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Xiaokun Liu

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#artificial intelligence Preprint Oct 2026

EventLens: Event-Structure Reinforcement Learning for Video Understanding

Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure that makes a video coherent. They may merge neighboring events, miss single-event progression, or infer implausible relations across events. We study structured temporal u...

Guo-Wen Zhang, Bo-Shen Xu, Zihao Yue et al. · 0 citations
Jul 2026

TimePLE: Rethinking Temporal Representation for Video Temporal Grounding

TimePLE is proposed, which reformulates VTG from endpoint prediction to interval-native grounding by predicting a single joint distribution over valid temporal intervals, and curate 90K-scale grounded samples and human-verify 3K-scale benchmark annotations.

Yuhui Zeng, Xin-Yu Mao, Xiaokun Liu et al. · 0 citations

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