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: train | |
| path: data/processdata_sft.parquet | |
| - split: eval | |
| path: data/processbench_eval.parquet | |
| # ProcessBench | |
| ## Dataset Summary | |
| ProcessBench is a process-aware benchmark for vision-language robotic manipulation understanding. It evaluates whether VLMs can infer how a manipulation execution unfolds, including phase, contact, motion, bimanual coordination, primitive-local progress, temporal order, outcome, and primitive-level transitions. | |
| This release contains 57,892 QA rows: 48,841 SFT rows and 9,051 evaluation rows across 12 task families and 260 manipulation tasks. The split follows strict episode / recording / scene isolation. The benchmark is derived from GM-100, RH20T, REASSEMBLE, and AIST-Bimanual. | |
| ## Task Families | |
| ProcessBench contains 12 diagnostic question families: | |
| - **T1 Phase Recognition:** identify the current coarse process phase. | |
| - **T2 Contact Detection:** determine whether task-relevant contact has occurred. | |
| - **T3 Motion Direction Prediction:** infer the dominant motion direction from short temporal context. | |
| - **T4 Bimanual Coordination State:** identify the current coordination state of two arms. | |
| - **T5 Primitive-local Progress:** estimate progress within the current local manipulation step. | |
| - **T6 Motion State Recognition:** distinguish actively moving from stationary states. | |
| - **T7 Operation Outcome Prediction:** predict eventual success or failure from partial execution evidence. | |
| - **T8 Temporal Ordering:** reconstruct the chronological order of shuffled observations. | |
| - **T9 Temporal Priority Prediction:** decide which of two observations occurred earlier. | |
| - **T10 Current Primitive Recognition:** identify the current low-level primitive. | |
| - **T11 Next Primitive Prediction:** infer the next primitive from local process context. | |
| - **T12 Primitive Chain Restoration:** restore a masked primitive in a local primitive chain. | |
| ## Repository Contents | |
| The release is organized as a compact, reviewable benchmark package: | |
| ```text | |
| ProcessBench-Anom/ | |
| ├── splits/ # SFT and Eval QA entries, split summaries | |
| │ ├── processdata_sft.jsonl | |
| │ ├── processdata_sft.parquet | |
| │ ├── sft_manifest.jsonl | |
| │ ├── processdata_eval.jsonl | |
| │ ├── processdata_eval.parquet | |
| │ └── eval-manifest.jsonl | |
| │ | |
| ├── metadata/ # statistics, schema, licenses, prompt templates, reconstruction notes | |
| │ ├── split_summary.json | |
| │ ├── task_distribution.csv | |
| │ ├── asset_licenses.csv | |
| │ ├── schema.md | |
| │ ├── prompt_templates.md | |
| │ └── reconstruction.md | |
| │ | |
| ├── examples/ # rendered representative benchmark cards | |
| │ └── task_cards/ | |
| │ ├── T1_phase_recognition.png | |
| │ ├── T2_contact_detection.png | |
| │ ├── ... | |
| │ └── T12_primitive_chain_restoration.png | |
| │ | |
| ├── ProcessData-SFT-Qwen/ # LoRA adapter weights and training configuration | |
| │ ├── adapter_config.json | |
| │ ├── adapter_model.safetensors | |
| │ ├── ... | |
| │ └── training_config.json | |
| │ | |
| ├── ProcessData-SFT-Qwen_results/ # predictions and summary of the post-trained model | |
| │ ├── ProcessData-SFT-Qwen_predictions.json | |
| │ └── ProcessData-SFT-Qwen_summary.json | |
| │ | |
| ├── benchmark_card.md # benchmark-level documentation | |
| ├── croissant.json # Croissant core + Responsible AI metadata | |
| └── README.md | |
| ``` | |
| Full upstream videos and full frame dumps are not redistributed in this release. | |
| ## License and Terms | |
| This release uses `license: other`. | |
| - Derived benchmark metadata in this release remains subject to upstream dataset terms. | |