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Distinguishing semantically similar queries in temporal video grounding via LLM-generated query | Synapse
March 3, 2026
Distinguishing semantically similar queries in temporal video grounding via LLM-generated query
YD
Yibo Dang
ZQ
Zhaobo Qi
City University of Hong Kong
XL
Xinyan Liu
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Key Points
Query distinction improves video grounding accuracy, enhancing overall performance.
Key evidence includes notable advancements in processing semantically similar queries, showing up to a 30% increase in accuracy.
Analysis of temporal video grounding utilizes LLM-generated queries to identify unique query features for differentiation.
Findings imply that artificial intelligence can significantly enhance query processing, potentially streamlining video content interactions.
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Cite This Study
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Dang et al. (Tue,) studied this question.
synapsesocial.com/papers/69a76653badf0bb9e87dc973
https://doi.org/https://doi.org/10.1007/s00530-025-02147-z