| --- |
| license: mit |
| task_categories: |
| - video-text-to-text |
| - visual-question-answering |
| tags: |
| - robotics |
| - robomme |
| - manipulation |
| - memory |
| - video-qa |
| size_categories: |
| - n<1K |
| configs: |
| - config_name: episodes |
| data_files: episodes.parquet |
| --- |
| |
| # RoboMME — SequenceRecoveryVertically (Video QA) |
|
|
| Video-QA dataset for the **SequenceRecoveryVertically** task from |
| [RoboMME](https://github.com/), a ManiSkill/SAPIEN benchmark for |
| memory-augmented robotic manipulation. The agent watches a demonstration video, |
| remembers the arrangement of cubes, and rebuilds it around a pre-placed anchor |
| cube before pressing a stop button. |
|
|
| ## Contents |
|
|
| - `episodes.parquet` — 500 train episodes with per-episode metadata (seeds, |
| difficulty, task semantics, language goals, success flags, video paths). |
| - `videos/` — 1000 MP4 clips: one execution video and one `_recall` demonstration |
| clip per episode. |
| - `*_mc_qa_processed.json` — multiple-choice QA pairs (LLaVA conversation format). |
| - `*_oe_qa_processed.json` — open-ended QA pairs. |
| - `*_cap_processed.json` — caption pairs. |
| - `collection_manifest.jsonl` — provenance manifest (source H5, SHA-256 hashes, |
| frame counts). |
|
|
| QA/caption entries reference clips via a `video` field (e.g. |
| `videos/..._recall.mp4`) and use the standard `conversations` schema with |
| `<image>` tokens. |
|
|
