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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)

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Deep Learning Embeddings for Discontinuous Linguistic Units., and . ICLR (Workshop Poster), (2014)Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference., , and . CoRR, (2022)MT-Ranker: Reference-free machine translation evaluation by inter-system ranking., , and . CoRR, (2024)Meta-learning for Few-shot Natural Language Processing: A Survey. (2020)cite arxiv:2007.09604Comment: no submission intent.Empirical evaluation of multi-task learning in deep neural networks for natural language processing., , , , , and . Neural Comput. Appl., 33 (9): 4417-4428 (2021)Mixup-Transformer: Dynamic Data Augmentation for NLP Tasks., , , , , and . COLING, page 3436-3440. International Committee on Computational Linguistics, (2020)Event Linking: Grounding Event Mentions to Wikipedia., , , and . EACL, page 2671-2680. Association for Computational Linguistics, (2023)Robustness of Learning from Task Instructions., , , , , and . ACL (Findings), page 13935-13948. Association for Computational Linguistics, (2023)Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning., , , , and . EMNLP, page 6998-7010. Association for Computational Linguistics, (2023)Robustness of Learning from Task Instructions., , , and . CoRR, (2022)