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cs.CV2026
A Paradigm Shift: Fully End-to-End Training for Temporal Sentence Grounding in Videos
Allen He, Qi Liu, Kun Liu +2
Temporal sentence grounding in videos (TSGV) aims to localize a temporal segment that semantically corresponds to a sentence query from an untrimmed video. Most current methods ado…
cs.CV2026
Magic-MM-Embedding: Towards Visual-Token-Efficient Universal Multimodal Embedding with MLLMs
Qi Li, Yanzhe Zhao, Yongxin Zhou +4
Multimodal Large Language Models (MLLMs) have shown immense promise in universal multimodal retrieval, which aims to find relevant items of various modalities for a given query. Ho…