "next_step": "Collect or generate train, validation, and test prediction JSONL files first.",
       "ready_for_all_task_probe": false,
       "required_splits": [
         "hand_trajectory_forecast",
         "modality_reconstruction",
         "interaction_text_prediction",
+        "imu_to_hand_pose"
       ],
       "split_status": {
         "test": {

results/omni_finetune/model_output_task_probes_20260616/action_object_relation/cosmos3_nano_future_window/per_class_metrics.csv ADDED Viewed

	@@ -0,0 +1,152 @@

+class_name,support,predicted,precision,recall,f1
+Adjust canned food on shelf :: canned food | cardboard box | store shelf,2,0,0.0,0.0,0.0
+Adjust item on shelf :: shelf | stationery package,4,1,0.0,0.0,0.0
+Adjust lantern shape :: red pleated paper lantern,2,0,0.0,0.0,0.0
+Adjust paper :: cardboard square | paper | pen | star beads,3,0,0.0,0.0,0.0
+Adjust pot position :: pot,3,0,0.0,0.0,0.0
+Adjust puzzle piece :: jigsaw puzzle | puzzle box | puzzle pieces,3,0,0.0,0.0,0.0
+Align edges of paper lantern :: hands | red paper lantern,2,0,0.0,0.0,0.0
+Align paper lantern edges :: hands | red paper lantern,2,0,0.0,0.0,0.0
+Apply adhesive tape to lantern :: adhesive tape | red paper lantern,3,0,0.0,0.0,0.0
+Approach boxes :: cardboard boxes | colleague | shelving unit,3,0,0.0,0.0,0.0
+Approaching and pressing the door switch :: glass door | switch | wall,6,0,0.0,0.0,0.0
+Approaching the table :: beads | chairs | table,2,0,0.0,0.0,0.0
+Arrange buttons :: red buttons | smartphone | table,2,0,0.0,0.0,0.0
+Arrange buttons in a line :: buttons | phone | table,7,0,0.0,0.0,0.0
+Arrange star beads for counting :: paper | pen | star beads,4,0,0.0,0.0,0.0
+Attempt to fit puzzle piece :: puzzle board | puzzle piece,3,0,0.0,0.0,0.0
+Attempt to fit puzzle piece :: puzzle piece,2,0,0.0,0.0,0.0
+Bend and manipulate plastic strip :: plastic strip | stationary box | table | water bottle,1,0,0.0,0.0,0.0
+Browse smartphone screen :: paper strips | smartphone | star ornaments,3,0,0.0,0.0,0.0
+Closing the door :: door | dustpan,2,0,0.0,0.0,0.0
+Counting and organizing beads :: cardboard squares | paper | pen | star-shaped beads,2,0,0.0,0.0,0.0
+Counting star beads :: paper | pen | star beads,2,0,0.0,0.0,0.0
+Cut along the marked line :: cardboard | hand | utility knife,7,0,0.0,0.0,0.0
+Cut cardboard piece :: cardboard strip | scissors,3,0,0.0,0.0,0.0
+Entering the VR training room :: doorway | person | table,3,0,0.0,0.0,0.0
+Expand paper lantern :: adhesive tape roll | cardboard box | red paper lantern,3,0,0.0,0.0,0.0
+Extract wire hangers from box :: cardboard box | wire hangers,1,0,0.0,0.0,0.0
+Fold paper lantern :: red paper honeycomb lantern,2,0,0.0,0.0,0.0
+Gesturing :: cardboard pieces | marker | pencil case | ruler | scissors,2,0,0.0,0.0,0.0
+Grasp cleaning bottle :: bowls | chopping board | cleaning fluid bottle,1,0,0.0,0.0,0.0
+Grasp lantern :: red paper honeycomb lantern,1,0,0.0,0.0,0.0
+Grasping cleaning cloth :: cleaning cloth | countertop,4,361,0.0110803324099723,1.0,0.021917808219178086
+Greeting/acknowledging participants :: person | table | vr headset,2,0,0.0,0.0,0.0
+Handle paper lantern component :: cardboard box | paper lantern component | plastic bag | red paper lantern,1,0,0.0,0.0,0.0
+Hold and bend plastic strip :: bottle | purple plastic strip | stationery box,2,0,0.0,0.0,0.0
+Hold and manipulate paper strip :: beads | mobile phone | power bank | yellow paper strip,3,0,0.0,0.0,0.0
+Hold and manipulate paper strip :: beads | paper strip | power bank | smartphone,1,0,0.0,0.0,0.0
+Hold beads :: paper | pen | power bank | smartphone | star-shaped beads,2,0,0.0,0.0,0.0
+Hold container lid :: dustpan | red plastic container lid,1,0,0.0,0.0,0.0
+Hold earbud case :: box of products | earbud case | shelf,1,0,0.0,0.0,0.0
+Hold smartphone :: quilling paper strips | small blue beads | smartphone,1,0,0.0,0.0,0.0
+Identify next cardboard piece :: cardboard pieces | marker,3,0,0.0,0.0,0.0
+Inspect shelf condition :: colleague | shelf,1,0,0.0,0.0,0.0
+Interact with smartphone :: beads | smartphone | yellow paper strip,2,0,0.0,0.0,0.0
+Interact with smartphone :: cans | cereal box | shelf | smartphone,1,0,0.0,0.0,0.0
+Interact with smartphone :: cans | shelf | smartphone,4,0,0.0,0.0,0.0
