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Generalized Intent Discovery: Learning from Open World Dialogue System.

, , , , , , , , and . COLING, page 707-720. International Committee on Computational Linguistics, (2022)

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Knowledge Editing on Black-box Large Language Models., , , , , , and . CoRR, (2024)Beyond the Known: Investigating LLMs Performance on Out-of-Domain Intent Detection., , , , , , , , and . CoRR, (2024)Improving Few-Shot Performance of DST Model Through Multitask to Better Serve Language-Impaired People., , , , , and . ICASSP Workshops, page 1-5. IEEE, (2023)Distribution Calibration for Out-of-Domain Detection with Bayesian Approximation., , , , , and . COLING, page 608-615. International Committee on Computational Linguistics, (2022)APP: Adaptive Prototypical Pseudo-Labeling for Few-shot OOD Detection., , , , , , , , and . EMNLP (Findings), page 3926-3939. Association for Computational Linguistics, (2023)UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood Learning., , , , , , and . EMNLP, page 7317-7325. Association for Computational Linguistics, (2022)Disentangled Knowledge Transfer for OOD Intent Discovery with Unified Contrastive Learning., , , , , , , and . ACL (2), page 46-53. Association for Computational Linguistics, (2022)Continual Generalized Intent Discovery: Marching Towards Dynamic and Open-world Intent Recognition., , , , , and . CoRR, (2023)Bridge Pre-Training and Clustering: A Unified Contrastive Learning Framework for OOD Intent Discovery., and . IEEE Access, (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)