{ "name": "MathVista", "release_date": "2026-05-15", "subsets": { "main": { "language": [ "en" ], "modalities": [ "single_image_start" ], "task_type": "multiple_choice_qa", "score_pipeline": [ "rule-match", "llm-match" ], "score_protocol": { "reference": "lmms-eval@lmms_eval/tasks/mathvista/mathvista_evals.py:218-266 — rule extraction first (direct choice match, int/float parse), GPT extraction fallback via DEMO_PROMPT; utils.py:48-62 normalize_extracted_answer + safe_equal rule compare. Mirrors official lupantech/MathVista (evaluation/extract_answer.py + calculate_score.py). [Re-verified in clone 2026-07-07: extract_answer at mathvista_evals.py:221-266, process_results/normalize/safe_equal at utils.py:48-64.]", "note": "Official float normalization rounds the extracted value to a per-row `precision` column (mathvista/utils.py:60); the mm-eval copy ships answer_type but not precision (the required precision is only stated in the hint text baked into the question). Mixed MCQ/free-form subset: MAJORITY format is multi_choice (540/1000 vs 460 free_form); per-sample question_type carries the split." }, "prompt_template": "{{ question }}", "mapping_from_source": { "media": { "from": "decoded_image", "type": "list", "min_items": 1, "max_items": 1 }, "id": { "from": "pid" }, "question": { "from": "query", "note": "use upstream `query` field (pre-built format-prompt with hint + question)" }, "answer": { "from": "answer", "optional": true }, "extra": { "question_type": { "from": "question_type" }, "answer_type": { "from": "answer_type" } }, "source": { "format": "json", "url": { "testmini": "https://huggingface.co/datasets/AI4Math/MathVista" } } }, "prompt_template_source": { "origin": "official", "reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/mathvista/utils.py (mathvista_doc_to_text — uses 'query' column which is pre-rendered)", "notes": "Tier 4: lmms-eval MathVista canonical: pre-rendered 'query' column from source; template is bare to forward unchanged." } } } }