Datasets:
Tasks:
Visual Question Answering
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
License:
| license: other | |
| language: | |
| - en | |
| pretty_name: ProcessBench | |
| task_categories: | |
| - visual-question-answering | |
| tags: | |
| - robotics | |
| - embodied-ai | |
| - benchmark | |
| - vision-language-models | |
| - process-understanding | |
| - manipulation | |
| size_categories: | |
| - 10K<n<100K | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: eval | |
| path: data/processbench_eval.parquet | |
| - split: train | |
| path: data/train-* | |
| dataset_info: | |
| features: | |
| - name: image | |
| dtype: image | |
| splits: | |
| - name: train | |
| num_bytes: 5095162001 | |
| num_examples: 148933 | |
| download_size: 7614328888 | |
| dataset_size: 5095162001 | |
| # ProcessBench | |
| ## Dataset Summary | |
| ProcessBench is a process-aware benchmark for robotic manipulation understanding. This release build contains `57,892` public QA rows: `9,051` eval rows and `48,841` SFT rows across `12` task families. | |
| ## Included in this local release build | |
| - `data/processbench_eval.parquet` and `data/processbench_eval.jsonl` | |
| - `data/processdata_sft.parquet` and `data/processdata_sft.jsonl` | |
| - dataset-specific split files for all four sources | |
| - `metadata/split_summary.json`, `metadata/eval_manifest.json`, `metadata/sft_manifest.json` | |
| - `metadata/task_distribution.csv` | |
| - `metadata/schema.md`, `metadata/reconstruction.md`, `metadata/prompt_templates.md` | |
| - post-trained `ProcessEval-7B` results under `ProcessEval_results/` | |
| - benchmark suite `ProcessData-58k` under `ProcessData-58k/` | |
| ## Sources | |
| - `GM-100` | |
| - `RH20T` | |
| - `REASSEMBLE` | |
| - `AIST-Bimanual` | |
| ## Task Families | |
| - `T1`: Phase Recognition | |
| - `T2`: Contact Detection | |
| - `T3`: Motion Direction Prediction | |
| - `T4`: Bimanual Coordination State | |
| - `T5`: Primitive-local Progress | |
| - `T6`: Motion State Recognition | |
| - `T7`: Operation Outcome Prediction | |
| - `T8`: Temporal Ordering | |
| - `T9`: Temporal Priority Prediction | |
| - `T10`: Current Primitive Recognition | |
| - `T11`: Next Primitive Prediction | |
| - `T12`: Primitive Chain Restoration | |
| ## Splits | |
| - `eval`: `9,051` | |
| - `sft`: `48,841` | |
| - split rule: strict episode / recording / scene isolation | |
| ## License and Terms | |
| This release uses `license: other`. | |
| - Derived benchmark metadata in this release remains subject to upstream dataset terms. | |