+Lift pot lid :: pot | pot lid,1,0,0.0,0.0,0.0
+Manipulate adhesive strip :: adhesive strip | paper sheets | puzzle box | smartphone | water bottle,5,0,0.0,0.0,0.0
+Manipulate bead :: bead piles | container | paper strips | yellow bead,2,0,0.0,0.0,0.0
+Manipulate bead :: bead | bead piles | pen holder | table,1,0,0.0,0.0,0.0
+Manipulate bead :: bead | bead piles | table,1,0,0.0,0.0,0.0
+Manipulate beads :: blue beads | power bank | smartphone | yellow beads,2,0,0.0,0.0,0.0
+Manipulate craft paper strips :: paper strips | scissors | smartphone,8,0,0.0,0.0,0.0
+Manipulate craft piece :: craft pieces | scissors | smartphone,2,0,0.0,0.0,0.0
+Manipulate material :: blue crafting material | hand,2,0,0.0,0.0,0.0
+Manipulate paper edge :: hands | paper cone | puzzle box | smartphone | water bottle,8,0,0.0,0.0,0.0
+Manipulate paper strip :: container with tools | table | yellow paper strip,2,0,0.0,0.0,0.0
+Manipulate paper strip :: craft materials | purple paper strip | scissors | smartphone,7,0,0.0,0.0,0.0
+Manipulate paper strip :: paper cone | paper strip | puzzle box | smartphone | water bottle,2,0,0.0,0.0,0.0
+Manipulate paper strip :: purple paper strip | quilling paper pile | smartphone,3,0,0.0,0.0,0.0
+Manipulate plastic strip :: purple plastic strip | storage bin | water bottle,6,0,0.0,0.0,0.0
+Manipulate plastic strips :: desk | plastic strips | water bottle,7,0,0.0,0.0,0.0
+Manipulate puzzle pieces :: puzzle box | puzzle mat | puzzle pieces,6,0,0.0,0.0,0.0
+Manipulate yellow strip :: beads | cell phone | pen | yellow strip,2,0,0.0,0.0,0.0
+Manipulating paper strips :: beads | blue paper strip | yellow paper strip,1,0,0.0,0.0,0.0
+Marking cardboard piece :: cardboard pieces | marker | ruler | scissors,3,0,0.0,0.0,0.0
+Move dustpan to side :: dustpan,1,2,0.0,0.0,0.0
+Move marker and adjust hand :: cardboard pieces | marker,3,0,0.0,0.0,0.0
+Move phone :: cardboard | smartphone | utility knife,13,0,0.0,0.0,0.0
+Move pot :: faucet | pot | sink,1,0,0.0,0.0,0.0
+Move smartphone :: craft beads | paper strips | smartphone,3,2,0.5,0.3333333333333333,0.4
+Observe and pause :: cardboard pieces | marker | pencil case | ruler | scissors,2,0,0.0,0.0,0.0
+Open earbud case :: earbud case,3,0,0.0,0.0,0.0
+Open folded paper lantern :: cardboard box | red pleated paper lantern,4,0,0.0,0.0,0.0
+Open paper lantern component :: paper lantern component,1,0,0.0,0.0,0.0
+Open stove pot lid :: blue bowl | cloth | faucet | red bowl | sink | soap dispenser | white bowl,2,0,0.0,0.0,0.0
+Operate smartphone :: craft paper strips | folded paper fan | paper scraps | scissors | smartphone | table,1,0,0.0,0.0,0.0
+Operate smartphone :: craft paper strips | folded paper fan | smartphone,7,1,0.0,0.0,0.0
+Operate smartphone :: paper scraps | scissors | smartphone | table,2,0,0.0,0.0,0.0
+Organize cardboard pieces :: cardboard pieces | marker | pencil case | ruler | scissors,5,0,0.0,0.0,0.0
+Pick up button :: buttons | table,3,0,0.0,0.0,0.0
+Pick up items from the shopping bag :: cardboard boxes | red shopping bag | retail shelf,3,3,0.0,0.0,0.0
+Pick up new cardboard piece :: cardboard piece | marker,2,0,0.0,0.0,0.0
+Pick up packaged paper lantern component :: cardboard box | packaged paper lantern component,1,0,0.0,0.0,0.0
+Pick up smartphone :: cans | shelf | smartphone,2,0,0.0,0.0,0.0
+Pick up star bead :: cardboard squares | mobile phone | paper | pen | power bank | star beads,1,0,0.0,0.0,0.0
+Pick up utility knife :: cardboard | utility knife,4,0,0.0,0.0,0.0
+Picking up bottle :: bottle,1,0,0.0,0.0,0.0
+Picking up crafting material :: beads | smartphone | table | yellow strip,3,0,0.0,0.0,0.0
+Place and count bead :: paper | pen | star beads,4,0,0.0,0.0,0.0
+Place another canned food on shelf :: box | canned food,2,0,0.0,0.0,0.0
+Place button :: buttons | hand | smartphone | table,3,0,0.0,0.0,0.0
+Place can on shelf :: canned food | retail shelf,3,0,0.0,0.0,0.0
+Place canned food on shelf :: canned food | store shelf,1,0,0.0,0.0,0.0
+Place cloth on floor :: cloth,1,0,0.0,0.0,0.0
+Place item on shelf :: stationery package,2,0,0.0,0.0,0.0
+Place items on the shelf :: packaged items | retail shelf,4,0,0.0,0.0,0.0
+Place material :: bead design | blue crafting material | hand,1,0,0.0,0.0,0.0
+Place phone down :: beads | pencil holder | smartphone | yellow paper strip,2,0,0.0,0.0,0.0
