{ "name": "PhyX", "release_date": "2025-01-01", "subsets": { "mc": { "language": [ "en" ], "modalities": [ "single_image_start" ], "task_type": "multiple_choice_qa", "score_pipeline": [ "exact-match", "rule-match", "llm-judge" ], "score_protocol": { "reference": "VLMEvalKit@vlmeval/dataset/utils/phyx.py:333-373 (PhyX_process_line_MC: regex letter extraction + case-insensitive string compare) and :214-253 (PhyX_auxeval_MC: rule match first; LLM semantic 1/0 judgement only for responses not resolved to a clean option letter). Authors' recommended flow (repo points to VLMEvalKit; --judge deepseek, image_vqa.py:3441-3448); lmms-eval@lmms_eval/tasks/phyx/phyx.yaml (quick_extract: false, eval_model_name deepseek-chat) uses the same PhyX_auxeval_MC path. [Re-verified in clone 2026-07-07: PhyX_process_line_MC at phyx.py:336-375, PhyX_auxeval_MC at :218-254 (letter mismatch scored 0 without judge at :236-238), evaluate valid_type assert at image_vqa.py:3448-3455, phyx.yaml:9-10.]", "note": "Official judge model is deepseek-chat. Rule-extracted letters that mismatch are scored 0 without a judge call; the judge only handles non-letter/verbose responses. mm-eval ships only the MC subset (phyx_mc + phyx_mini_mc splits); official OE subset and its text-only variants are not published. NOTE: phyx_mini_mc's 1000 ids are fully contained in phyx_mc's 3000 — pooling both splits double-counts the mini rows; evaluate one split at a time." }, "prompt_template": "{{ question }}", "mapping_from_source": { "media": { "from": "image", "type": "list", "min_items": 1, "max_items": 1 }, "id": { "from": "index" }, "question": { "from": "question" }, "answer": { "from": "answer", "optional": true }, "extra": { "category": { "from": "category" }, "subfield": { "from": "subfield" } }, "source": { "format": "huggingface", "url": { "phyx_mc": "https://huggingface.co/datasets/Cloudriver/PhyX", "phyx_mini_mc": "https://huggingface.co/datasets/Cloudriver/PhyX" } } }, "prompt_template_source": { "origin": "official", "reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/phyx/utils.py (phyx_doc_to_text — bare question; multi-choice variant)", "notes": "Tier 4: lmms-eval PhyX canonical evaluation prompt." } } } }