Improve dataset card: add paper link, code link, sample usage, and video-text-to-text task category
#2
by nielsr HF Staff - opened
README.md
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---
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license: cc-by-nc-4.0
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pretty_name: RoboJudge-Bench
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task_categories:
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- video-classification
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- visual-question-answering
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tags:
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- robojudge
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- embodied-ai
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# RoboJudge-Bench
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RoboJudge
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## Files
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## Scores
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- **Physical Adherence (PA):** agent consistency, scene consistency, and
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language:
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- en
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license: cc-by-nc-4.0
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task_categories:
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- video-classification
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- visual-question-answering
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- video-text-to-text
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pretty_name: RoboJudge-Bench
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tags:
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- robojudge
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- embodied-ai
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# RoboJudge-Bench
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**Paper:** [RoboJudge: Multimodal Language Models as Judges for Embodied Video Generation](https://huggingface.co/papers/2610.27782)
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**Code:** [GitHub - Sphere-AI-Lab/RoboJudge](https://github.com/Sphere-AI-Lab/RoboJudge)
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**Project page:** https://siyuanmacs.github.io/RoboJudge/
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RoboJudge-Bench contains 800 human-annotated embodied videos from 8 source corpora and 10 video generators. Every record includes the task instruction, locally hosted video and initial-frame URLs, PA/IA ratings, and six diagnostic sub-scores.
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## Files
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## Scores
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- **Physical Adherence (PA):** agent consistency, scene consistency, and interaction realism.
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- **Instruction Alignment (IA):** agent match, object correctness, and goal completion.
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Main scores are integers from 1 to 5. Diagnostic sub-scores are integers from 0 to 2.
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## Sample Usage
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```bash
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python -m pip install -r requirements.txt
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huggingface-cli download HuggingFriends/RoboJudge-Bench \
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--repo-type dataset --local-dir data_root
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CKPT=HuggingFriends/RoboJudge-9B \
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DATA_ROOT="$PWD/data_root" \
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LIMIT=4 \
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bash code/run_inference.sh
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python code/evaluate.py \
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outputs/predictions.jsonl \
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data/benchmark/robojudge_bench.jsonl
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```
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