+Place piece into puzzle :: jigsaw puzzle | puzzle piece,4,0,0.0,0.0,0.0
+Place puzzle piece :: puzzle board | puzzle piece,3,0,0.0,0.0,0.0
+Place smartphone down :: power bank | quilling paper strips | small paper stars | smartphone,1,0,0.0,0.0,0.0
+Place smartphone down :: quilling paper strips | small paper stars | smartphone,2,0,0.0,0.0,0.0
+Place smartphone on stand :: saucepan | smartphone | smartphone stand | yellow jacket,1,0,0.0,0.0,0.0
+Place towel :: pot | towel,1,0,0.0,0.0,0.0
+Placing paper strip :: adhesive strip | paper cone | phone,4,2,0.0,0.0,0.0
+Put down smartphone :: paper quilling strips | power bank | smartphone | star beads,1,0,0.0,0.0,0.0
+Put down smartphone :: paper quilling strips | smartphone | star beads,1,2,0.0,0.0,0.0
+Put down smartphone :: power bank | smartphone,1,0,0.0,0.0,0.0
+Reach for another item :: item | packaged item | shelf,1,0,0.0,0.0,0.0
+Reach for cleaning supplies :: bowls | chopping board | cleaning fluid bottle,3,0,0.0,0.0,0.0
+Reach for next canned food :: box | canned food,1,0,0.0,0.0,0.0
+Reach for next canned food :: box | canned food | retail shelf,1,0,0.0,0.0,0.0
+Reach for next item :: packaged item | shelf,1,0,0.0,0.0,0.0
+Reach for puzzle piece :: puzzle board | puzzle box | puzzle pieces,2,0,0.0,0.0,0.0
+Reach for wire hangers :: cardboard box | wire hangers,2,0,0.0,0.0,0.0
+Reach into box :: box of cans,1,0,0.0,0.0,0.0
+Release cardboard piece and gesture :: cardboard piece | cardboard piles | marker | pouch | ruler | scissors,2,0,0.0,0.0,0.0
+Release hook :: display hook,1,0,0.0,0.0,0.0
+Release lantern :: red paper lantern,2,0,0.0,0.0,0.0
+Remove paper lantern part from packaging :: paper lantern component | plastic packaging,1,0,0.0,0.0,0.0
+Remove paper lantern part from packaging :: paper lantern | red hand fan,1,0,0.0,0.0,0.0
+Remove plastic packaging :: packaging | paper lantern component,1,0,0.0,0.0,0.0
+Reposition hand :: cardboard | utility knife,3,0,0.0,0.0,0.0
+Resume observation :: cardboard pieces | marker | pencil case | ruler | scissors,2,0,0.0,0.0,0.0
+Retrieve canned food from box :: box | canned food,1,0,0.0,0.0,0.0
+Retrieve next canned food item :: canned food | cardboard box,2,0,0.0,0.0,0.0
+Retrieving more beads :: paper | pen | star beads,2,0,0.0,0.0,0.0
+Rinse cloth in sink :: cloth | sink | water faucet,2,0,0.0,0.0,0.0
+Scroll smartphone screen :: paper stars | paper strips | smartphone,2,0,0.0,0.0,0.0
+Search for puzzle piece :: jigsaw puzzle | puzzle pieces,2,0,0.0,0.0,0.0
+Secure paper edges with adhesive :: adhesive strip | paper cone pieces | puzzle box | smartphone | water bottle,3,0,0.0,0.0,0.0
+Secure paper edges with adhesive :: adhesive strip | paper cone | paper cone pieces | puzzle box | smartphone | water bottle,1,0,0.0,0.0,0.0
+Securing paper structure :: paper cone | paper strip | puzzle box | smartphone | water bottle,4,0,0.0,0.0,0.0
+Sort and adjust button line :: buttons | smartphone | table,3,0,0.0,0.0,0.0
+Sort and arrange buttons :: buttons | smartphones | soda can | table,1,0,0.0,0.0,0.0
+Sort and arrange buttons :: buttons | smartphones | table,2,0,0.0,0.0,0.0
+Sort and count beads :: cell phone | paper | pen | star beads,1,0,0.0,0.0,0.0
+Sort and count beads :: paper | pen | star beads,2,0,0.0,0.0,0.0
+Sort beads and write count :: paper | pen | power bank | smartphone | star-shaped beads,2,0,0.0,0.0,0.0
+Sort button :: buttons | cell phone,3,0,0.0,0.0,0.0
+Sort craft items :: star-shaped craft items | table,4,2,0.0,0.0,0.0
+Sort puzzle pieces :: jigsaw puzzle pieces | table,2,0,0.0,0.0,0.0
+Sort star-shaped beads :: marker | mobile phone | paper | power bank | star-shaped beads,1,0,0.0,0.0,0.0
+Stir contents :: cooking utensil | pot,1,0,0.0,0.0,0.0
+Use smartphone :: buttons | chair | smartphone | table,1,0,0.0,0.0,0.0
+Use smartphone :: buttons | smartphone | table,2,0,0.0,0.0,0.0
+Use smartphone :: charging cable | paper strips | power bank | smartphone | star-shaped paper crafts,5,0,0.0,0.0,0.0
+Walk towards shelves :: cardboard boxes | red bin | shelving unit,4,0,0.0,0.0,0.0
+Walking towards door :: door | dustpan,1,0,0.0,0.0,0.0
+Write count on paper :: marker | mobile phone | paper | power bank | star-shaped beads,1,0,0.0,0.0,0.0

