Add model citation and fine-tuning dataset note

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by smojitoy - opened
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  1. README.md +24 -15
README.md CHANGED
@@ -157,9 +157,11 @@ pose_labels/
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  or as a CSV with `image_path, pose` columns. Class counts are inherently imbalanced and are handled at the sampler level (see below).
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- More detail is provided in the [training dataset repository](https://huggingface.co/datasets/imageomics/mmla-pose).
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- [More Information Needed — exact per-class sample counts, splits, and dataset card link]
 
 
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  ### Training Procedure
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@@ -303,27 +305,34 @@ Training objective: cross-entropy with label smoothing (0.1), optimized only ove
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  ## Citation
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- [More Information Needed]
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-
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- <!--
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- If you use our model in your work, please cite the model and any associated paper.
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  **Model**
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- ```
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- @software{<ref_code>,
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- author = {<author1 and author2>},
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- doi = {<doi once generated>},
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- title = {DINOv2 8-Class Animal Pose Classifier},
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- version = {<version#>},
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  year = {2026},
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- url = {https://huggingface.co/imageomics/mmla-dino-pose}
 
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  }
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  ```
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- -->
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- Underlying backbone:
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  ```
 
 
 
 
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  @article{oquab2023dinov2,
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  title = {DINOv2: Learning Robust Visual Features without Supervision},
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  author = {Oquab, Maxime and Darcet, Timoth{\'e}e and Moutakanni, Th{\'e}o and Vo, Huy V. and Szafraniec, Marc and Khalidov, Vasil and Fernandez, Pierre and Haziza, Daniel and Massa, Francisco and El-Nouby, Alaaeldin and others},
 
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  or as a CSV with `image_path, pose` columns. Class counts are inherently imbalanced and are handled at the sampler level (see below).
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+ This model was fine-tuned on the MMLA pose dataset:
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+ - Dataset: [imageomics/mmla-pose](https://huggingface.co/datasets/imageomics/mmla-pose)
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+
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+ The dataset contains cropped images of zebras from MMLA drone footage labeled with one of eight pose orientations: front, front-left, front-right, left, back-left, back, back-right, and right.
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  ### Training Procedure
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  ## Citation
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+ If you use this model, please cite this model repository, the MMLA pose dataset, the associated CV4Animals workshop paper, and the underlying DINOv2 backbone.
 
 
 
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  **Model**
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+
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+ ```bibtex
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+ @software{imageomics_mmla_dino_pose_2026,
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+ author = {Sun, Claire and Kline, Jenna and Pillai, Bharath and Berger-Wolf, Tanya},
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+ title = {MMLA DINOv2 8-Class Animal Pose Classifier},
 
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  year = {2026},
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+ url = {https://huggingface.co/imageomics/mmla-dino-pose},
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+ note = {Fine-tuned on the MMLA pose dataset: https://huggingface.co/datasets/imageomics/mmla-pose}
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  }
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  ```
 
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+ **Dataset**
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+ Please also cite the MMLA pose dataset:
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+ ```bibtex
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+ @dataset{imageomics_mmla_pose_2026,
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+ title = {MMLA Pose Dataset},
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+ year = {2026},
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+ url = {https://huggingface.co/datasets/imageomics/mmla-pose}
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+ }
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  ```
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+
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+ **Underlying backbone**
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+
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+ ```bibtex
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  @article{oquab2023dinov2,
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  title = {DINOv2: Learning Robust Visual Features without Supervision},
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  author = {Oquab, Maxime and Darcet, Timoth{\'e}e and Moutakanni, Th{\'e}o and Vo, Huy V. and Szafraniec, Marc and Khalidov, Vasil and Fernandez, Pierre and Haziza, Daniel and Massa, Francisco and El-Nouby, Alaaeldin and others},