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"name": "MathVerse",
"release_date": "2024-03-22",
"subsets": {
"testmini": {
"language": [
"en"
],
"modalities": [
"single_image_start"
],
"task_type": "multiple_choice_qa",
"score_pipeline": [
"exact-match",
"rule-match",
"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_pipeline": [
"exact-match",
"rule-match",
"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"
}
}
}
}
}
} |