---
license: other
language: 
- en
pretty_name: ProcessBench
task_categories: 
- visual-question-answering
tags:
- robotics
- vision-language-models
- embodied-ai
- benchmark
- 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 VLM benchmark for robotic manipulation. It contains 57,892 QA items, including 48,841 SFT items and 9,051 evaluation items, across 12 task families.

## What is included
- Frozen evaluation QA items
- SFT QA items or manifests
- Split metadata
- Task distribution statistics
- Human audit summary
- ProcessEval-7B bootstrap CI
- Rendered task cards
- Reconstruction metadata

## What is not included
We do not redistribute full upstream raw videos or full frame dumps. Full visual reconstruction requires users to obtain the upstream datasets under their original licenses.

## Data Sources
GM-100, RH20T, REASSEMBLE, and AIST-Bimanual.

## Task Families
T1--T12 with short descriptions.

## Data Fields
Explain item_id, source, task_id, input_type, question, choices, answer, visual_ref, source_episode_ref, builder_version.

## Splits
Strict episode / recording / scene isolation. Report 48,841 SFT and 9,051 eval.

## Metrics
Accuracy, random baseline, majority baseline, bootstrap CI.

## Human Audit
50 sampled items per task, two annotators.

## Intended Use
Diagnostic evaluation of VLM-side process understanding and process-aware VLM adaptation.

## Out-of-Scope Use
Not a closed-loop robot safety benchmark, not a deployment certificate, not a generic VLM leaderboard.

## Licenses and Terms
Code MIT; derived data subject to upstream terms.

## Croissant Metadata
This release includes Croissant metadata with core and Responsible AI fields.

## Citation
Anonymous during review.