{ "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": "{{ 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" } } } } } }