ShoppingBench SN15: Trajectory Primitive
Collection
Datasets + distilled Qwen3-4B models from the ORO Subnet 15 trajectory-primitive paper (raw/filtered corpora, SFT, rejection, SFT+KTO). • 6 items • Updated
Datasets:
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
messages: list<item: struct<role: string, content: string, tool_calls: list<item: struct<function: struct<name (... 403 chars omitted)
child 0, item: struct<role: string, content: string, tool_calls: list<item: struct<function: struct<name: string, a (... 391 chars omitted)
child 0, role: string
child 1, content: string
child 2, tool_calls: list<item: struct<function: struct<name: string, arguments: struct<q: string, price: string, page: i (... 304 chars omitted)
child 0, item: struct<function: struct<name: string, arguments: struct<q: string, price: string, page: int64, produ (... 292 chars omitted)
child 0, function: struct<name: string, arguments: struct<q: string, price: string, page: int64, product_ids: string, s (... 248 chars omitted)
child 0, name: string
child 1, arguments: struct<q: string, price: string, page: int64, product_ids: string, status: string, service: string, (... 215 chars omitted)
child 0, q: string
child 1, price: string
child 2, page: int64
child 3, product_ids: string
child 4, status: string
child 5, service: string
child 6, sort: string
child 7, product_queries: string
child 8, shop_id: string
child 9, product_id: string
child 10,
...
description: string
child 1, name: string
child 2, parameters: struct<additionalProperties: bool, properties: struct<page: struct<type: string>, price: struct<type (... 267 chars omitted)
child 0, additionalProperties: bool
child 1, properties: struct<page: struct<type: string>, price: struct<type: string>, q: struct<type: string>, query: stru (... 205 chars omitted)
child 0, page: struct<type: string>
child 0, type: string
child 1, price: struct<type: string>
child 0, type: string
child 2, q: struct<type: string>
child 0, type: string
child 3, query: struct<type: string>
child 0, type: string
child 4, service: struct<type: string>
child 0, type: string
child 5, shop_id: struct<type: string>
child 0, type: string
child 6, sort: struct<type: string>
child 0, type: string
child 7, product_id: struct<type: string>
child 0, type: string
child 8, product_ids: struct<items: struct<type: string>, type: string>
child 0, items: struct<type: string>
child 0, type: string
child 1, type: string
child 2, type: string
child 3, type: string
trac_export_version: string
problem_id: string
_reward_components: null
_gap: null
to
{'problem_id': Value('string'), '_gap': Value('null'), '_reward_components': Value('null')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1816, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 310, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 130, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
messages: list<item: struct<role: string, content: string, tool_calls: list<item: struct<function: struct<name (... 403 chars omitted)
child 0, item: struct<role: string, content: string, tool_calls: list<item: struct<function: struct<name: string, a (... 391 chars omitted)
child 0, role: string
child 1, content: string
child 2, tool_calls: list<item: struct<function: struct<name: string, arguments: struct<q: string, price: string, page: i (... 304 chars omitted)
child 0, item: struct<function: struct<name: string, arguments: struct<q: string, price: string, page: int64, produ (... 292 chars omitted)
child 0, function: struct<name: string, arguments: struct<q: string, price: string, page: int64, product_ids: string, s (... 248 chars omitted)
child 0, name: string
child 1, arguments: struct<q: string, price: string, page: int64, product_ids: string, status: string, service: string, (... 215 chars omitted)
child 0, q: string
child 1, price: string
child 2, page: int64
child 3, product_ids: string
child 4, status: string
child 5, service: string
child 6, sort: string
child 7, product_queries: string
child 8, shop_id: string
child 9, product_id: string
child 10,
...
description: string
child 1, name: string
child 2, parameters: struct<additionalProperties: bool, properties: struct<page: struct<type: string>, price: struct<type (... 267 chars omitted)
child 0, additionalProperties: bool
child 1, properties: struct<page: struct<type: string>, price: struct<type: string>, q: struct<type: string>, query: stru (... 205 chars omitted)
child 0, page: struct<type: string>
child 0, type: string
child 1, price: struct<type: string>
child 0, type: string
child 2, q: struct<type: string>
child 0, type: string
child 3, query: struct<type: string>
child 0, type: string
child 4, service: struct<type: string>
child 0, type: string
child 5, shop_id: struct<type: string>
child 0, type: string
child 6, sort: struct<type: string>
child 0, type: string
child 7, product_id: struct<type: string>
child 0, type: string
child 8, product_ids: struct<items: struct<type: string>, type: string>
child 0, items: struct<type: string>
child 0, type: string
child 1, type: string
child 2, type: string
child 3, type: string
trac_export_version: string
problem_id: string
_reward_components: null
_gap: null
to
{'problem_id': Value('string'), '_gap': Value('null'), '_reward_components': Value('null')}
because column names don't match
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1348, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 890, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 951, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1683, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1869, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
problem_id string | _gap null | _reward_components null |
|---|---|---|
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
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069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
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069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
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069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
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069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
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069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
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069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
069dd149-19f1-7eb4-8000-7a4861c44f27 | null | null |
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069dd149-1b42-7fdd-8000-ddb5438f1dab | null | null |
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069dd149-1b42-7fdd-8000-ddb5438f1dab | null | null |
End of preview.
ShoppingBench SN15 SFT Corpus (15K filtered + 2.7K eval holdout)
Paper: arXiv:2606.10064
Code: https://github.com/ORO-AI/shoppingbench-trajectory-primitive
The filtered, leak-cluster-guarded SFT corpus from the paper Bittensor Agent Arenas as a Trajectory Primitive: Distilling a Shopping Agent from ShoppingBench Subnet Traces. This is the trainable corpus produced by the structural-quality filter from the raw 18K race traces (oro-ai/sn15-shoppingbench-traces-18k).
Post-training Qwen3-4B on this corpus lifts ShoppingBench ASR from the published 18.0% base to 42.7% on a leak-cluster-guarded held-out partition scored production-strict.
Contents
| File | Rows | Description |
|---|---|---|
oro_sft_15k_v0.jsonl |
15,269 | Train. Leak-cluster-clean SFT corpus, NeMo SFT OpenAI format |
oro_sft_eval_v0.jsonl |
2,676 | Eval holdout. Leak-cluster-clean, anti-memorised |
oro_sft_15k_metadata_v0.jsonl |
15,269 | Train metadata sidecar (problem_id, gap, reward components). Not for training |
oro_sft_eval_metadata_v0.jsonl |
2,676 | Eval metadata sidecar |
leak_cluster_audit_v0.json |
- | Train/eval product-ID intersection audit (empty intersection) |
oro_sft_funnel_v0.json |
- | Per-stage filter counts |
The leak-cluster guard
The key value-add over the raw 18K traces: the filter drops trajectories whose recommended product_ids appear in the eval-side ground truth. Without it, held-out eval numbers would be contaminated by trajectories that effectively memorise eval answers. leak_cluster_audit_v0.json records the train/eval intersection (empty).
Format
NeMo SFT OpenAI shape, <think> stripped (keep_think=False):
{"messages": [...], "tools": [...4 tool schemas...], "task_name": "trac_shoppingbench_sft", "trac_export_version": "trac-nemo-sft-openai-v0.1-oro-converted"}
License
CC BY 4.0. Please cite the paper if you use this corpus.
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