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"name": "MMHal-Bench",
"release_date": "2023-12-01",
"subsets": {
"main": {
"language": [
"en"
],
"modalities": [
"single_image_start"
],
"task_type": "open_ended_qa",
"score_pipeline": [
"llm-judge"
],
"score_params": {
"rubric": "scale",
"scale": [
0,
6
],
"official_judge_model": "gpt-4",
"judge_inputs": [
"image_content"
]
},
"score_protocol": {
"reference": "Official eval script https://huggingface.co/datasets/Shengcao1006/MMHal-Bench/blob/main/eval_gpt4.py (lines 94-96: judge template consumes image_content, question, gt_answer, model_answer) — GPT-4 rates each response 0-6 (informativeness x hallucination rubric: 0-2 = hallucination present, 3-6 = none). Not implemented in VLMEvalKit or lmms-eval.",
"note": "Official headline = average rating (0-6) AND hallucination rate = fraction of responses rated 0-2, with per-question-type breakdown (8 types x 12 questions, 96 rows). Per-sample binary grading deviates. Rows carry the image_content object list (extra) that the official judge template interpolates. Per-row question_type extra carries MMHal categories (attribute/relation/holistic/other...), NOT scorer vocabulary — scorer must not treat it as a question_type signal."
},
"prompt_template": "<image>{{ question }}",
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/open-compass/VLMEvalKit/blob/main/vlmeval/dataset/image_vqa.py (MMHal-Bench — judge-scored; bare question)",
"notes": "Tier 3: MMHal-Bench judge-scored eval: bare question per the official MMHal-Bench paper."
},
"mapping_from_source": {
"media": {
"from": "image",
"type": "list",
"min_items": 1,
"max_items": 1
},
"id": {
"from": "image_id"
},
"question": {
"from": "question"
},
"answer": {
"from": "gt_answer",
"optional": true
},
"extra": {
"question_type": {
"from": "question_type"
},
"image_content": {
"from": "image_content"
}
},
"source": {
"format": "json",
"url": {
"test": "https://huggingface.co/datasets/Shengcao1006/MMHal-Bench"
}
}
}
}
}
} |