Datasets:

ParaVT
/

ParaVT-Source

license: apache-2.0
task_categories:
  - video-text-to-text
  - visual-question-answering
language:
  - en
tags:
  - video
  - long-video
  - reasoning
  - tool-calling
  - multimodal
size_categories:
  - 100K<n<1M

ParaVT-Source

Source media archives for the ParaVT training corpus. Pair this repository with the annotations in ParaVT/ParaVT-Parquet.

Overview

ParaVT is a multi-agent agentic framework for long-video understanding, post-trained with PARA-GRPO (Parseability-Anchored and Ratio-gAted GRPO). This dataset bundles the raw video files referenced by every row in ParaVT-Parquet, packaged as per-source zip archives.

Layout

Files are grouped by sentinel bucket (matching the path scheme used by paravt.data.sanitize). Each bucket's archives extract directly into a directory tree that the paravt.data.materialize helper can re-attach to absolute paths in a single call.

Bucket	Contents	Archive convention
`longvt_source/<src>/`	LongVT shared training clips (`videor1_`, `longvideoreason_`, `geminicot_`, `tvg_`, `selftrace_*`)	`<src>_<idx>.zip`, mirroring the `longvideotool/LongVT-Source` naming
`museg/charades/`	Charades-STA clips used by the `charades` SFT split and the `charades_tvg` RL split	`charades_<idx>.zip`
`museg/et_instruct_164k/`	MuSeG `et_instruct_164k` clips used by the `museg` SFT split	`et_instruct_<idx>.zip`
`selfqa/`	Self-curated open-ended QA clips (HACS- and Ego4D-derived UUIDs / YouTube IDs) used by the `hacs` and `ego4d_naq` RL splits	`selfqa.zip` (single archive, ~6 GB)

Each archive is sized to stay below 10 GB on disk so that LFS pointer + Cloudflare CDN serving stays well-behaved.

Usage

huggingface-cli download ParaVT/ParaVT-Source --repo-type dataset --local-dir ./paravt-source

# Selective: pull only the buckets you need (e.g. charades grounding only)
huggingface-cli download ParaVT/ParaVT-Source \
    --repo-type dataset --local-dir ./paravt-source \
    --include "museg/charades/*"

# Extract zips in place
( cd ./paravt-source && for z in */*.zip; do unzip -q -d "$(dirname "$z")" "$z"; done )

# Re-link absolute paths inside the parquets (one shot; see ParaVT/ParaVT-Parquet)
python -m paravt.data.materialize \
    --root        ./paravt-source \
    --parquet-dir ./paravt-parquet \
    --output-dir  ./paravt-parquet-materialized

Citation

@misc{yang2026paravt,
  title={{ParaVT}: From Format Fragility to Parallel Tool Mastery in Agentic Video {RL}},
  author={Zuhao Yang and others},
  year={2026},
  archivePrefix={arXiv},
  primaryClass={cs.CV}
}

Acknowledgements

The longvt_source/ archives reuse subsets of the LongVT training media released at longvideotool/LongVT-Source; the MuSeG, Charades-STA, HACS, and Ego4D source clips are attributed to their respective original publications and used under their original licenses.