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"name": "BenchLMM",
"release_date": "2024-07-01",
"subsets": {
"main": {
"language": [
"en"
],
"modalities": [
"single_image_start"
],
"task_type": "short_answer_qa",
"score_pipeline": [
"llm-judge"
],
"score_params": {
"rubric": "scale",
"scale": [
0,
1
],
"official_judge_model": "gpt-4-0613"
},
"score_protocol": {
"reference": "official@github.com/AIFEG/BenchLMM evaluate/gpt_evaluation_script.py — GPT judge prompt: 'Compare the ground truth and prediction from AI models, to give a correctness score for the prediction' ignoring case/grammar, '/' = multiple acceptable answers, similar meaning gets full marks; judge outputs a score in {0.0,0.1,...,1.0}; example model gpt-4-0613; final metric = mean score (avg_score.py).",
"note": "Every sample is LLM-judged with fractional credit on a 0-1 scale (11 discrete values); headline is the mean per-sample score, not binary accuracy. The mm-eval copy has only 96 rows (test split) whereas official BenchLMM spans many style/domain files (CT, MRI, infrared, AD, RS, styles, Robots/Games, each with its own eval variant) — published copy appears to be a small subset."
},
"prompt_template": "<image>{{ question }}\nAnswer the question using a single word or phrase.",
"mapping_from_source": {
"media": {
"from": "image",
"type": "list",
"min_items": 1,
"max_items": 1
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"source": {
"format": "json",
"url": {
"test": "https://huggingface.co/datasets/AIFEG/BenchLMM"
}
}
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/AIFEG/BenchLMM/blob/main/baseline/LLaVA/BenchGPT_LLaVA_model_vqa.py#L44-L49 (qs = line['text']; DEFAULT_IMAGE_TOKEN + '\\n' + qs); trailer '\\nAnswer the question using a single word or phrase.' is embedded in every official jsonl 'text' field, e.g. https://github.com/AIFEG/BenchLMM/blob/main/jsonl/Benchmark_style_cartoon.jsonl",
"notes": "Tier 1: BenchLMM authors' own inference script feeds <image>\\n + question, and the official jsonl question text carries the '\\nAnswer the question using a single word or phrase.' trailer; the mm-eval template reproduces this (trailer re-appended because the mm-eval question column is trailer-free)."
}
}
}
} |