| { |
| "name": "MathVerse", |
| "release_date": "2024-03-22", |
| "subsets": { |
| "testmini": { |
| "language": [ |
| "en" |
| ], |
| "modalities": [ |
| "single_image_start" |
| ], |
| "task_type": "multiple_choice_qa", |
| "score_type": "rule_llm_judge", |
| "score_protocol": { |
| "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]", |
| "note": "Official protocol judges with an LLM after LLM extraction (binary 0/1); VLMEvalKit pre-resolves exact string matches by rule, which this classification adopts. mm-eval publishes the answer-only protocol (query_wo prompts, 'please directly answer'), not the official CoT eval (query_cot + multi-step CoT judging) — scores are comparable to VLMEvalKit MathVerse_MINI, not to the paper's CoT-E numbers. The HF repo also carries a testmini_text_only config (788 rows, no image) that metadata.json does not describe as a subset." |
| }, |
| "prompt_template": "<image>{{ question }}", |
| "prompt_template_source": { |
| "origin": "source_column", |
| "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)", |
| "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim and prepend <image>." |
| }, |
| "mapping_from_source": { |
| "media": { |
| "from": "image", |
| "type": "list", |
| "min_items": 1, |
| "max_items": 1 |
| }, |
| "id": { |
| "from": "sample_index" |
| }, |
| "question": { |
| "from": "query_wo" |
| }, |
| "answer": { |
| "from": "answer", |
| "optional": true |
| }, |
| "extra": { |
| "question_type": { |
| "from": "question_type" |
| }, |
| "problem_version": { |
| "from": "problem_version" |
| }, |
| "problem_index": { |
| "from": "problem_index" |
| }, |
| "source": { |
| "from": "source", |
| "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)" |
| }, |
| "subfield": { |
| "from": "subfield", |
| "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)" |
| }, |
| "subject": { |
| "from": "subject", |
| "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)" |
| } |
| }, |
| "source": { |
| "format": "huggingface", |
| "url": { |
| "testmini": "https://huggingface.co/datasets/AI4Math/MathVerse" |
| } |
| } |
| } |
| }, |
| "testmini_text_only": { |
| "language": [ |
| "en" |
| ], |
| "modalities": [ |
| "text" |
| ], |
| "task_type": "multiple_choice_qa", |
| "score_type": "rule_llm_judge", |
| "score_protocol": { |
| "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]", |
| "note": "Same protocol as the testmini subset (answer-only query_wo prompts, two-stage LLM extract+score). This subset IS the repo's testmini_text_only config (788 rows, text-dominant problems without the diagram image), previously published as data but undescribed in metadata.json; declared as a subset at the format-v3 re-emission." |
| }, |
| "prompt_template": "{{ question }}", |
| "prompt_template_source": { |
| "origin": "source_column", |
| "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)", |
| "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim. Text-only variant rows carry no media, so no <image> placeholder is prepended." |
| }, |
| "mapping_from_source": { |
| "media": { |
| "from": "image", |
| "type": "list", |
| "min_items": 0, |
| "max_items": 0 |
| }, |
| "id": { |
| "from": "sample_index" |
| }, |
| "question": { |
| "from": "query_wo" |
| }, |
| "answer": { |
| "from": "answer", |
| "optional": true |
| }, |
| "extra": { |
| "question_type": { |
| "from": "question_type" |
| }, |
| "problem_version": { |
| "from": "problem_version" |
| }, |
| "problem_index": { |
| "from": "problem_index" |
| }, |
| "source": { |
| "from": "source", |
| "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)" |
| }, |
| "subfield": { |
| "from": "subfield", |
| "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)" |
| }, |
| "subject": { |
| "from": "subject", |
| "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)" |
| } |
| }, |
| "source": { |
| "format": "huggingface", |
| "url": { |
| "testmini_text_only": "https://huggingface.co/datasets/AI4Math/MathVerse" |
| } |
| } |
| } |
| } |
| } |
| } |
|
|
