Update OpenWhistle links, citation, and authorship

README.md

@@ -8,6 +8,8 @@ configs:
     path: data/validation-*
   - split: test
     path: data/test-*
+tags:
+- arxiv:2609.34839
 ---
 
 # OpenWhistle Detection Finetuning
@@ -69,6 +71,29 @@ Expert-annotated whistle-type detection dataset for OpenWhistle. Each example is
 ```python
 from datasets import Audio, load_dataset
 
-dataset = load_dataset("OpenWhistleNeurIPS26/OpenWhistle-Detection-Finetuning")
+dataset = load_dataset("dolphinteam/OpenWhistle-Detection-Finetuning")
 decoded_train = dataset["train"].cast_column("audio", Audio())
 sample = decoded_train[0]
+```
+
+## Paper, collection, and authors
+
+- Paper: [OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations](https://arxiv.org/abs/2609.34839)
+- Hugging Face collection: [NeurIPS 2026 OpenWhistle](https://huggingface.co/collections/dolphinteam/neurips26-openwhistle)
+- This repository: [https://huggingface.co/datasets/dolphinteam/OpenWhistle-Detection-Finetuning](https://huggingface.co/datasets/dolphinteam/OpenWhistle-Detection-Finetuning)
+
+Authors: Faadil Mustun, Chiara Semenzin, Roberto Dessi, Pablo Robin Guerrero, Pierre Orhan, Alexis Emanuelli, Emanuele Rossi, Yair Lakretz, Gonzalo de Polavieja, and German Sumbre.
+
+## Citation
+
+```bibtex
+@misc{mustun2026openwhistle,
+  title         = {OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations},
+  author        = {Mustun, Faadil and Semenzin, Chiara and Dessi, Roberto and Robin Guerrero, Pablo and Orhan, Pierre and Emanuelli, Alexis and Rossi, Emanuele and Lakretz, Yair and de Polavieja, Gonzalo and Sumbre, German},
+  year          = {2026},
+  eprint        = {2609.34839},
+  archivePrefix = {arXiv},
+  primaryClass  = {cs.CL},
+  url           = {https://arxiv.org/abs/2609.34839}
+}
+```

croissant_rai_OpenWhistle-Detection-Finetuning.json

@@ -54,25 +54,66 @@
   ],
   "name": "OpenWhistle-Detection-Finetuning",
   "alternateName": [
-    "OpenWhistleNeurIPS26/OpenWhistle-Detection-Finetuning"
+    "dolphinteam/OpenWhistle-Detection-Finetuning"
   ],
   "description": "OpenWhistle Detection Finetuning is a public whistle-type detection finetuning dataset. It contains 5,600 fixed-length audio windows with audio, a seven-dimensional multi-label whistle-type target vector, a derived binary whistle/noise label, original source labels, and original clip filenames. Background/no-whistle windows are represented by an all-zero target vector. The train/validation/test split is session-disjoint, uses ratios 0.70/0.15/0.15, and is exactly balanced across whistle-type source labels and background examples within each split.",
-  "url": "https://huggingface.co/datasets/OpenWhistleNeurIPS26/OpenWhistle-Detection-Finetuning",
-  "citeAs": "OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations. NeurIPS 2026 anonymous submission.",
-  "creator": {
-    "@type": "Organization",
-    "name": "Anonymous NeurIPS 2026 authors",
-    "url": "https://huggingface.co/OpenWhistleNeurIPS26"
-  },
+  "url": "https://huggingface.co/datasets/dolphinteam/OpenWhistle-Detection-Finetuning",
+  "citeAs": "Faadil Mustun, Chiara Semenzin, Roberto Dessi, Pablo Robin Guerrero, Pierre Orhan, Alexis Emanuelli, Emanuele Rossi, Yair Lakretz, Gonzalo de Polavieja, and German Sumbre. OpenWhistle: A Large-Scale Longitudinal Dataset and Benchmark of Bottlenose Dolphin Vocalizations. NeurIPS 2026 Datasets & Evaluations Track (Spotlight), arXiv:2609.34839. https://arxiv.org/abs/2609.34839",
+  "creator": [
+    {
+      "@type": "Person",
+      "name": "Faadil Mustun"
+    },
+    {
+      "@type": "Person",
+      "name": "Chiara Semenzin"
+    },
+    {
+      "@type": "Person",
+      "name": "Roberto Dessi"
+    },
+    {
+      "@type": "Person",
+      "name": "Pablo Robin Guerrero"
+    },
+    {
+      "@type": "Person",
+      "name": "Pierre Orhan"
+    },
+    {
+      "@type": "Person",
+      "name": "Alexis Emanuelli"
+    },
+    {
+      "@type": "Person",
+      "name": "Emanuele Rossi"
+    },
+    {
+      "@type": "Person",
+      "name": "Yair Lakretz"
+    },
+    {
+      "@type": "Person",
+      "name": "Gonzalo de Polavieja"
+    },
+    {
+      "@type": "Person",
+      "name": "German Sumbre"
+    }
+  ],
   "publisher": {
     "@type": "Organization",
-    "name": "OpenWhistleNeurIPS26",
-    "url": "https://huggingface.co/OpenWhistleNeurIPS26"
+    "name": "Dolphin Team",
+    "url": "https://huggingface.co/dolphinteam"
   },
   "datePublished": "2026-04-22",
-  "dateModified": "2026-04-26",
+  "dateModified": "2026-09-29",
   "license": "https://creativecommons.org/licenses/by/4.0/",
-  "identifier": "https://huggingface.co/datasets/OpenWhistleNeurIPS26/OpenWhistle-Detection-Finetuning",
+  "identifier": "https://huggingface.co/datasets/dolphinteam/OpenWhistle-Detection-Finetuning",
+  "sameAs": [
+    "https://arxiv.org/abs/2609.34839",
+    "https://huggingface.co/collections/dolphinteam/neurips26-openwhistle"
+  ],
   "keywords": [
     "dolphin",
     "bioacoustics",
@@ -97,7 +138,7 @@
       "@id": "repo",
       "name": "repo",
       "description": "The Hugging Face git repository containing the dataset parquet conversion.",
