| --- |
| license: apache-2.0 |
| task_categories: |
| - robotics |
| tags: |
| - LeRobot |
| - robotics |
| - vision-language-action |
| - semantic-reasoning |
| - compositional-generalization |
| pretty_name: Reasoning Benchmark 800 |
| --- |
| |
| # Reasoning Benchmark 800 |
|
|
| `Reasoning_Benchmark_800` is an 800-episode LeRobot v3 training dataset for |
| studying semantic and compositional generalization in vision-language-action |
| models. It combines four completed 200-episode datasets while preserving the |
| original observations, actions, timing, and videos. Only the training-language |
| metadata was reassigned. |
|
|
| The experimental control is that held semantic concepts are absent from the |
| training prompts even though the corresponding visual and motor trajectories |
| are present. Those trajectories receive an object-identity prompt or a more |
| generic relation/action prompt. This makes held-prompt evaluation test semantic |
| generalization rather than unseen motor behavior. |
|
|
| ## Composition |
|
|
| | Combined episodes | Task family | Source dataset | Seen-language episodes | Masked/held-support episodes | |
| |---:|---|---|---:|---:| |
| | 0–199 | Relational placement | `SP_Relational_Placement_200` | 100 front/back | 100 left/right trajectories prompted as next-to | |
| | 200–399 | Ordering/sequencing | `SP_Sequencing_200` | 76 seen combinations | 124 first-from-right/third-from-left trajectories prompted by object identity | |
| | 400–599 | Counting | `SP_Counting_200` | 80 counts 0/2 | 120 counts 1/3 prompted as generic object transfers | |
| | 600–799 | Size recognition | `MT_Size_Recognition_200` | 150 seen combinations | 50 held object–size combinations prompted by object identity | |
|
|
| This version intentionally excludes referential disambiguation and state |
| recognition. They can be added in a later benchmark release after those source |
| datasets are finalized. |
|
|
| ## Dataset summary |
|
|
| - 800 episodes |
| - 413,545 frames |
| - 30 FPS |
| - SO follower robot |
| - 5 RGB video observations: wrist, middle, above, right, and left |
| - 6-dimensional robot state and action |
| - 434 unique paraphrased training prompts |
| - 191 MP4 files, copied without re-encoding |
|
|
| ## Prompt assignment |
|
|
| The LeRobot task for each episode is taken only from the final `prompt` column |
| of `VLA Prompts.xlsx`. The training prompts are represented conventionally by |
| `meta/tasks.parquet` and the per-frame `task_index` column. |
|
|
| The `benchmark_metadata/` directory contains: |
|
|
| - `prompt_manifest.csv`: compact episode-to-prompt mapping |
| - `prompt_manifest.jsonl`: full audit mapping, including workbook annotations |
| - `prompt_manifest_summary.json`: counts and manifest/workbook checksums |
| - `source_datasets.json`: exact source repositories, revisions, and offsets |
| - `validation_report.json`: completed integrity checks |
|
|
| The audit JSONL is provenance metadata, not a model input. Training pipelines |
| should consume the standard LeRobot task field only. See |
| `benchmark_metadata/TRAINING_NOTES.md`. |
|
|
| ## Validation |
|
|
| The merged artifact passed checks for: |
|
|
| - contiguous episode indices 0–799 |
| - contiguous global frame indices 0–413,544 |
| - contiguous per-episode frame indices |
| - exact episode prompt agreement with the 800-row manifest |
| - exact per-frame task-index agreement with each episode prompt |
| - preservation of every source episode's frame count |
| - SHA-256 multiset equality between all source and merged video files |
| - zero detected held-concept leakage in the assigned training prompts |
|
|
| ## Intended evaluation |
|
|
| Train each architecture on the same 800 episodes and prompt assignments, then |
| evaluate with separate: |
|
|
| 1. matched identity prompts, |
| 2. seen semantic prompts, and |
| 3. held semantic prompts. |
|
|
| Keep held evaluation instructions outside the training input pipeline. |
|
|
|
|
