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"name": "MuirBench",
"release_date": "2024-06-06",
"subsets": {
"main": {
"language": [
"en"
],
"modalities": [
"multi_image_interleave"
],
"task_type": "multiple_choice_qa",
"score_pipeline": [
"exact-match",
"rule-match"
],
"score_protocol": {
"reference": "official@github.com/muirbench/MuirBench eval/utils/postprocess.py:13 (parse_multi_choice_response) — deterministic string matching: '(A)' form, then isolated ' A ', then option-content substring for long responses; random option as last resort (L42-43, random.seed(42)); no LLM. lmms-eval@lmms_eval/tasks/muirbench/muirbench.yaml:23-37 + utils.py (MultiChoiceRegexFilter + lowercase exact match, muir_aggregation) agrees.",
"note": "Official falls back to a RANDOM choice when nothing matches — a per-sample scorer should instead mark unparseable responses incorrect (deterministic, slightly stricter). VLMEvalKit's MUIRDataset (image_mcq.py:667) inherits the generic MCQ pipeline with optional GPT extraction, but the authors' own code is LLM-free. Official reporting is overall accuracy plus per-task accuracy (lmms-eval utils.py muir_aggregation)."
},
"prompt_template": "{{ question }}",
"mapping_from_source": {
"media": {
"from": "images",
"type": "list",
"min_items": 2,
"max_items": 9
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"task": {
"from": "task"
}
},
"source": {
"format": "json",
"url": {
"test": "https://huggingface.co/datasets/MUIRBENCH/MUIRBENCH"
}
}
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/open-compass/VLMEvalKit/blob/main/vlmeval/dataset/image_mcq.py (MUIRDataset.build_prompt — question column already bakes 'Answer with the option letter only.' trailer; bare-question template avoids duplication)",
"notes": "Tier 3: VLMEvalKit MUIRDataset.build_prompt: MuirBench's question column already contains its answer-format trailer baked in, so the official handling is bare {{ question }}."
}
}
}
} |