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license: mit |
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language: |
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- en |
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pretty_name: LongTVQA+ |
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--- |
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# LongTVQA+ Dataset |
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This repository contains the **LongTVQA+** dataset in JSON format. |
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LongTVQA+ is built upon the original **TVQA+** dataset, with the key difference that it **extends the question grounding scope from short clip-level segments (≈1 minute) to long episode-level videos (up to ~20 minutes)**. |
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This enables research on long-form video understanding, long-range temporal reasoning, and fine-grained spatio-temporal grounding in realistic TV show episodes. |
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In addition to the extended temporal scope, LongTVQA+ preserves and leverages the rich annotations provided in TVQA+, including: |
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1. Frame-level bounding box annotations for visual concept words appearing in questions and correct answers. |
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2. Refined timestamp annotations aligned with long episode-level context. |
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Please refer to the original **TVQA+ paper** for details on the annotation protocol and baseline evaluations. |
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--- |
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## Files |
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- `LongTVQA_plus_train.json` — training split (23,545 QA samples) |
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- `LongTVQA_plus_val.json` — validation split (3,017 QA samples) |
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- `LongTVQA_plus_subtitle_clip_level.json` — clip-level subtitles indexed by video clip (4,198 clips) |
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- `LongTVQA_plus_subtitle_episode_level.json` — episode-level subtitles indexed by episode (220 episodes) |
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--- |
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## QA JSON Format |
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Each entry in `LongTVQA_plus_train.json` and `LongTVQA_plus_val.json` is a dictionary with the following fields: |
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| Key | Type | Description | |
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| --- | --- | --- | |
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| `qid` | int | Question ID (same as in TVQA+). | |
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| `q` | str | Question text. | |
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| `a0` ... `a4` | str | Five multiple-choice answers. | |
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| `answer` | str | Correct answer key (`"a0"`–`"a4"`). | |
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| `ts` | list | Refined timestamp annotation. For example, `[0, 5.4]` indicates the localized temporal span starts at 0s and ends at 5.4s. | |
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| `episode_name` | str | Episode ID (e.g. `s01e02`). | |
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| `occur_clip` | str | Video clip name. Format: `{show_name_abbr}_s{season}e{episode}_seg{segment}_clip_{clip}`. Episodes are typically divided into two segments separated by the opening theme. For **The Big Bang Theory**, `{show_name_abbr}` is omitted (e.g. `s05e02_seg02_clip_00`). | |
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| `bbox` | dict | Frame-level bounding box annotations sampled at 3 FPS. Keys are frame indices. Values are lists of bounding boxes with `img_id`, `top`, `left`, `width`, `height`, and `label`. | |
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--- |
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### QA Sample |
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```json |
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{ |
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"answer": "a1", |
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"qid": 134094, |
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"ts": [5.99, 11.98], |
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"a1": "Howard is talking to Raj and Leonard", |
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"a0": "Howard is talking to Bernadette", |
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"a3": "Howard is talking to Leonard and Penny", |
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"a2": "Howard is talking to Sheldon , and Raj", |
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"q": "Who is Howard talking to when he is in the lab room ?", |
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"episode_name": "s05e02", |
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"occur_clip": "s05e02_seg02_clip_00", |
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"a4": "Howard is talking to Penny and Bernadette", |
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"bbox": { |
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"14": [ |
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{ |
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"img_id": 14, |
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"top": 153, |
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"label": "Howard", |
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"width": 180, |
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"height": 207, |
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"left": 339 |
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}, |
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{ |
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"img_id": 14, |
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"top": 6, |
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"label": "lab", |
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"width": 637, |
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"height": 354, |
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"left": 3 |
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} |
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], |
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"20": [], |
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"26": [], |
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"32": [], |
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"38": [] |
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} |
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} |
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``` |
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--- |
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## Subtitles JSON Format |
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Two subtitle files are provided to support different temporal granularities: |
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| File | Key | Type | Description | |
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| ------------------------------------------- | -------------- | ---- | ------------------------------------------------------------------------------------------------------------------- | |
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| `LongTVQA_plus_subtitle_clip_level.json` | `vid_name` | str | Clip-level subtitle text, with utterances separated by `<eos>`. | |
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| `LongTVQA_plus_subtitle_episode_level.json` | `episode_name` | str | Episode-level subtitle text, including clip markers such as `<seg01_clip_00>`, and utterances separated by `<eos>`. | |
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--- |
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### Subtitles Sample |
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```json |
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{ |
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"s09e14_seg02_clip_04": "Sheldon : That 's a risk I'm willing to take ! <eos> Amy : Well , this is so nice . <eos> ..." |
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} |
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``` |
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--- |
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## License |
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This dataset is released under the **MIT License**. |
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## 📝 Citation |
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If you find our work helpful, please cite: |
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```bibtex |
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@misc{liu2025longvideoagentmultiagentreasoninglong, |
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title={LongVideoAgent: Multi-Agent Reasoning with Long Videos}, |
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author={Runtao Liu and Ziyi Liu and Jiaqi Tang and Yue Ma and Renjie Pi and Jipeng Zhang and Qifeng Chen}, |
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year={2025}, |
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eprint={2512.20618}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.AI}, |
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url={[https://arxiv.org/abs/2512.20618](https://arxiv.org/abs/2512.20618)}, |
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} |
