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Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery.

, , , , , , , and . ACL (1), page 9661-9675. Association for Computational Linguistics, (2023)

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Improving Few-Shot Performance of DST Model Through Multitask to Better Serve Language-Impaired People., , , , , and . ICASSP Workshops, page 1-5. IEEE, (2023)Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection., , , , , , , , and . LREC/COLING, page 2354-2364. ELRA and ICCL, (2024)UEGP: Unified Expert-Guided Pre-training for Knowledge Rekindle., , , , , , , , , and . NAACL-HLT (Findings), page 2661-2673. Association for Computational Linguistics, (2024)Exploiting domain-slot related keywords description for Few-Shot Cross-Domain Dialogue State Tracking., , , , , , , and . EMNLP, page 2460-2465. Association for Computational Linguistics, (2022)Value type: the bridge to a better DST model., , , , and . ACL (Findings), page 1211-1219. Association for Computational Linguistics, (2023)Generalized Intent Discovery: Learning from Open World Dialogue System., , , , , , , , and . COLING, page 707-720. International Committee on Computational Linguistics, (2022)Decoupling Pseudo Label Disambiguation and Representation Learning for Generalized Intent Discovery., , , , , , , and . ACL (1), page 9661-9675. Association for Computational Linguistics, (2023)Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent Recognition., , , , , , and . EMNLP (Findings), page 4370-4382. Association for Computational Linguistics, (2023)Large Language Models Meet Open-World Intent Discovery and Recognition: An Evaluation of ChatGPT., , , , , , , , and . EMNLP, page 10291-10304. Association for Computational Linguistics, (2023)Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent Recognition., , , , , and . CoRR, (2023)