Initial README
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README.md
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---
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license: apache-2.0
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task_categories:
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- video-text-to-text
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- visual-question-answering
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language:
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- en
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tags:
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- video
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- long-video
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- reasoning
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- tool-calling
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- multimodal
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size_categories:
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- 100K<n<1M
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---
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# ParaVT-Source
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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).
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## Overview
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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.
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## Layout
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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.
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| Bucket | Contents | Archive convention |
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|---|---|---|
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| `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 |
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| `museg/charades/` | Charades-STA clips used by the `charades` SFT split and the `charades_tvg` RL split | `charades_<idx>.zip` |
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| `museg/et_instruct_164k/` | MuSeG `et_instruct_164k` clips used by the `museg` SFT split | `et_instruct_<idx>.zip` |
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| `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) |
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Each archive is sized to stay below 10 GB on disk so that LFS pointer + Cloudflare CDN serving stays well-behaved.
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## Usage
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```bash
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huggingface-cli download ParaVT/ParaVT-Source --repo-type dataset --local-dir ./paravt-source
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# Selective: pull only the buckets you need (e.g. charades grounding only)
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huggingface-cli download ParaVT/ParaVT-Source \
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--repo-type dataset --local-dir ./paravt-source \
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--include "museg/charades/*"
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# Extract zips in place
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( cd ./paravt-source && for z in */*.zip; do unzip -q -d "$(dirname "$z")" "$z"; done )
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# Re-link absolute paths inside the parquets (one shot; see ParaVT/ParaVT-Parquet)
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python -m paravt.data.materialize \
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--root ./paravt-source \
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--parquet-dir ./paravt-parquet \
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--output-dir ./paravt-parquet-materialized
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```
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## Citation
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```bibtex
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@misc{yang2026paravt,
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title={{ParaVT}: From Format Fragility to Parallel Tool Mastery in Agentic Video {RL}},
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author={Zuhao Yang and others},
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year={2026},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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## Acknowledgements
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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.
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