results/omni_finetune/model_output_task_probes_20260616/action_object_relation/cosmos3_nano_future_window/predictions.csv ADDED Viewed

The diff for this file is too large to render. See raw diff

results/omni_finetune/model_output_task_probes_20260616/action_object_relation/qwen3_omni_v6_lora/metrics.json CHANGED Viewed

@@ -8,7 +8,7 @@
     "predictions_csv": "results/omni_finetune/model_output_task_probes_20260616/action_object_relation/qwen3_omni_v6_lora/predictions.csv"
   },
   "excluded_rows_without_true_relation": 18,
-  "generated_at_utc": "2026-06-18T20:58:29+00:00",
   "labels": [
     "Adjust canned food on shelf :: canned food | cardboard box | store shelf",
     "Adjust item on shelf :: hand | packaged item | shelf",

     "predictions_csv": "results/omni_finetune/model_output_task_probes_20260616/action_object_relation/qwen3_omni_v6_lora/predictions.csv"
   },
   "excluded_rows_without_true_relation": 18,
+  "generated_at_utc": "2026-06-18T22:52:17+00:00",
   "labels": [
     "Adjust canned food on shelf :: canned food | cardboard box | store shelf",
     "Adjust item on shelf :: hand | packaged item | shelf",

results/omni_finetune/model_output_task_probes_20260616/next_subtask_forecast/cosmos3_nano_future_window/metrics.json CHANGED Viewed

@@ -5,7 +5,7 @@
     "per_class_metrics_csv": "results/omni_finetune/model_output_task_probes_20260616/next_subtask_forecast/cosmos3_nano_future_window/per_class_metrics.csv",
     "predictions_csv": "results/omni_finetune/model_output_task_probes_20260616/next_subtask_forecast/cosmos3_nano_future_window/predictions.csv"
   },
-  "generated_at_utc": "2026-06-18T20:58:30+00:00",
   "known_limitation": "This is a retrieval-derived future-subtask score. It is not a separately prompted generative subtask head, but it is target-backed by verified future-record retrieval outputs.",
   "labels": [
     "Adjust lantern string and handle components",

     "per_class_metrics_csv": "results/omni_finetune/model_output_task_probes_20260616/next_subtask_forecast/cosmos3_nano_future_window/per_class_metrics.csv",
     "predictions_csv": "results/omni_finetune/model_output_task_probes_20260616/next_subtask_forecast/cosmos3_nano_future_window/predictions.csv"
   },
+  "generated_at_utc": "2026-06-18T22:52:18+00:00",
   "known_limitation": "This is a retrieval-derived future-subtask score. It is not a separately prompted generative subtask head, but it is target-backed by verified future-record retrieval outputs.",
   "labels": [
     "Adjust lantern string and handle components",

scripts/build_unified_task_model_radar.py CHANGED Viewed

@@ -71,6 +71,9 @@ QWEN_ACTION_OBJECT_METRICS_PATH = (
 COSMOS_SUPER_ACTION_OBJECT_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "action_object_relation/cosmos3_super_reasoner/metrics.json"
 )
 COSMOS_SUPER_TIME_TO_TRANSITION_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "time_to_transition/cosmos3_super_reasoner/metrics.json"
 )
@@ -89,6 +92,9 @@ COSMOS_NANO_MODALITY_RECONSTRUCTION_METRICS_PATH = (
 COSMOS_NANO_OBJECT_SET_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "object_set_forecast/cosmos3_nano_future_window/metrics.json"
 )
 COSMOS_NANO_TIME_TO_TRANSITION_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "time_to_transition/cosmos3_nano_future_window/metrics.json"
 )
@@ -231,6 +237,10 @@ FOUNDATION_TASK_METRICS = {
     "action_object_relation": {
         "qwen3_omni_v6_lora": "action_object_relation_macro_f1",
         "cosmos3_super_reasoner": "action_object_relation_macro_f1",
     },
     "long_horizon_next_action": {
         "cosmos3_super_reasoner": "long_horizon_next_action_macro_f1",
@@ -263,6 +273,7 @@ FOUNDATION_METRIC_PATHS = {
 FOUNDATION_METRIC_SOURCE_OVERRIDES = {
     ("qwen3_omni_v6_lora", "action_object_relation"): QWEN_ACTION_OBJECT_METRICS_PATH,
     ("cosmos3_super_reasoner", "action_object_relation"): COSMOS_SUPER_ACTION_OBJECT_METRICS_PATH,
     ("qwen3_omni_v6_lora", "caption_grounding"): QWEN_FUTURE_TASK_METRIC_PATHS["caption_grounding"],
     ("qwen3_omni_v6_lora", "cross_modal_retrieval"): QWEN_FUTURE_TASK_METRIC_PATHS["cross_modal_retrieval"],
     ("qwen3_omni_v6_lora", "temporal_order"): QWEN_FUTURE_TASK_METRIC_PATHS["temporal_order"],
@@ -275,6 +286,7 @@ FOUNDATION_METRIC_SOURCE_OVERRIDES = {
     ("cosmos3_nano_future_window", "long_horizon_next_action"): COSMOS_NANO_LONG_HORIZON_METRICS_PATH,
     ("cosmos3_nano_future_window", "next_subtask_forecast"): COSMOS_NANO_NEXT_SUBTASK_METRICS_PATH,
     ("cosmos3_nano_future_window", "modality_reconstruction"): COSMOS_NANO_MODALITY_RECONSTRUCTION_METRICS_PATH,
     ("cosmos3_nano_future_window", "object_set_forecast"): COSMOS_NANO_OBJECT_SET_METRICS_PATH,
     ("cosmos3_nano_future_window", "time_to_transition"): COSMOS_NANO_TIME_TO_TRANSITION_METRICS_PATH,
     ("cosmos3_super_reasoner", "long_horizon_next_action"): COSMOS_SUPER_LONG_HORIZON_METRICS_PATH,
@@ -312,8 +324,8 @@ METHOD_DETAILS = {
     "raw128_simple": "128-episode 4430-dim sensor NPZ simple heads; tasks 15/19 use compact proxies.",
     "raw128_neural_mlp": "128-episode 4430-dim sensor NPZ MLP heads; tasks 15/19 use compact proxies.",
     "qwen3_omni_v6_lora": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
-    "cosmos3_super_reasoner": "Verified Cosmos3-Super base-weight Reasoner JSON-task evaluation, plus task 16 and a derived task-20 action-boundary timing probe scored from existing verified JSON.",
-    "cosmos3_nano_future_window": "Verified Cosmos3-Nano future-window compatibility metrics, plus tasks 10/13/14/17 and a derived task-20 boundary timing probe scored from existing held-out future-window artifacts.",
 }
 PROXY_TASK_IDS = {"interaction_text_prediction", "camera_view_sync_retrieval"}
@@ -669,11 +681,13 @@ def build_payload() -> dict[str, Any]:
     cosmos_fd = read_json(COSMOS_SUPER_FD_METRICS_PATH)
     qwen.update(read_json(QWEN_ACTION_OBJECT_METRICS_PATH))
     cosmos_super.update(read_json(COSMOS_SUPER_ACTION_OBJECT_METRICS_PATH))
     cosmos_super.update(read_json(COSMOS_SUPER_LONG_HORIZON_METRICS_PATH))
     cosmos_super.update(read_json(COSMOS_SUPER_TIME_TO_TRANSITION_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_LONG_HORIZON_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_NEXT_SUBTASK_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_MODALITY_RECONSTRUCTION_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_OBJECT_SET_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_TIME_TO_TRANSITION_METRICS_PATH))
     foundation_task_metrics = foundation_task_metric_mapping(qwen)

