Q-Bench-Plus / metadata.json
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metadata: migrate score_type -> score_pipeline (atomic stage contract; see mm-eval scorer docs/en/SCORING.md)
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{
"name": "Q-Bench-Plus",
"release_date": "2024-04-15",
"subsets": {
"default": {
"language": [
"en"
],
"modalities": [
"multi_image_start"
],
"task_type": "multiple_choice_qa",
"score_pipeline": [
"rule-match",
"llm-match"
],
"score_protocol": {
"reference": "official paper@arXiv:2402.07116 (Q-Bench+) — GPT-assisted evaluation matches the model's MCQ answer to the choices, with 5-round voting (raises match accuracy 93.2%->98.4%). Cross-check: lmms-eval@lmms_eval/tasks/qbench/qbench2_dev.yaml + utils.py:42-100,103-119 — rule-only MMMU-style parse then exact compare; VLMEvalKit hosts the sibling Q-Bench1/A-Bench as ImageMCQDataset (image_mcq.py:89-94) = rule prefetch + GPT extraction.",
"note": "Official uses 5-round GPT voting for answer matching; our llm_extract chain does rule prefetch + single-pass LLM extraction. lmms-eval variant is rule-only and falls back to a RANDOM choice when unparseable (not reproduced). Published copy = dev split (public-labeled), options stored as extra fields option0-option3 with 'N/A' padding possible."
},
"prompt_template": "{% for _ in range(n_images) %}<image>{% endfor %}{{ question }}\nA. {{ options.option0 }}\nB. {{ options.option1 }}\nC. {{ options.option2 }}\nD. {{ options.option3 }}\nAnswer with the option's letter from the given choices directly.",
"prompt_template_source": {
"origin": "official",
"reference": "https://huggingface.co/datasets/q-future/Q-Bench2-HF",
"notes": "Tier 1: Q-Bench2 (Q-Bench+) paired-image quality MCQ; dev split is the public-labeled split."
},
"mapping_from_source": {
"media": {
"from": "images",
"type": "list",
"min_items": 2,
"max_items": 2
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"n_images": {
"from": "n_images"
},
"option0": {
"from": "option0"
},
"option1": {
"from": "option1"
},
"option2": {
"from": "option2"
},
"option3": {
"from": "option3"
},
"question_type": {
"from": "question_type"
},
"question_concern": {
"from": "question_concern"
}
},
"source": {
"format": "json",
"url": {
"dev": "https://huggingface.co/datasets/q-future/Q-Bench2-HF"
}
}
}
}
}
}