Datasets:

UniX-Lab
/

StreamOPD-Data

---
pretty_name: StreamOPD Data
license: other
license_name: upstream-and-component-terms
license_link: LICENSE.md
language:
- en
task_categories:
- video-text-to-text
- question-answering
tags:
- streaming-video
- video-question-answering
- on-policy-distillation
- visual-cues
- annotations-only
size_categories:
- 10K<n<100K
configs:
- config_name: current
  default: true
  data_files:
  - split: train
    path: data/current/train.parquet
  - split: validation
    path: data/current/validation.parquet
- config_name: legacy_25118
  data_files:
  - split: train
    path: data/legacy_25118/train.parquet
  - split: validation
    path: data/legacy_25118/validation.parquet
- config_name: grpo_25114
  data_files:
  - split: train
    path: data/grpo_25114/train.parquet
  - split: validation
    path: data/grpo_25114/validation.parquet
---
# StreamOPD: Training Data for Streaming Video Post-Training

StreamOPD-Data provides video question-answer annotations, local video time intervals,
and optional teacher-side visual cues for on-policy distillation and related controls.
**Video files, model weights, training logs and credentials are not included.**
The QA annotations are derived from [ThinkStream](https://huggingface.co/datasets/CASIA-IVA-Lab/ThinkStream).
Video references resolve to [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-Video-178K)
and the Kinetics-700 component of [Tarsier2-Recap-585K](https://huggingface.co/datasets/omni-research/Tarsier2-Recap-585K).

## Configurations

| Configuration | Train | Validation | Training rows with cues | Purpose |
|---|---:|---:|---:|---|
| `current` (default) | 25,106 | 326 | 24,245 | Current shared OPD/CueGate pool after known input and source-overlap exclusions |
| `legacy_25118` | 25,118 | 326 | 24,257 | Earlier QA pool with the explicit cue-instruction teacher prompt |
| `grpo_25114` | 25,114 | 326 | 0 | Readability-filtered GRPO data with the actual direct-answer prompt suffixes |

These are overlapping versions of the same data family, **not independent datasets to concatenate**.
Validation questions, answers and intervals are shared; the GRPO version has its own
direct-answer prompt wording. Each configuration's original row order is retained.
The `legacy_25118` configuration retains the known problematic rows for historical
reproduction; use `current` unless reproducing that specific configuration.

Two source questions contained email text among answer choices. This publication replaces
those strings with `[REDACTED_EMAIL]` in every affected prompt, without changing answer
letters. `privacy_redacted` marks the two affected training rows in each configuration.
Therefore this release is a privacy-sanitized representation, not a byte-identical copy
of private training inputs. See [data processing](docs/data_processing.md).

## Load annotations

```python
from datasets import load_dataset
data = load_dataset("UniX-Lab/StreamOPD-Data", "current")
print(data["train"][0]["prompt"])
print(data["train"][0]["videos"])
```

`videos` contains plain relative-path metadata, not embedded video bytes or automatic
downloads. Obtain the upstream videos using [video_sources.md](docs/video_sources.md).

Download this small annotation release with one worker:

```python
from huggingface_hub import snapshot_download
snapshot_download(
    repo_id="UniX-Lab/StreamOPD-Data",
    repo_type="dataset",
    local_dir="StreamOPD-Data",
    max_workers=1,
)
```

Resolve paths into local trainer inputs after obtaining the videos:

```bash
python StreamOPD-Data/scripts/prepare_local_data.py \
  --config current --video-root /path/to/videos \
  --output-dir ./streamopd-local
python StreamOPD-Data/scripts/validate_data.py
```

The preparation tool requires all video paths to resolve, preserves timestamps and
annotation content, and writes `train.parquet` and `validation.parquet` to a new local
directory. It supports the extra `data/` alias used in some historical LLaVA paths.
It checks file presence without decoding videos; the known legacy interval failures
remain documented rather than silently filtered.

