R-Bench-V / 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": "R-Bench-V",
"release_date": "2026-05-25",
"subsets": {
"main": {
"language": [
"en"
],
"modalities": [
"single_image_start"
],
"task_type": "short_answer_qa",
"score_pipeline": [
"llm-judge"
],
"score_params": {
"rubric": "binary",
"official_judge_model": "gpt-4o"
},
"score_protocol": {
"reference": "official paper arXiv:2505.16770 §4.2 — 'we adopt a unified LLM-as-a-Judge framework, with the judge model being GPT-4o. We report Top-1 accuracy (%) as our default evaluation metric.' for all 803 questions (both MCQ and open-ended); official eval code released as a VLMEvalKit fork (github.com/CHEN-Xinsheng/VLMEvalKit_RBench-V). [Quote re-verified verbatim against arxiv.org/html/2505.16770 §4.2, 2026-07-07.]",
"note": "Every sample is officially judge-graded binary; ground truths are often multi-part/unit-laden strings (e.g. '(1)60W(2)80%', '11cm'), so rule pre-resolution is unreliable and was not part of the official protocol. Not present in upstream VLMEvalKit or lmms-eval. NOTE: the math/physics/game/counting splits are category re-slices of the full split (176+157+275+195=803) — pooling any category split with 'full' double-counts; official headline = accuracy over the 803 'full' rows."
},
"prompt_template": "{% if has_image %}<image>{% endif %}{{ question }}",
"mapping_from_source": {
"media": {
"from": "image",
"type": "list",
"min_items": 0,
"max_items": 1
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"catagory": {
"from": "catagory"
},
"has_image": {
"from": "has_image"
}
},
"source": {
"format": "huggingface",
"url": {
"full": "https://huggingface.co/datasets/R-Bench/R-Bench-V",
"math": "https://huggingface.co/datasets/R-Bench/R-Bench-V",
"physics": "https://huggingface.co/datasets/R-Bench/R-Bench-V",
"game": "https://huggingface.co/datasets/R-Bench/R-Bench-V",
"counting": "https://huggingface.co/datasets/R-Bench/R-Bench-V"
}
}
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/SCUT-DLVCLab/R-Bench (R-Bench-V official: bare image+question with has_image conditional)",
"notes": "Tier 1: R-Bench-V official evaluation prompt as published by the dataset authors."
}
}
}
}