| --- |
| 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](https://github.com/mwxely/ParaVT) training corpus. Pair this repository with the annotations in [`ParaVT/ParaVT-Parquet`](https://huggingface.co/datasets/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`](https://github.com/mwxely/ParaVT/blob/paravt-release/paravt/data/sanitize.py)). Each bucket's archives extract directly into a directory tree that the [`paravt.data.materialize`](https://github.com/mwxely/ParaVT/blob/paravt-release/paravt/data/materialize.py) 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`](https://huggingface.co/datasets/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 |
|
|
| ```bash |
| 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 |
|
|
| ```bibtex |
| @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](https://github.com/EvolvingLMMs-Lab/LongVT) training media released at [`longvideotool/LongVT-Source`](https://huggingface.co/datasets/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. |
|
|