## Fields

| Field | Meaning |
|---|---|
| `sample_id` | Stable ID, including split; shared across configurations for the same underlying source row |
| `source_row_id` | Original zero-based row number in the base train pool or validation split |
| `privacy_redacted` | Whether contact text was replaced in this row for publication |
| `prompt` | Student chat messages, with `<video>` placeholder and question/choices |
| `videos` | List of `{video, video_start, video_end}`; paths relative to the video root, times in seconds |
| `video_source` | `LLaVA-Video-178K` or `Kinetics-700` |
| `ground_truth` | Verifiable reference answer as a string |
| `response_format` | `Multiple Choice`, `Binary`, or `Counting` |
| `data_source` | Preserved training reward-routing tag; not the video's provenance |
| `reward_model` | Reference-answer struct expected by the original training interface |
| `teacher_prompt` | Cue-augmented teacher messages where available; otherwise identical to the student prompt |
| `teacher_reference_raw` | Original student messages used as a no-cue reference |
| `teacher_reference_empty` | Same cue instruction wrapper with the cue removed; or original messages on fallback rows |
| `cue_text`, `cue_available` | Optional generated pointer and availability flag |

Teacher-reference fields are stored for convenience in every configuration. Only
`current` used both stored reference forms in the reference-template preparation;
the corresponding fields in `legacy_25118` are reconstructed from the unchanged cue
wrapper. All teacher fields in `grpo_25114` equal its direct-answer student prompt.
Plain OPD must use the student prompt without injecting `teacher_prompt` as a cue.

## Current training split statistics

| Answer format | Rows |
|---|---:|
| Multiple choice | 17,485 |
| Binary | 6,364 |
| Counting | 1,257 |

19,814 training records reference LLaVA-Video-178K and 5,292 reference Kinetics-700.
There are 22,848 unique video files in the current training split. Intervals range
from 0.4 to 30 seconds. 861 training rows have no accepted cue and use the original
prompt as their teacher input. Validation has no cue annotations.

## Scope and limitations

- `current` excludes four confirmed unreadable video intervals and eight training
  records tied to seven confirmed overlapping source videos. This is not an
  exhaustive disjointness guarantee against every benchmark.
- An existing audit identified 252 current MCQs without an explicit option block.
  Their mapping is unresolved; this release preserves them and publishes stable
  IDs in `metadata/known_issues.json`.
- Cues are generated annotations. Automated screening is not a guarantee that a
  cue is correct or free of answer-bearing information.
- Historical cue generation could inspect the full source clip, including content
  after a query timestamp. These are **not certified prefix-only cues**.
- Student input intervals end at the recorded query timestamp. This does not
  certify that every answer or cue is recoverable from the sampled student frames.
- Training interval sampling and four-frame streaming deployment are distinct.
  No rendered clips or precomputed frame cache are distributed here.
- This dataset release does not establish new benchmark scores or independent
  training-seed uncertainty.

## Provenance, terms and integrity

See [video sources](docs/video_sources.md), [construction and preprocessing](docs/data_processing.md),
and [component terms](LICENSE.md). ThinkStream's MIT notice is included under `licenses/`.
Source videos remain subject to their original distribution conditions; the dataset
repository does not grant rights to those videos.

`metadata/release_manifest.json` identifies the release files and upstream revisions.
`checksums.sha256` enables local integrity checks. `metadata/video_manifest.parquet`
lists unique source video paths without internal machine paths.

If you use these annotations, cite StreamOPD and acknowledge the upstream ThinkStream,
LLaVA-Video and Tarsier2/Kinetics sources. Use the repository revision when reporting
the precise data version.

## Citation

```bibtex
@article{wu2026streamopd,
  title={StreamOPD: A Post-Training Recipe with Spatio-Temporal Cue Gating for Streaming Video Understanding},
  author={Wu, Keming and Wang, Baoyi and Zhang, Kaichen and An, Xiang and Yang, Zuhao and Wang, Sudong and Zhu, Haowei and Huang, Tingxuan and Gao, Hongcheng and Wang, Bin},
  journal={arXiv preprint arXiv:2608.16320},
  year={2026}
}
```

