{
  "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"
          }
        }
      }
    }
  }
}