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cs.CV2026
SER: Learning to Ground Video Reasoning with Semantic Evidence Rewards
Sheng Xia, Zhengqin Lai, Tianxiang Jiang +4
Video MLLMs often struggle with fine-grained spatio-temporal reasoning, sometimes generating correct answers based on irrelevant frames or objects. Although outputting spatio-tempo…
cs.CV2025
M-Med: A Benchmark for Multi-lingual, Multi-modal, and Multi-hop Reasoning in Medical Instructional Video Understanding
Shenxi Liu, Kan Li, Mingyang Zhao +5
With the rapid progress of artificial intelligence (AI) in multi-modal understanding, there is increasing potential for video comprehension technologies to support professional dom…
cs.CV2025
Overview of the NLPCC 2025 Shared Task 4: Multi-modal, Multilingual, and Multi-hop Medical Instructional Video Question Answering Challenge
Bin Li, Shenxi Liu, Yixuan Weng +3
Following the successful hosts of the 1-st (NLPCC 2023 Foshan) CMIVQA and the 2-rd (NLPCC 2024 Hangzhou) MMIVQA challenges, this year, a new task has been introduced to further adv…