	---
	pretty_name: StreamOPD Data
	license: other
	license_name: upstream-and-component-terms
	license_link: LICENSE.md
	language:
	- en
	task_categories:
	- video-text-to-text
	- question-answering
	tags:
	- streaming-video
	- video-question-answering
	- on-policy-distillation
	- visual-cues
	- annotations-only
	size_categories:
	- 10K<n<100K
	configs:
	- config_name: current
	default: true
	data_files:
	- split: train
	path: data/current/train.parquet
	- split: validation
	path: data/current/validation.parquet
	- config_name: legacy_25118
	data_files:
	- split: train
	path: data/legacy_25118/train.parquet
	- split: validation
	path: data/legacy_25118/validation.parquet
	- config_name: grpo_25114
	data_files:
	- split: train
	path: data/grpo_25114/train.parquet
	- split: validation
	path: data/grpo_25114/validation.parquet
	---

	# StreamOPD: Training Data for Streaming Video Post-Training

	StreamOPD-Data provides video question-answer annotations, local video time intervals,
	and optional teacher-side visual cues for on-policy distillation and related controls.
	Video files, model weights, training logs and credentials are not included.
	The QA annotations are derived from [ThinkStream](https://huggingface.co/datasets/CASIA-IVA-Lab/ThinkStream).
	Video references resolve to [LLaVA-Video-178K](https://huggingface.co/datasets/lmms-lab/LLaVA-Video-178K)
	and the Kinetics-700 component of [Tarsier2-Recap-585K](https://huggingface.co/datasets/omni-research/Tarsier2-Recap-585K).

	## Configurations

	\| Configuration \| Train \| Validation \| Training rows with cues \| Purpose \|
	\|---\|---:\|---:\|---:\|---\|
	\| `current` (default) \| 25,106 \| 326 \| 24,245 \| Current shared OPD/CueGate pool after known input and source-overlap exclusions \|
	\| `legacy_25118` \| 25,118 \| 326 \| 24,257 \| Earlier QA pool with the explicit cue-instruction teacher prompt \|
	\| `grpo_25114` \| 25,114 \| 326 \| 0 \| Readability-filtered GRPO data with the actual direct-answer prompt suffixes \|

	These are overlapping versions of the same data family, not independent datasets to concatenate.
	Validation questions, answers and intervals are shared; the GRPO version has its own
	direct-answer prompt wording. Each configuration's original row order is retained.
	The `legacy_25118` configuration retains the known problematic rows for historical
	reproduction; use `current` unless reproducing that specific configuration.

	Two source questions contained email text among answer choices. This publication replaces
	those strings with `[REDACTED_EMAIL]` in every affected prompt, without changing answer
	letters. `privacy_redacted` marks the two affected training rows in each configuration.
	Therefore this release is a privacy-sanitized representation, not a byte-identical copy
	of private training inputs. See [data processing](docs/data_processing.md).

	## Load annotations

	```python
	from datasets import load_dataset

	data = load_dataset("UniX-Lab/StreamOPD-Data", "current")
	print(data["train"][0]["prompt"])
	print(data["train"][0]["videos"])
	```

	`videos` contains plain relative-path metadata, not embedded video bytes or automatic
	downloads. Obtain the upstream videos using [video_sources.md](docs/video_sources.md).

	Download this small annotation release with one worker:

	```python
	from huggingface_hub import snapshot_download

	snapshot_download(
	repo_id="UniX-Lab/StreamOPD-Data",
	repo_type="dataset",
	local_dir="StreamOPD-Data",
	max_workers=1,
	)
	```

	Resolve paths into local trainer inputs after obtaining the videos:

	```bash
	python StreamOPD-Data/scripts/prepare_local_data.py \
	--config current --video-root /path/to/videos \
	--output-dir ./streamopd-local

	python StreamOPD-Data/scripts/validate_data.py
	```

	The preparation tool requires all video paths to resolve, preserves timestamps and
	annotation content, and writes `train.parquet` and `validation.parquet` to a new local
	directory. It supports the extra `data/` alias used in some historical LLaVA paths.
	It checks file presence without decoding videos; the known legacy interval failures
	remain documented rather than silently filtered.

