| { | |
| "name": "VSI-Bench", | |
| "release_date": "2024-12-18", | |
| "subsets": { | |
| "mc": { | |
| "language": [ | |
| "en" | |
| ], | |
| "modalities": [ | |
| "single_video_start" | |
| ], | |
| "task_type": "multiple_choice_qa", | |
| "score_pipeline": [ | |
| "exact-match", | |
| "rule-match" | |
| ], | |
| "score_protocol": { | |
| "reference": "lmms-eval@lmms_eval/tasks/vsibench/utils.py:87-89,115-121 — MCA question types graded by fuzzy_matching (first token, strip trailing period) + case-insensitive exact match against the ground-truth letter; no LLM.", | |
| "note": "The org ships ONLY the multiple-choice question types (mc config, 2490 rows; confirmed in rows file). The official benchmark also contains NA (numerical) types graded with Mean Relative Accuracy MRA:.5:.95:.05 (utils.py:95-100,29-31), and the official headline 'overall' averages 8 per-question-type scores after averaging object_rel_direction easy/medium/hard (utils.py:158-170) — neither is reproducible from this copy or from a per-sample mean. Rows carry extra 'question_type' with VSI type names (object_rel_direction_hard, ...) that are not scorer vocabulary." | |
| }, | |
| "prompt_template": "<video>These are frames of a video.\n{{ question }}\nOptions:\n{% for o in options %}{{ o }}\n{% endfor %}Answer with the option's letter from the given choices directly.", | |
| "prompt_template_source": { | |
| "origin": "official", | |
| "reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/vsibench/utils.py (vsibench_doc_to_text — canonical MCA prompt) + _default_template_yaml", | |
| "notes": "Tier 4: lmms-eval VSI-Bench canonical MCA prompt for the MC question types. SAT paper (arXiv 2412.07755, Appendix A.3, p.20) restricts VSI-Bench evaluation to the MC split — numerical splits (object_counting, object_size_estimation, room_size_estimation, object_abs_distance) are excluded. Each MC row carries the source `options` list verbatim from nyu-visionx/VSI-Bench under `choices`." | |
| }, | |
| "video_storage": { | |
| "format": "files", | |
| "media_root": "videos", | |
| "notes": "512 source videos (243 referenced by the MC split): arkitscenes (121), scannet (79), scannetpp (43). Videos are mirrored from lccshunli/VSIBench at 5.7 GB total; nyu-visionx/VSI-Bench provides only QA metadata. Each scene_name resolves to videos/<dataset_source>/<scene_name>.mp4. Frame sampling is the inference backend's responsibility." | |
| }, | |
| "mapping_from_source": { | |
| "media": { | |
| "from": "video_path", | |
| "type": "list", | |
| "min_items": 1, | |
| "max_items": 1 | |
| }, | |
| "id": { | |
| "from": "id" | |
| }, | |
| "question": { | |
| "from": "question" | |
| }, | |
| "answer": { | |
| "from": "ground_truth" | |
| }, | |
| "choices": { | |
| "from": "options" | |
| }, | |
| "extra": { | |
| "scene_name": { | |
| "from": "scene_name" | |
| }, | |
| "dataset_source": { | |
| "from": "dataset" | |
| }, | |
| "question_type": { | |
| "from": "question_type" | |
| } | |
| }, | |
| "source": { | |
| "format": "huggingface", | |
| "url": { | |
| "test": "https://huggingface.co/datasets/nyu-visionx/VSI-Bench (QA metadata, 'full' config); videos mirrored from https://huggingface.co/datasets/lccshunli/VSIBench" | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } |