Datasets:
metadata
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/processdata_sft.parquet
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.parquetanddata/processbench_eval.jsonldata/processdata_sft.parquetanddata/processdata_sft.jsonl- dataset-specific split files for all four sources
metadata/split_summary.json,metadata/eval_manifest.json,metadata/sft_manifest.jsonmetadata/task_distribution.csvmetadata/schema.md,metadata/reconstruction.md,metadata/prompt_templates.md- post-trained
ProcessEval-7Bresults underProcessEval_results/
Not included in this local release build
- full upstream raw videos
- full extracted frame caches
- local absolute paths from the development machine
- separate structured task-meta fields
- Croissant metadata
- task-card PNGs and human-audit assets
Sources
GM-100RH20TREASSEMBLEAIST-Bimanual
Task Families
T1: Phase RecognitionT2: Contact DetectionT3: Motion Direction PredictionT4: Bimanual Coordination StateT5: Primitive-local ProgressT6: Motion State RecognitionT7: Operation Outcome PredictionT8: Temporal OrderingT9: Temporal Priority PredictionT10: Current Primitive RecognitionT11: Next Primitive PredictionT12: Primitive Chain Restoration
Splits
eval:9,051sft: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.
- Raw videos and full frame caches are not redistributed here.
- Full visual reconstruction requires obtaining the upstream datasets under their original terms.