---
license: other
license_name: mixed-source
task_categories: [image-text-to-text, video-text-to-text]
tags: [multimodal, reasoning, sft, rl, distillation, mopd]
configs:
- config_name: sft_imgr
  data_files: sft_v4/imgr/*.jsonl
- config_name: sft_imgp
  data_files: sft_v4/imgp/*.jsonl
- config_name: sft_vid
  data_files: sft_v4/vid/*.jsonl
- config_name: rl_imgr
  data_files: rl_v2/imgr.parquet
- config_name: rl_imgp
  data_files: rl_v2/imgp.parquet
- config_name: rl_vid
  data_files: rl_v2/vid.parquet
---

# MOPD training data (SFT v4 + RL v2, full media)

The data that trains the MOPD domain teachers on Qwen3.5-9B: one SFT set and one RL prompt set per domain
(`imgr` image reasoning, `imgp` image perception, `vid` video).

| Split | Rows | Format | Media |
|---|---|---|---|
| `sft_v4/imgr` | 1,022,304 | chat jsonl (`messages`, `meta`) | images in `media/` |
| `sft_v4/imgp` | 1,456,403 | chat jsonl | images in `media/` |
| `sft_v4/vid` | 710,735 | chat jsonl | videos in `media/` |
| `rl_v2/imgr` | 64,307 | verl parquet (`prompt`, `images`, `reward_model.ground_truth`, `extra_info`) | images embedded (bytes) |
| `rl_v2/imgp` | 67,915 | verl parquet | images embedded (bytes) |
| `rl_v2/vid` | 60,805 | verl parquet | videos in `media/` |

**SFT rows**: single-turn multimodal questions pooled from public datasets; the assistant turn is a reasoning trace
(`<think>...</think>` + answer, final answer in `\boxed{}`) written by Qwen3.8-Flash-Next with the gold answer given,
then filtered by agreement with the gold. `meta` keeps the source card, task type and generator.
**RL rows**: prompts with a rule-checkable gold answer (`reward_model.ground_truth`, `extra_info.task_type`), decontaminated
against our eval benchmarks.

## Media

65 store-only zip shards in `media_zips/` (523 GB). Unzip all at the repo root:

```bash
huggingface-cli download ngqtrung/mopd-data --repo-type dataset --local-dir mopd-data
cd mopd-data && for z in media_zips/*.zip; do unzip -q -n "$z"; done   # -> media/<group>/...
```
Every media path in the rows is relative to the repo root (`media/...`). `media_index.tsv` lists path, bytes and shard.
Media processing used in training: images 65,536-1,605,632 px; videos 1 fps, 4-150 frames, ≤ 65,536 px per frame.

## Sources and license

The questions and media come from public datasets (e.g. LLaVA-Video-178K, FineVideo, Vript, VideoRFT, LLaVA-OneVision,
and others listed in `meta.card_id`). Each source keeps its own license; check it before use. The reasoning traces are
model-generated. Released for research.