| { | |
| "name": "TheoremQA", | |
| "release_date": "2023-05-21", | |
| "subsets": { | |
| "image": { | |
| "language": [ | |
| "en" | |
| ], | |
| "modalities": [ | |
| "single_image_start" | |
| ], | |
| "task_type": "short_answer_qa", | |
| "score_pipeline": [ | |
| "exact-match", | |
| "rule-match" | |
| ], | |
| "score_params": { | |
| "numeric_rel_tol": 0.04 | |
| }, | |
| "score_protocol": { | |
| "reference": "official TIGER-AI-Lab/TheoremQA@utils.py compare_answer_with_groundtruth + number_utils.py compare_two_numbers/within_eps (float: 4% relative tolerance eps=abs(gt)*0.04; int: round(p)==gt; lists element-wise after sorting; option '(a)'..'(f)' substring; strings case-insensitive equality); run_gpt.py splits the response on the literal 'answer is ' — no LLM in extraction or grading. [Re-verified 2026-07-07 against the live repo: eps = abs(gt) * 0.04 in number_utils.py; round(p)==gt for ints; sorted element-wise list compare.]", | |
| "note": "Official inference prompt instructs 'Therefore, the answer is ...' which the rule split relies on; the mm-eval prompt is bare <image>{{question}} with no final-answer instruction, so extraction robustness is reduced (template matchers must handle free-form output). mm-eval ships only the 53-row image subset of the 800-question benchmark (documented in metadata); official overall accuracy not reproducible. List-typed answers (e.g. '[2, 2]') need element-wise numeric comparison, beyond plain exact matching." | |
| }, | |
| "prompt_template": "<image>{{ question }}", | |
| "prompt_template_source": { | |
| "origin": "official", | |
| "reference": "https://huggingface.co/datasets/TIGER-Lab/TheoremQA", | |
| "notes": "Tier 1: TheoremQA image subset — multimodal theorem-driven open-ended QA. Filtered to rows with Picture column non-null (text-only rows excluded to fit single-image VQA schema; preserve image subset under \"image\" subset name)." | |
| }, | |
| "mapping_from_source": { | |
| "media": { | |
| "from": "images", | |
| "type": "list", | |
| "min_items": 1, | |
| "max_items": 1 | |
| }, | |
| "id": { | |
| "from": "id" | |
| }, | |
| "question": { | |
| "from": "question" | |
| }, | |
| "answer": { | |
| "from": "answer", | |
| "optional": true | |
| }, | |
| "extra": { | |
| "n_images": { | |
| "from": "n_images" | |
| }, | |
| "answer_type": { | |
| "from": "answer_type" | |
| } | |
| }, | |
| "source": { | |
| "format": "json", | |
| "url": { | |
| "test": "https://huggingface.co/datasets/TIGER-Lab/TheoremQA" | |
| } | |
| } | |
| } | |
| } | |
| } | |
| } |