@inproceedings{xia-liu-2026-event,
    title = "Event-Guided Slot Interaction for Multi-Domain Dialogue State Tracking",
    author = "Xia, Ying  and
      Liu, Wei",
    editor = "Bonial, Claire  and
      Berzak, Yevgeni",
    booktitle = "Proceedings of the 30th Conference on Computational Natural Language Learning",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.conll-main.30/",
    pages = "515--525",
    ISBN = "979-8-89176-410-1",
    abstract = "Multi-domain Dialogue State Tracking (DST) requires discourse coherence that transcends independent slot-filling. Most existing approaches rely on statistical regularities within static schemas, failing to capture the semantic coordination governing simultaneous slot updates. In this paper, we propose Event-DST, which models latent events as cognitive organizing units to dynamically coordinate slot interactions. By projecting dialogue context into a continuous semantic space, our model induces a dynamic structural bias to enforce pragmatic consistency. This structural guidance is integrated via a dual-stream fusion strategy that balances top-down structural constraints with bottom-up textual precision. Experimental results on two benchmarks demonstrate the superiority of our framework, providing an interpretable and parameter-efficient path toward robust dialogue understanding."
}