| { | |
| "name": "HRBench4K", | |
| "release_date": "2026-05-15", | |
| "subsets": { | |
| "main": { | |
| "language": [ | |
| "en" | |
| ], | |
| "modalities": [ | |
| "single_image_start" | |
| ], | |
| "task_type": "multiple_choice_qa", | |
| "score_pipeline": [ | |
| "rule-match", | |
| "llm-match" | |
| ], | |
| "score_protocol": { | |
| "reference": "vlmevalkit@vlmeval/dataset/image_mcq.py:1302-1364 HRBenchDataset.evaluate -> mcq_vanilla_eval (can_infer + GPT extractor; DEFAULT_JUDGE ['chatgpt-0125','gpt-4-0125'] @vlmeval/dataset/image_mcq.py:1303) + report_acc_hrbench @vlmeval/dataset/utils/hrbench.py:7-29 (per-cycle x category accuracy, averaged over 4 cycles). HR-Bench authors (DreamMr/HR-Bench) vendor VLMEvalKit, so this is tier-1. Cross-check: lmms-eval hrbench also GPT-extracts (lmms_eval/tasks/hrbench/utils.py:24)", | |
| "note": "Official report averages accuracy per cycle_category (0-3) and per category (single/cross); the mm-eval copy ships all 4 rotations as rows (800 = 4 x 200, cycle_category field preserved in extra), so overall per-sample accuracy equals the official 'all' average (cycles partition the file); the per-category/per-cycle breakdown itself is not reproduced per-sample. Note this is NOT CircularEval — each rotation counts independently." | |
| }, | |
| "prompt_template": "<image>Question: {{ question }}\nOptions:\nA. {{ options.A }}\nB. {{ options.B }}\nC. {{ options.C }}\nD. {{ options.D }}\nPlease select the correct answer from the options above. \n", | |
| "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" | |
| }, | |
| "A": { | |
| "from": "A" | |
| }, | |
| "B": { | |
| "from": "B" | |
| }, | |
| "C": { | |
| "from": "C" | |
| }, | |
| "D": { | |
| "from": "D" | |
| }, | |
| "cycle_category": { | |
| "from": "cycle_category" | |
| } | |
| }, | |
| "source": { | |
| "format": "json", | |
| "url": { | |
| "hrbench_4k": "https://huggingface.co/datasets/DreamMr/HR-Bench" | |
| } | |
| } | |
| }, | |
| "prompt_template_source": { | |
| "origin": "official", | |
| "reference": "https://github.com/open-compass/VLMEvalKit/blob/main/vlmeval/dataset/image_mcq.py (ImageMCQDataset.build_prompt — Question:/Options:/A.B.C.D./'Please select the correct answer from the options above. ' trailer; HR-Bench authors' eval at https://github.com/DreamMr/HR-Bench/blob/main/hrbench/vlmeval/dataset/image_mcq.py inherits this via HRBenchDataset)", | |
| "notes": "Tier 1/3: HR-Bench authors use VLMEvalKit's ImageMCQDataset.build_prompt; mm-eval prompt reproduces it byte-for-byte. lmms-eval's hrbench_doc_to_text uses a different trailer ('Answer the option letter directly.') and is not the canonical reference." | |
| } | |
| } | |
| } | |
| } |