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"name": "VizWiz-VQA",
"release_date": "2024-01-01",
"subsets": {
"main": {
"language": [
"en"
],
"modalities": [
"single_image_start"
],
"task_type": "short_answer_qa",
"score_pipeline": [
"vqa-accuracy"
],
"score_protocol": {
"reference": "lmms-eval@lmms_eval/tasks/vizwiz_vqa/utils.py:13-36 (vizwiz_vqa_process_results) verified: EvalAIAnswerProcessor then acc=min(1,#matches/3) over 10 answers. Published answer maps from source `answers` (10-item list) — CONFIRMED retained: rows show list[10].",
"note": "Fractional per-sample VQA accuracy over 10 reference answers. VizWiz includes an 'unanswerable' class handled inside the same 10-answer voting; no separate aggregation."
},
"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": {
"val": "https://huggingface.co/datasets/lmms-lab/VizWiz-VQA"
}
}
},
"prompt_template_source": {
"origin": "official",
"reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/vizwiz_vqa/utils.py (vizwiz_vqa_doc_to_text — canonical short-answer with VizWiz-specific 'When the provided information is insufficient, respond with Unanswerable.' or canonical trailer)",
"notes": "Tier 4: lmms-eval VizWiz-VQA canonical evaluation prompt."
}
}
}
} |