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README.md

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+---
+license: apache-2.0
+dataset_info:
+- config_name: human_object_interactions
+  features:
+  - name: video_id
+    dtype: string
+  - name: video_path
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answer
+    dtype: string
+  - name: candidates
+    dtype: string
+  - name: source
+    dtype: string
+  splits:
+  - name: mini
+    num_bytes: 1749322
+    num_examples: 5724
+  - name: full
+    num_bytes: 4074313
+    num_examples: 14046
+  download_size: 594056
+  dataset_size: 5823635
+- config_name: intuitive_physics
+  features:
+  - name: video_id
+    dtype: string
+  - name: video_path
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answer
+    dtype: string
+  - name: candidates
+    dtype: string
+  - name: source
+    dtype: string
+  splits:
+  - name: mini
+    num_bytes: 6999824
+    num_examples: 8680
+  - name: full
+    num_bytes: 10570407
+    num_examples: 12220
+  download_size: 805372
+  dataset_size: 17570231
+- config_name: robot_object_interactions
+  features:
+  - name: video_id
+    dtype: string
+  - name: video_path
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answer
+    dtype: string
+  - name: candidates
+    dtype: string
+  - name: source
+    dtype: string
+  splits:
+  - name: mini
+    num_bytes: 771052
+    num_examples: 2000
+  - name: full
+    num_bytes: 9954084
+    num_examples: 25796
+  download_size: 1547348
+  dataset_size: 10725136
+- config_name: temporal_reasoning
+  features:
+  - name: video_id
+    dtype: string
+  - name: video_path
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answer
+    dtype: string
+  - name: candidates
+    dtype: string
+  - name: source
+    dtype: string
+  splits:
+  - name: mini
+    num_bytes: 611241
+    num_examples: 2012
+  - name: full
+    num_bytes: 783157
+    num_examples: 2766
+  download_size: 254438
+  dataset_size: 1394398
+configs:
+- config_name: human_object_interactions
+  data_files:
+  - split: mini
+    path: human_object_interactions/mini-*
+  - split: full
+    path: human_object_interactions/full-*
+- config_name: intuitive_physics
+  data_files:
+  - split: mini
+    path: intuitive_physics/mini-*
+  - split: full
+    path: intuitive_physics/full-*
+- config_name: robot_object_interactions
+  data_files:
+  - split: mini
+    path: robot_object_interactions/mini-*
+  - split: full
+    path: robot_object_interactions/full-*
+- config_name: temporal_reasoning
+  data_files:
+  - split: mini
+    path: temporal_reasoning/mini-*
+  - split: full
+    path: temporal_reasoning/full-*
+task_categories:
+- question-answering
+- video-text-to-text
+language:
+- en
+size_categories:
+- 10K<n<100K
+---
+
+# Minimal Video Pairs
+
+A shortcut-aware benchmark for spatio-temporal and intuitive physics video understanding (VideoQA) using minimally different video pairs.
+
+- [Github](https://github.com/facebookresearch/minimal_video_pairs)
+
+
+
+<p align="center">
+  <img src="overview.png" width="75%" alt="Overview"/>
+</p>
+
+For legal reasons, we are unable to upload the videos directly to Huggingface. However, we provide scripts in this repository for downloading the videos in our github repository. Our benchmark is built on top of videos source from 9 domains:
+
+| Subset | Data sources |
+| --- | --- |
+| Human object interactions | [PerceptionTest](https://github.com/google-deepmind/perception_test), [SomethingSomethingV2](https://www.qualcomm.com/developer/software/something-something-v-2-dataset) |
+| Robot object interactions | [Language Table](https://github.com/google-research/language-table) |
+| Intuitive Physics and collisions | [IntPhys](https://intphys.cognitive-ml.fr/), [InfLevel](https://github.com/allenai/inflevel), [GRASP](https://github.com/i-machine-think/grasp), [CLEVRER](http://clevrer.csail.mit.edu/) |
+| Temporal Reasoning | [STAR](https://bobbywu.com/STAR/), [Vinoground](https://vinoground.github.io/) |
+
+## Run evaluation
+
+To enable reproducible evaluation, we utilize the [lmms-eval](https://github.com/EvolvingLMMs-Lab/lmms-eval) library. We have provided the task files you need to run `mvp` and `mvp_mini`. `mvp_mini` is essentially a smaller, balanced evaluation set with 9k examples for enabling faster evaluations.
+
+Please follow the instructions on our [Github repository](https://github.com/facebookresearch/minimal_video_pairs) for running reproducible evals.
+
+## Leaderboard
+
+We also release our [Physical Reasoning Leaderboard](https://huggingface.co/spaces/facebook/physical_reasoning_leaderboard), where you can submit your model outputs for this dataset. Use the `data_name` as `mvp` and `mvp_mini` for submissions against `full` and `mini` split respectvely.
+
+## Citation and acknowledgements
+We are grateful to the datasets listed above for utilizing their videos to create this benchmark.
+Please cite us if you use the benchmark or any other part of the paper:
+```bibtex
+@article{krojer2025shortcut,
+  title={A Shortcut-aware Video-QA Benchmark for Physical Understanding via Minimal Video Pairs}
+  author={Benno Krojer and Mojtaba Komeili and Candace Ross and Quentin Garrido and Koustuv Sinha and Nicolas Ballas and Mahmoud Assran},
+  journal={arXiv},
+  year={2025}
+}
+```
+

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