Datasets:
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README.md
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---
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license: other
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---
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---
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license: other
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language:
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- en
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pretty_name: ProcessBench
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task_categories:
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- visual-question-answering
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tags:
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- robotics
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- vision-language-models
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- embodied-ai
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- benchmark
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- process-understanding
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- manipulation
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size_categories:
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- 10K<n<100K
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configs:
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- config_name: default
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data_files:
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- split: eval
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path: data/processbench_eval.parquet
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- split: train
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path: data/processdata_sft.parquet
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---
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# ProcessBench
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## Dataset Summary
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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.
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## What is included
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- Frozen evaluation QA items
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- SFT QA items or manifests
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- Split metadata
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- Task distribution statistics
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- Human audit summary
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- ProcessEval-7B bootstrap CI
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- Rendered task cards
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- Reconstruction metadata
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## What is not included
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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.
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## Data Sources
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GM-100, RH20T, REASSEMBLE, and AIST-Bimanual.
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## Task Families
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T1--T12 with short descriptions.
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## Data Fields
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Explain item_id, source, task_id, input_type, question, choices, answer, visual_ref, source_episode_ref, builder_version.
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## Splits
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Strict episode / recording / scene isolation. Report 48,841 SFT and 9,051 eval.
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## Metrics
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Accuracy, random baseline, majority baseline, bootstrap CI.
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## Human Audit
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50 sampled items per task, two annotators.
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## Intended Use
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Diagnostic evaluation of VLM-side process understanding and process-aware VLM adaptation.
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## Out-of-Scope Use
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Not a closed-loop robot safety benchmark, not a deployment certificate, not a generic VLM leaderboard.
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## Licenses and Terms
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Code MIT; derived data subject to upstream terms.
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## Croissant Metadata
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This release includes Croissant metadata with core and Responsible AI fields.
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## Citation
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Anonymous during review.
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