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"name": "MEGA-Bench",
"release_date": "2024-10-18",
"subsets": {
"main": {
"language": [
"en"
],
"modalities": [
"multi_image_interleave",
"text"
],
"task_type": "short_answer_qa",
"score_pipeline": {
"unsupported": "per-task-metric",
"reason": "requires the benchmark's own evaluator (per-row metric dispatch)"
},
"score_params": {
"metric_field": "task_name"
},
"score_protocol": {
"reference": "lmms-eval@lmms_eval/tasks/megabench/metrics/metric_type.py:1-120 + metrics/scoring/* (45 per-task metric types: exact/near str match, set/dict equality+Jaccard, BLEU/GLEU, Levenshtein similarity, nbbox IoU, number_rel_diff_ratio, LaTeX equality, program_judge, symbolic planning, VLM-as-judge, ...) and tasks/megabench/README.md + evaluator.py — official protocol (adapted from TIGER-AI-Lab/MEGA-Bench) runs a stand-alone evaluator that dispatches each task to its own metric; core split = rule metrics, open split = GPT(-4o) judge; headline = macro mean over ~505 tasks.",
"note": "The mm-eval copy merges test_core and test_open into one subset and stores only task_name in extra — the per-task metric/aggregation/parsing config required by the official evaluator is not shipped, so no executable score_pipeline can reproduce the official protocol (declared unsupported). Many metrics are fractional per-sample; official headline is macro-averaged per task, not per-sample mean."
},
"prompt_template": "{{ question }}",
"mapping_from_source": {
"media": {
"from": "images",
"type": "list",
"min_items": 0,
"max_items": 21
},
"id": {
"from": "id"
},
"question": {
"from": "question"
},
"answer": {
"from": "answer",
"optional": true
},
"extra": {
"task_name": {
"from": "task_name"
}
},
"source": {
"format": "json",
"url": {
"test_core": "https://huggingface.co/datasets/TIGER-Lab/MEGA-Bench",
"test_open": "https://huggingface.co/datasets/TIGER-Lab/MEGA-Bench"
}
}
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/TIGER-AI-Lab/MEGA-Bench/blob/main/megabench/loader.py (task_description+example_text+query_text concatenated into question column at conversion time; template is bare {{ question }})",
"notes": "Tier 1: MEGA-Bench: per-task scaffolding (task_description, example_text, query_text) is concatenated into the question column at conversion time; template is intentionally bare to avoid double-scaffolding."
}
}
}
} |