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:
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.