 COSMOS_SUPER_ACTION_OBJECT_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "action_object_relation/cosmos3_super_reasoner/metrics.json"
 )
+COSMOS_SUPER_CAPTION_GROUNDING_METRICS_PATH = (
+    MODEL_OUTPUT_TASK_PROBE_DIR / "caption_grounding/cosmos3_super_reasoner/metrics.json"
+)
 COSMOS_SUPER_TIME_TO_TRANSITION_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "time_to_transition/cosmos3_super_reasoner/metrics.json"
 )
 COSMOS_NANO_OBJECT_SET_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "object_set_forecast/cosmos3_nano_future_window/metrics.json"
 )
+COSMOS_NANO_ACTION_OBJECT_METRICS_PATH = (
+    MODEL_OUTPUT_TASK_PROBE_DIR / "action_object_relation/cosmos3_nano_future_window/metrics.json"
+)
 COSMOS_NANO_TIME_TO_TRANSITION_METRICS_PATH = (
     MODEL_OUTPUT_TASK_PROBE_DIR / "time_to_transition/cosmos3_nano_future_window/metrics.json"
 )
     "action_object_relation": {
         "qwen3_omni_v6_lora": "action_object_relation_macro_f1",
         "cosmos3_super_reasoner": "action_object_relation_macro_f1",
+        "cosmos3_nano_future_window": "action_object_relation_macro_f1",
+    },
+    "caption_grounding": {
+        "cosmos3_super_reasoner": "caption_grounding_iou",
     },
     "long_horizon_next_action": {
         "cosmos3_super_reasoner": "long_horizon_next_action_macro_f1",
 FOUNDATION_METRIC_SOURCE_OVERRIDES = {
     ("qwen3_omni_v6_lora", "action_object_relation"): QWEN_ACTION_OBJECT_METRICS_PATH,
     ("cosmos3_super_reasoner", "action_object_relation"): COSMOS_SUPER_ACTION_OBJECT_METRICS_PATH,
+    ("cosmos3_super_reasoner", "caption_grounding"): COSMOS_SUPER_CAPTION_GROUNDING_METRICS_PATH,
     ("qwen3_omni_v6_lora", "caption_grounding"): QWEN_FUTURE_TASK_METRIC_PATHS["caption_grounding"],
     ("qwen3_omni_v6_lora", "cross_modal_retrieval"): QWEN_FUTURE_TASK_METRIC_PATHS["cross_modal_retrieval"],
     ("qwen3_omni_v6_lora", "temporal_order"): QWEN_FUTURE_TASK_METRIC_PATHS["temporal_order"],
     ("cosmos3_nano_future_window", "long_horizon_next_action"): COSMOS_NANO_LONG_HORIZON_METRICS_PATH,
     ("cosmos3_nano_future_window", "next_subtask_forecast"): COSMOS_NANO_NEXT_SUBTASK_METRICS_PATH,
     ("cosmos3_nano_future_window", "modality_reconstruction"): COSMOS_NANO_MODALITY_RECONSTRUCTION_METRICS_PATH,
+    ("cosmos3_nano_future_window", "action_object_relation"): COSMOS_NANO_ACTION_OBJECT_METRICS_PATH,
     ("cosmos3_nano_future_window", "object_set_forecast"): COSMOS_NANO_OBJECT_SET_METRICS_PATH,
     ("cosmos3_nano_future_window", "time_to_transition"): COSMOS_NANO_TIME_TO_TRANSITION_METRICS_PATH,
     ("cosmos3_super_reasoner", "long_horizon_next_action"): COSMOS_SUPER_LONG_HORIZON_METRICS_PATH,
     "raw128_simple": "128-episode 4430-dim sensor NPZ simple heads; tasks 15/19 use compact proxies.",
     "raw128_neural_mlp": "128-episode 4430-dim sensor NPZ MLP heads; tasks 15/19 use compact proxies.",
     "qwen3_omni_v6_lora": "Verified held-out Qwen3-Omni v6 LoRA metrics, plus task 16 and any completed private-GPU future-task probes scored from task-specific JSON.",
+    "cosmos3_super_reasoner": "Verified Cosmos3-Super base-weight Reasoner JSON-task evaluation, plus task 8/16 and a derived task-20 action-boundary timing probe scored from existing verified JSON.",
+    "cosmos3_nano_future_window": "Verified Cosmos3-Nano future-window compatibility metrics, plus tasks 10/13/14/16/17 and a derived task-20 boundary timing probe scored from existing held-out future-window artifacts.",
 }
 PROXY_TASK_IDS = {"interaction_text_prediction", "camera_view_sync_retrieval"}
     cosmos_fd = read_json(COSMOS_SUPER_FD_METRICS_PATH)
     qwen.update(read_json(QWEN_ACTION_OBJECT_METRICS_PATH))
     cosmos_super.update(read_json(COSMOS_SUPER_ACTION_OBJECT_METRICS_PATH))
+    cosmos_super.update(read_json(COSMOS_SUPER_CAPTION_GROUNDING_METRICS_PATH))
     cosmos_super.update(read_json(COSMOS_SUPER_LONG_HORIZON_METRICS_PATH))
     cosmos_super.update(read_json(COSMOS_SUPER_TIME_TO_TRANSITION_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_LONG_HORIZON_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_NEXT_SUBTASK_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_MODALITY_RECONSTRUCTION_METRICS_PATH))
+    cosmos_nano.update(read_json(COSMOS_NANO_ACTION_OBJECT_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_OBJECT_SET_METRICS_PATH))
     cosmos_nano.update(read_json(COSMOS_NANO_TIME_TO_TRANSITION_METRICS_PATH))
     foundation_task_metrics = foundation_task_metric_mapping(qwen)

