Datasets:

HuggingFriends
/

RoboJudge-Bench

language:
  - en
license: cc-by-nc-4.0
task_categories:
  - video-classification
  - visual-question-answering
  - video-text-to-text
pretty_name: RoboJudge-Bench
tags:
  - robojudge
  - embodied-ai
  - video-evaluation
  - benchmark

RoboJudge-Bench

Paper: RoboJudge: Multimodal Language Models as Judges for Embodied Video Generation
Code: GitHub - Sphere-AI-Lab/RoboJudge
Project page: https://siyuanmacs.github.io/RoboJudge/

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.

Files

data/test.jsonl: benchmark metadata, instructions, links, and labels.
data/<source>/generated_data/.../*.mp4: all 800 benchmark videos.
data/<source>/generated_data/.../prompt/: initial frames and instructions.
metadata/summary.json: release counts and source revision.

Scores

Physical Adherence (PA): agent consistency, scene consistency, and interaction realism.
Instruction Alignment (IA): agent match, object correctness, and goal completion.

Main scores are integers from 1 to 5. Diagnostic sub-scores are integers from 0 to 2.

Sample Usage

python -m pip install -r requirements.txt
huggingface-cli download HuggingFriends/RoboJudge-Bench \
  --repo-type dataset --local-dir data_root

CKPT=HuggingFriends/RoboJudge-9B \
DATA_ROOT="$PWD/data_root" \
LIMIT=4 \
bash code/run_inference.sh

python code/evaluate.py \
  outputs/predictions.jsonl \
  data/benchmark/robojudge_bench.jsonl