| { | |
| "name": "PathVQA", | |
| "release_date": "2003-03-30", | |
| "subsets": { | |
| "main": { | |
| "language": [ | |
| "en" | |
| ], | |
| "modalities": [ | |
| "single_image_start" | |
| ], | |
| "task_type": "yes_no_qa", | |
| "score_pipeline": [ | |
| "exact-match", | |
| "rule-match", | |
| "llm-judge" | |
| ], | |
| "score_protocol": { | |
| "reference": "VLMEvalKit@vlmeval/dataset/image_shortqa.py:144-160 (PathVQA_VAL/PathVQA_TEST -> ImageShortQADataset.evaluate, lines 87-142) verified: grades short answers with an LLM judge (build_judge default gpt-4o-mini via Comprehensive_auxeval / ShortQA_auxeval line 15), with exact_matching fallback when model=='exact_matching' or the API is down. Returns binary correctness (report_acc).", | |
| "note": "Official/standard med-VQA reports closed-ended (yes/no) accuracy plus open-ended token-recall/F1; VLMEvalKit ships an LLM-judge correctness grader. Modeled here as rule_llm_judge: deterministic exact match resolves closed yes/no rows, LLM judge grades open answers. Token-F1 open metric is not reproduced per-sample." | |
| }, | |
| "prompt_template": "<image>{{ question }}\nPlease directly provide a short answer to the question. ", | |
| "mapping_from_source": { | |
| "media": { | |
| "from": "image", | |
| "type": "list", | |
| "min_items": 1, | |
| "max_items": 1 | |
| }, | |
| "id": { | |
| "from": "-" | |
| }, | |
| "question": { | |
| "from": "question" | |
| }, | |
| "answer": { | |
| "from": "answer", | |
| "optional": true | |
| }, | |
| "source": { | |
| "format": "huggingface", | |
| "url": { | |
| "train": "https://huggingface.co/datasets/flaviagiammarino/path-vqa", | |
| "validation": "https://huggingface.co/datasets/flaviagiammarino/path-vqa", | |
| "test": "https://huggingface.co/datasets/flaviagiammarino/path-vqa" | |
| } | |
| } | |
| }, | |
| "prompt_template_source": { | |
| "origin": "official", | |
| "reference": "VLMEvalKit vlmeval/dataset/image_shortqa.py#L80-L84 (ImageShortQADataset.build_prompt, byte-verified in clone; PathVQA registered as ShortQA)", | |
| "notes": "Tier 3: VLMEvalKit ShortQA trailer (with its official trailing space). Fixed 2026-07-07 (previous LLaVA-1.5-style trailer matched no source; LLaVA-Med feeds the raw question but is a model harness, not a benchmark prompt spec)." | |
| } | |
| } | |
| } | |
| } |