scripts/omni/score_existing_model_output_task_probes.py CHANGED Viewed

@@ -67,7 +67,6 @@ MODEL_SPECS = {
             "results/omni_finetune/model_output_task_probes_20260616/"
             "cosmos3_nano_future_window_target_map.jsonl"
         ),
-        "action_object_relation_unsupported_reason": "verified future-window predictions do not contain object-set fields",
     },
 }
@@ -661,6 +660,263 @@ def score_cosmos_nano_object_set_from_target_map(
     return metrics
 def score_modality_reconstruction_from_feature_error(
     *,
     model_id: str,
@@ -1142,6 +1398,7 @@ def build_report(summary: dict[str, Any]) -> str:
         task16 = task_results.get("action_object_relation", {})
         task17 = task_results.get("object_set_forecast", {})
         task20 = task_results.get("time_to_transition", {})
         rows.append(
             "| "
             + " | ".join(
@@ -1175,6 +1432,11 @@ def build_report(summary: dict[str, Any]) -> str:
                         if task20.get("time_to_transition_mae") is not None
                         else "n/a"
                     ),
                     result.get("reason") or result.get("source_prediction_jsonl", ""),
                 ]
             )
@@ -1188,8 +1450,8 @@ This package scores only task targets already present in verified held-out
 prediction JSON. It does not run new inference and does not infer targets that
 are absent from a model branch.
-| Method | ID | Status | Scored tasks | Task 13 macro-F1 | Task 14 macro-F1 | Task 16 macro-F1 | Task 17 micro-F1 | Task 20 MAE | Evidence |
-| --- | --- | --- | --- | ---: | ---: | ---: | ---: | ---: | --- |
 {chr(10).join(rows)}
 """
@@ -1213,9 +1475,7 @@ def main() -> int:
             continue
         task_results: dict[str, Any] = {}
         unsupported: dict[str, str] = {}
-        if spec.get("action_object_relation_unsupported_reason"):
-            unsupported["action_object_relation"] = spec["action_object_relation_unsupported_reason"]
-        else:
             metrics = score_action_object_relation(
                 model_id=model_id,
                 spec=spec,
@@ -1230,6 +1490,21 @@ def main() -> int:
                 "action_object_relation_macro_f1": metrics["action_object_relation_macro_f1"],
                 "action_object_relation_accuracy": metrics["action_object_relation_accuracy"],
             }
         if model_id == "cosmos3_nano_future_window":
             manifest_path = workspace / spec["dataset_manifest"]
             metrics = score_cosmos_nano_long_horizon_next_action(
@@ -1278,6 +1553,20 @@ def main() -> int:
                     "object_set_forecast_precision": metrics["object_set_forecast_precision"],
                     "object_set_forecast_recall": metrics["object_set_forecast_recall"],
                 }
             metrics_path = workspace / spec["metrics_json"]
             metrics = score_modality_reconstruction_from_feature_error(
                 model_id=model_id,
@@ -1356,6 +1645,7 @@ def main() -> int:
         ),
         "task_ids_added_to_matrix": [
             "action_object_relation",
             "long_horizon_next_action",
             "modality_reconstruction",
             "next_subtask_forecast",