-      "contentUrl": "https://huggingface.co/datasets/OpenWhistleNeurIPS26/OpenWhistle-Detection-Finetuning/tree/refs%2Fconvert%2Fparquet",
+      "contentUrl": "https://huggingface.co/datasets/dolphinteam/OpenWhistle-Detection-Finetuning/tree/refs%2Fconvert%2Fparquet",
       "encodingFormat": "git+https",
       "sha256": "https://github.com/mlcommons/croissant/issues/80"
     },
@@ -265,15 +306,15 @@
   "rai:personalSensitiveInformation": "[\"No human subjects are involved in the dataset. Public columns contain animal audio clips, binary/source labels, original clip filenames, and source-label tensors.\", \"The data consists of underwater animal acoustic recordings. Users should nevertheless treat incidental non-target sounds as possible and avoid attempts to infer people, vessels, precise locations, or sensitive field-site details from the audio or filenames.\"]",
   "rai:dataSocialImpact": "The dataset supports open research on passive acoustic monitoring, dolphin bioacoustics, and non-invasive whistle-type detection. Positive impacts include reproducible evaluation of whistle-type detectors and improved tooling for animal communication research. Misuse risks include deploying detectors in new sites without local validation, treating benchmark detection as proof of ecological or behavioral conclusions, or ignoring source-label-specific failure modes hidden by aggregate metrics. The original data collection was passive and non-invasive, did not interfere with dolphin behavior, and involved no human subjects.",
   "rai:hasSyntheticData": false,
-  "rai:dataReleaseMaintenancePlan": "The dataset is hosted publicly on Hugging Face under OpenWhistleNeurIPS26/OpenWhistle-Detection-Finetuning and released under CC-BY 4.0. The release documents the exact session-disjoint split, source-label balancing, seed, and leakage checks. Future OpenWhistle releases may expand detection coverage, labels, contextual metadata, or evaluation protocols.",
+  "rai:dataReleaseMaintenancePlan": "The dataset is hosted publicly on Hugging Face under dolphinteam/OpenWhistle-Detection-Finetuning and released under CC-BY 4.0. The release documents the exact session-disjoint split, source-label balancing, seed, and leakage checks. Future OpenWhistle releases may expand detection coverage, labels, contextual metadata, or evaluation protocols.",
   "prov:wasDerivedFrom": [
     {
-      "@id": "urn:openwhistle:detection-source-recordings-and-clips:anonymous-neurips-2026",
+      "@id": "urn:openwhistle:detection-source-recordings-and-clips:neurips-2026",
       "prov:label": "OpenWhistle curated detection clips and passive acoustic source recordings",
       "sc:license": "https://creativecommons.org/licenses/by/4.0/",
       "prov:wasAttributedTo": {
-        "@id": "anonymous_openwhistle_authors",
-        "prov:label": "Anonymous OpenWhistle authors"
+        "@id": "openwhistle_authors",
+        "prov:label": "OpenWhistle authors"
       }
     }
   ],
@@ -288,9 +329,9 @@
       "prov:wasAttributedTo": [
         {
           "@type": "prov:Agent",
-          "@id": "anonymous_openwhistle_authors",
-          "prov:label": "Anonymous OpenWhistle authors",
-          "sc:description": "Anonymous research team responsible for the OpenWhistle data release and documentation during double-blind review."
+          "@id": "openwhistle_authors",
+          "prov:label": "OpenWhistle authors",
+          "sc:description": "OpenWhistle research team responsible for the OpenWhistle data release and documentation."
         }
       ]
     },
@@ -304,9 +345,9 @@
       "prov:wasAttributedTo": [
         {
           "@type": "prov:Agent",
-          "@id": "anonymous_openwhistle_authors",
-          "prov:label": "Anonymous OpenWhistle authors",
-          "sc:description": "Anonymous research team responsible for curation and whistle-type target encoding during double-blind review."
+          "@id": "openwhistle_authors",
+          "prov:label": "OpenWhistle authors",
+          "sc:description": "OpenWhistle research team responsible for curation and whistle-type target encoding."
         }
       ]
     },
@@ -332,9 +373,9 @@
         },
         {
           "@type": "prov:Agent",
-          "@id": "anonymous_openwhistle_authors",
-          "prov:label": "Anonymous OpenWhistle authors",
-          "sc:description": "Anonymous research team responsible for preprocessing, curation, and release during double-blind review."
+          "@id": "openwhistle_authors",
+          "prov:label": "OpenWhistle authors",
+          "sc:description": "OpenWhistle research team responsible for preprocessing, curation, and release."
         }
       ]
     },
@@ -348,11 +389,11 @@
       "prov:wasAttributedTo": [
         {
           "@type": "prov:Agent",
-          "@id": "anonymous_openwhistle_authors",
-          "prov:label": "Anonymous OpenWhistle authors",
-          "sc:description": "Anonymous research team responsible for split audit and release artifacts."
+          "@id": "openwhistle_authors",
+          "prov:label": "OpenWhistle authors",
+          "sc:description": "OpenWhistle research team responsible for split audit and release artifacts."
         }
       ]
     }
   ]
-}
+}