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Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System., , , and . NAACL-HLT, page 1351-1360. Association for Computational Linguistics, (2021)Learning to Select from Multiple Options., , , and . AAAI, page 12754-12762. AAAI Press, (2023)Zero-shot User Intent Detection via Capsule Neural Networks., , , , and . EMNLP, page 3090-3099. Association for Computational Linguistics, (2018)HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization., , , , , and . EMNLP (1), page 146-154. Association for Computational Linguistics, (2021)Pseudo Siamese Network for Few-shot Intent Generation., , and . SIGIR, page 2005-2009. ACM, (2021)BL-MNE: Emerging Heterogeneous Social Network Embedding Through Broad Learning with Aligned Autoencoder., , , , , and . ICDM, page 605-614. IEEE Computer Society, (2017)Composed Variational Natural Language Generation for Few-shot Intents., , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 3379-3388. Association for Computational Linguistics, (2020)User Preference-aware Fake News Detection., , , , and . SIGIR, page 2051-2055. ACM, (2021)Low-shot Learning in Natural Language Processing., , , , , and . CogMI, page 185-189. IEEE, (2020)All Labels Together: Low-shot Intent Detection with an Efficient Label Semantic Encoding Paradigm., , , , and . IJCNLP (2), page 131-138. Association for Computational Linguistics, (2023)