             "results/omni_finetune/model_output_task_probes_20260616/"
             "cosmos3_nano_future_window_target_map.jsonl"
         ),
     },
 }
     return metrics
+def score_cosmos_nano_action_object_relation_from_target_map(
+    *,
+    model_id: str,
+    spec: dict[str, Any],
+    prediction_jsonl: Path,
+    target_map_jsonl: Path,
+    output_dir: Path,
+    workspace: Path,
+) -> dict[str, Any]:
+    source_rows = read_jsonl(prediction_jsonl)
+    target_by_id = load_target_map(target_map_jsonl)
+    scored_rows: list[dict[str, Any]] = []
+    y_true: list[str] = []
+    y_pred: list[str] = []
+    missing_true_target_count = 0
+    missing_pred_target_count = 0
+    for row in source_rows:
+        future_id = str(row.get("future_record_id") or "")
+        pred_future_id = str(row.get("pred_future_record_id") or "")
+        true_target = target_by_id.get(future_id)
+        if not true_target:
+            missing_true_target_count += 1
+            continue
+        pred_target = target_by_id.get(pred_future_id)
+        if not pred_target:
+            missing_pred_target_count += 1
+        true_relation = relation_label(true_target.get("action"), true_target.get("objects"))
+        if true_relation is None:
+            continue
+        pred_relation = relation_label(
+            pred_target.get("action") if pred_target else None,
+            pred_target.get("objects") if pred_target else None,
+            missing_label=MISSING_PRED_RELATION,
+        )
+        y_true.append(true_relation)
+        y_pred.append(pred_relation or MISSING_PRED_RELATION)
+        scored_rows.append(
+            {
+                "id": row.get("id"),
+                "split": row.get("split"),
+                "episode_id": row.get("episode_id"),
+                "future_record_id": future_id,
+                "pred_future_record_id": pred_future_id,
+                "true_relation": true_relation,
+                "pred_relation": pred_relation,
+                "correct": int(true_relation == pred_relation),
+                "rank": row.get("rank"),
+                "top_k_hit": row.get("top_k_hit"),
+            }
+        )
+    if not y_true:
+        raise RuntimeError(f"no joined future action-object relation targets found in {prediction_jsonl}")
+    label_options = sorted(set(y_true))
+    metrics, per_class, _ = class_metrics(y_true, y_pred, label_options)
+    metrics.update(
+        {
+            "title": f"{spec['label']} Future Action-Object Relation Probe",
+            "status": "pass",
+            "generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
+            "model_id": model_id,
+            "model_label": spec["label"],
+            "task_id": "action_object_relation",
+            "task_number": 16,
+            "task_label": "Action-Object Relation",
+            "metric_key": "action_object_relation_macro_f1",
+            "primary_metric": "action_object_relation_macro_f1",
+            "primary_score": metrics["macro_f1"],
+            "action_object_relation_macro_f1": metrics["macro_f1"],
+            "action_object_relation_accuracy": metrics["accuracy"],
+            "source_prediction_jsonl": relpath(prediction_jsonl, workspace),
+            "source_target_map_jsonl": relpath(target_map_jsonl, workspace),
+            "scope": "held_out_test_existing_future_window_retrieval_probe",
+            "score_policy": (
+                "Derived from existing verified held-out Cosmos3-Nano future-window predictions. "
+                "The true future record and retrieved future record are joined to the public-safe "
+                "target map, then scored on the action plus object-set relation."
+            ),
+            "normalization_policy": (
+                "Action text is whitespace-normalized. Objects are casefolded, deduplicated, "
+                "sorted, and joined into a canonical relation label before macro-F1 scoring."
+            ),
+            "known_limitation": (
+                "This is a retrieval-derived future relation score, not a separately prompted "
+                "action-object generation head."
+            ),
+            "total_prediction_rows": len(source_rows),
+            "target_map_rows": len(target_by_id),
+            "scored_rows": len(scored_rows),
+            "missing_true_target_count": missing_true_target_count,
+            "missing_pred_target_count": missing_pred_target_count,
+            "artifact_files": {
+                "metrics_json": relpath(output_dir / "metrics.json", workspace),
+                "predictions_csv": relpath(output_dir / "predictions.csv", workspace),
+                "per_class_metrics_csv": relpath(output_dir / "per_class_metrics.csv", workspace),
+            },
+        }
+    )
+    write_json(output_dir / "metrics.json", metrics)
+    write_csv(
+        output_dir / "predictions.csv",
+        scored_rows,
+        [
+            "id",
+            "split",
+            "episode_id",
+            "future_record_id",
+            "pred_future_record_id",
+            "true_relation",
+            "pred_relation",
+            "correct",
+            "rank",
+            "top_k_hit",
+        ],
+    )
+    write_csv(
+        output_dir / "per_class_metrics.csv",
+        per_class,
+        ["class_name", "support", "predicted", "precision", "recall", "f1"],
+    )
+    return metrics
+def parse_window(value: Any) -> tuple[float, float] | None:
+    if not isinstance(value, dict):
+        return None
+    try:
+        start = float(value.get("start_frame"))
+        end = float(value.get("end_frame"))
+    except (TypeError, ValueError):
+        return None
+    if end < start:
+        return None
+    return start, end
+def interval_iou(a: tuple[float, float], b: tuple[float, float]) -> float:
+    inter = max(0.0, min(a[1], b[1]) - max(a[0], b[0]) + 1.0)
+    union = max(a[1], b[1]) - min(a[0], b[0]) + 1.0
+    return inter / union if union > 0 else 0.0
+def score_caption_grounding_from_evidence_window(
+    *,
+    model_id: str,
+    spec: dict[str, Any],
+    prediction_jsonl: Path,
+    output_dir: Path,
+    workspace: Path,
+) -> dict[str, Any]:
+    source_rows = read_jsonl(prediction_jsonl)
+    scored_rows: list[dict[str, Any]] = []
+    ious: list[float] = []
+    center_hits = 0
+    within_20_hits = 0
+    missing_pred_count = 0
+    for row in source_rows:
+        true_json = row.get("true_json") if isinstance(row.get("true_json"), dict) else {}
+        pred_json = row.get("pred_json") if isinstance(row.get("pred_json"), dict) else {}
+        true_window = parse_window(true_json.get("evidence_window"))
+        if true_window is None:
+            continue
+        pred_window = parse_window(pred_json.get("evidence_window"))
+        if pred_window is None:
+            missing_pred_count += 1
+            iou = 0.0
+            pred_center = None
+            center_error = None
+        else:
+            iou = interval_iou(true_window, pred_window)
+            pred_center = (pred_window[0] + pred_window[1]) / 2.0
+            true_center = (true_window[0] + true_window[1]) / 2.0
+            center_error = abs(pred_center - true_center)
+            center_hits += int(true_window[0] <= pred_center <= true_window[1])
+            within_20_hits += int(center_error <= 20.0)
+        ious.append(iou)
