TinyBench / Fullset /qa_v00.json
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[
{
"id": "0",
"doc_id": [
"TinyBench/videommmu_paper.pdf"
],
"file_type": "paper pdf",
"question": "What are novelties of Video-MMMU dataset",
"question_type": "summary",
"evidence_type": "text",
"answer": "1) Knowledge-Intensive Video Collection: The dataset includes 300 expert-level videos across 6 professional disciplines, covering 30 subjects. 2) Knowledge Acquisition-Based QA Design: Each video contains three QA pairs corresponding to the stages of knowledge acquisition—Perception (extracting key information), Comprehension (grasping concepts), and Adaptation (applying knowledge to new contexts). 3) Quantitative Knowledge Assessment: they introduce a delta knowledge metric to measure performance gains on practice exam questions after watching the videos, enabling quantitative evaluation of LMMs' ability to learn and apply new knowledge.",
"content_domain": "Academic paper",
"Comment": ""
},
{
"id": "1",
"doc_id": [
"TinyBench/videommmu_paper.pdf"
],
"file_type": "paper pdf",
"question": "How QA pairs are categorized in Video-MMMU?",
"question_type": "summary",
"evidence_type": "text",
"answer": "Perception Questions assess the ability to extract information from videos via: 1) Optical Character Recognition (OCR) and 2) Automatic Speech Recognition (ASR). Comprehension Questions evaluate understanding through: 1) Concept Comprehension (CC) and 2) Problem-Solving Strategy Comprehension (PSC). Adaptation Questions test the ability to apply knowledge to new scenarios via: 1) Case Study Analysis (CSA) and 2) Problem-Solving Strategy Adaptation (PSA).",
"content_domain": "Academic paper",
"Comment": ""
}
]