AI RESEARCH
CobSeg: Coherence Boundary Modeling for Dialogue Topic Segmentation
arXiv CS.AI
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ArXi:2605.30668v1 Announce Type: cross Dialogue topic segmentation is critical in many human-AI collaborative applications which requires identifying heterogeneous boundary cues, including lexical transitions near utterance edges and semantic discontinuities across utterances. Existing utterance models often dilute these local lexical signals. We propose CobSeg, a novel multi-branch architecture that separates coherence-level semantic continuity from lexical boundary transitions and recovers both through directional boundary prediction.