+        scored_rows.append(
+            {
+                "id": row.get("id"),
+                "split": row.get("split"),
+                "episode_id": row.get("episode_id"),
+                "true_start_frame": true_window[0],
+                "true_end_frame": true_window[1],
+                "pred_start_frame": pred_window[0] if pred_window else None,
+                "pred_end_frame": pred_window[1] if pred_window else None,
+                "pred_center_frame": pred_center,
+                "center_error_frames": center_error,
+                "iou": iou,
+            }
+        )
+    if not scored_rows:
+        raise RuntimeError(f"no evidence-window targets found in {prediction_jsonl}")
+    mean_iou = sum(ious) / len(ious)
+    center_hit_rate = center_hits / len(scored_rows)
+    within_20_rate = within_20_hits / len(scored_rows)
+    metrics = {
+        "title": f"{spec['label']} Evidence-Window Grounding Probe",
+        "status": "pass",
+        "generated_at_utc": datetime.now(timezone.utc).isoformat(timespec="seconds"),
+        "model_id": model_id,
+        "model_label": spec["label"],
+        "task_id": "caption_grounding",
+        "task_number": 8,
+        "task_label": "Language Grounding",
+        "metric_key": "caption_grounding_iou",
+        "primary_metric": "caption_grounding_iou",
+        "primary_score": mean_iou,
+        "caption_grounding_iou": mean_iou,
+        "caption_grounding_center_hit_rate": center_hit_rate,
+        "caption_grounding_within_20_frames": within_20_rate,
+        "source_prediction_jsonl": relpath(prediction_jsonl, workspace),
+        "scope": "held_out_test_existing_verified_prediction_json",
+        "score_policy": (
+            "Derived from existing verified held-out structured JSON predictions. The task target is "
+            "the evidence_window field already present in the true JSON; missing or invalid predicted "
+            "evidence windows receive zero IoU."
+        ),
+        "normalization_policy": (
+            "Evidence windows are frame intervals. The primary score is mean interval IoU; center-hit "
+            "and within-20-frame rates are reported as diagnostics."
+        ),
+        "known_limitation": (
+            "This is an evidence-window localization score, not a candidate-set retrieval MRR."
+        ),
+        "total_prediction_rows": len(source_rows),
+        "scored_rows": len(scored_rows),
+        "missing_pred_evidence_window_count": missing_pred_count,
+        "artifact_files": {
+            "metrics_json": relpath(output_dir / "metrics.json", workspace),
+            "predictions_csv": relpath(output_dir / "predictions.csv", workspace),
+        },
+    }
+    write_json(output_dir / "metrics.json", metrics)
+    write_csv(
+        output_dir / "predictions.csv",
+        scored_rows,
+        [
+            "id",
+            "split",
+            "episode_id",
+            "true_start_frame",
+            "true_end_frame",
+            "pred_start_frame",
+            "pred_end_frame",
+            "pred_center_frame",
+            "center_error_frames",
+            "iou",
+        ],
+    )
+    return metrics
 def score_modality_reconstruction_from_feature_error(
     *,
     model_id: str,
         task16 = task_results.get("action_object_relation", {})
         task17 = task_results.get("object_set_forecast", {})
         task20 = task_results.get("time_to_transition", {})
+        task8 = task_results.get("caption_grounding", {})
         rows.append(
             "| "
             + " | ".join(
                         if task20.get("time_to_transition_mae") is not None
                         else "n/a"
                     ),
+                    (
+                        f"{task8.get('caption_grounding_iou', 0.0):.6f}"
+                        if task8.get("caption_grounding_iou") is not None
+                        else "n/a"
+                    ),
                     result.get("reason") or result.get("source_prediction_jsonl", ""),
                 ]
             )
 prediction JSON. It does not run new inference and does not infer targets that
 are absent from a model branch.
+| Method | ID | Status | Scored tasks | Task 13 macro-F1 | Task 14 macro-F1 | Task 16 macro-F1 | Task 17 micro-F1 | Task 20 MAE | Task 8 IoU | Evidence |
+| --- | --- | --- | --- | ---: | ---: | ---: | ---: | ---: | ---: | --- |
 {chr(10).join(rows)}
 """
             continue
         task_results: dict[str, Any] = {}
         unsupported: dict[str, str] = {}
+        if model_id != "cosmos3_nano_future_window":
             metrics = score_action_object_relation(
                 model_id=model_id,
                 spec=spec,
                 "action_object_relation_macro_f1": metrics["action_object_relation_macro_f1"],
                 "action_object_relation_accuracy": metrics["action_object_relation_accuracy"],
             }
+        if model_id == "cosmos3_super_reasoner":
+            metrics = score_caption_grounding_from_evidence_window(
+                model_id=model_id,
+                spec=spec,
+                prediction_jsonl=prediction_path,
+                output_dir=output_dir / "caption_grounding" / model_id,
+                workspace=workspace,
+            )
+            task_results["caption_grounding"] = {
+                "source_metrics_json": metrics["artifact_files"]["metrics_json"],
+                "scored_rows": metrics["scored_rows"],
+                "caption_grounding_iou": metrics["caption_grounding_iou"],
+                "caption_grounding_center_hit_rate": metrics["caption_grounding_center_hit_rate"],
+                "missing_pred_evidence_window_count": metrics["missing_pred_evidence_window_count"],
+            }
         if model_id == "cosmos3_nano_future_window":
             manifest_path = workspace / spec["dataset_manifest"]
             metrics = score_cosmos_nano_long_horizon_next_action(
                     "object_set_forecast_precision": metrics["object_set_forecast_precision"],
                     "object_set_forecast_recall": metrics["object_set_forecast_recall"],
                 }
+                metrics = score_cosmos_nano_action_object_relation_from_target_map(
+                    model_id=model_id,
+                    spec=spec,
+                    prediction_jsonl=prediction_path,
+                    target_map_jsonl=target_map_path,
+                    output_dir=output_dir / "action_object_relation" / model_id,
+                    workspace=workspace,
+                )
+                task_results["action_object_relation"] = {
+                    "source_metrics_json": metrics["artifact_files"]["metrics_json"],
+                    "scored_rows": metrics["scored_rows"],
+                    "action_object_relation_macro_f1": metrics["action_object_relation_macro_f1"],
+                    "action_object_relation_accuracy": metrics["action_object_relation_accuracy"],
+                }
             metrics_path = workspace / spec["metrics_json"]
             metrics = score_modality_reconstruction_from_feature_error(
                 model_id=model_id,
         ),
         "task_ids_added_to_matrix": [
             "action_object_relation",
+            "caption_grounding",
             "long_horizon_next_action",
             "modality_reconstruction",
             "next_subtask_forecast",