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Ze-Long Xu

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#artificial intelligence Preprint Sep 2026

SyncRA: Learning Temporal Correspondence in Omni-Modal Models

Recent omni-modal models demonstrate strong perception of audio and visual inputs, yet often struggle to connect what they hear with what they see at the same moment. This weakness in temporal correspondence can cause models to associate spoken cues with the wrong visual scenes, producing plausible answers grounded in...

Ze-Long Xu, Yan Li, Wenpen Hu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

CUA-SWE: When Computer-Use Agents Meet Visual Software Engineering

Software development requires more than editing code: developers repeatedly run software, interact with its interfaces, visually inspect its behavior, and use these observations to decide what to change next and whether a change works. Existing coding agents and computer-use agents are largely studied in isolation, lea...

P. Wang, Chen-Hao Liang, Ze-Long Xu et al. · 0 citations

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