	## Fields

	\| Field \| Meaning \|
	\|---\|---\|
	\| `sample_id` \| Stable ID, including split; shared across configurations for the same underlying source row \|
	\| `source_row_id` \| Original zero-based row number in the base train pool or validation split \|
	\| `privacy_redacted` \| Whether contact text was replaced in this row for publication \|
	\| `prompt` \| Student chat messages, with `<video>` placeholder and question/choices \|
	\| `videos` \| List of `{video, video_start, video_end}`; paths relative to the video root, times in seconds \|
	\| `video_source` \| `LLaVA-Video-178K` or `Kinetics-700` \|
	\| `ground_truth` \| Verifiable reference answer as a string \|
	\| `response_format` \| `Multiple Choice`, `Binary`, or `Counting` \|
	\| `data_source` \| Preserved training reward-routing tag; not the video's provenance \|
	\| `reward_model` \| Reference-answer struct expected by the original training interface \|
	\| `teacher_prompt` \| Cue-augmented teacher messages where available; otherwise identical to the student prompt \|
	\| `teacher_reference_raw` \| Original student messages used as a no-cue reference \|
	\| `teacher_reference_empty` \| Same cue instruction wrapper with the cue removed; or original messages on fallback rows \|
	\| `cue_text`, `cue_available` \| Optional generated pointer and availability flag \|

	Teacher-reference fields are stored for convenience in every configuration. Only
	`current` used both stored reference forms in the reference-template preparation;
	the corresponding fields in `legacy_25118` are reconstructed from the unchanged cue
	wrapper. All teacher fields in `grpo_25114` equal its direct-answer student prompt.
	Plain OPD must use the student prompt without injecting `teacher_prompt` as a cue.

	## Current training split statistics

	\| Answer format \| Rows \|
	\|---\|---:\|
	\| Multiple choice \| 17,485 \|
	\| Binary \| 6,364 \|
	\| Counting \| 1,257 \|

	19,814 training records reference LLaVA-Video-178K and 5,292 reference Kinetics-700.
	There are 22,848 unique video files in the current training split. Intervals range
	from 0.4 to 30 seconds. 861 training rows have no accepted cue and use the original
	prompt as their teacher input. Validation has no cue annotations.

	## Scope and limitations

	- `current` excludes four confirmed unreadable video intervals and eight training
	records tied to seven confirmed overlapping source videos. This is not an
	exhaustive disjointness guarantee against every benchmark.
	- An existing audit identified 252 current MCQs without an explicit option block.
	Their mapping is unresolved; this release preserves them and publishes stable
	IDs in `metadata/known_issues.json`.
	- Cues are generated annotations. Automated screening is not a guarantee that a
	cue is correct or free of answer-bearing information.
	- Historical cue generation could inspect the full source clip, including content
	after a query timestamp. These are not certified prefix-only cues.
	- Student input intervals end at the recorded query timestamp. This does not
	certify that every answer or cue is recoverable from the sampled student frames.
	- Training interval sampling and four-frame streaming deployment are distinct.
	No rendered clips or precomputed frame cache are distributed here.
	- This dataset release does not establish new benchmark scores or independent
	training-seed uncertainty.

	## Provenance, terms and integrity

	See [video sources](docs/video_sources.md), [construction and preprocessing](docs/data_processing.md),
	and [component terms](LICENSE.md). ThinkStream's MIT notice is included under `licenses/`.
	Source videos remain subject to their original distribution conditions; the dataset
	repository does not grant rights to those videos.

	`metadata/release_manifest.json` identifies the release files and upstream revisions.
	`checksums.sha256` enables local integrity checks. `metadata/video_manifest.parquet`
	lists unique source video paths without internal machine paths.

	If you use these annotations, cite StreamOPD and acknowledge the upstream ThinkStream,
	LLaVA-Video and Tarsier2/Kinetics sources. Use the repository revision when reporting
	the precise data version.

	## Citation

	```bibtex
	@article{wu2026streamopd,
	title={StreamOPD: A Post-Training Recipe with Spatio-Temporal Cue Gating for Streaming Video Understanding},
	author={Wu, Keming and Wang, Baoyi and Zhang, Kaichen and An, Xiang and Yang, Zuhao and Wang, Sudong and Zhu, Haowei and Huang, Tingxuan and Gao, Hongcheng and Wang, Bin},
	journal={arXiv preprint arXiv:2608.16320},
	year={2026}
	}
	```