{
 "name": "OK-VQA",
 "release_date": "2024-01-01",
 "subsets": {
  "main": {
   "language": [
    "en"
   ],
   "modalities": [
    "single_image_start"
   ],
   "task_type": "short_answer_qa",
   "score_type": "vqa_accuracy",
   "score_protocol": {
    "reference": "lmms-eval@lmms_eval/tasks/ok_vqa/utils.py:13-36 (ok_vqa_process_results) verified: EvalAIAnswerProcessor normalization then acc=min(1,#matches/3) averaged over the 10-answer list. Published answer maps from source `answers` (10-item list) — confirmed retained in rows.",
    "note": "Fractional per-sample VQA accuracy averaged over held-out-one of 10 reference answers; headline is mean over samples."
   },
   "prompt_template": "<image>{{ question }}\nAnswer the question using a single word or phrase.",
   "mapping_from_source": {
    "media": {
     "from": "image",
     "type": "list",
     "min_items": 1,
     "max_items": 1
    },
    "id": {
     "from": "question_id"
    },
    "question": {
     "from": "question"
    },
    "answer": {
     "from": "answers",
     "optional": true
    },
    "source": {
     "format": "huggingface",
     "url": {
      "val2014": "https://huggingface.co/datasets/lmms-lab/OK-VQA"
     }
    }
   },
   "prompt_template_source": {
    "origin": "official",
    "reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/ok_vqa/utils.py (ok_vqa_doc_to_text — canonical short-answer)",
    "notes": "Tier 4: lmms-eval OK-VQA canonical evaluation prompt."
   }
  }
 }
}