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Meta-learning for Few-shot Natural Language Processing: A Survey

. (2020)cite arxiv:2007.09604Comment: no submission intent.

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Query-focused multi-document summarization based on query-sensitive feature space., , , and . CIKM, page 1652-1656. ACM, (2012)Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach., , and . EMNLP/IJCNLP (1), page 3912-3921. Association for Computational Linguistics, (2019)Learning to Synthesize Data for Semantic Parsing., , , and . NAACL-HLT, page 2760-2766. Association for Computational Linguistics, (2021)Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning., , , , and . CoRR, (2023)LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing., , , , , , , , , and 30 other author(s). CoRR, (2024)Fighting Against the Repetitive Training and Sample Dependency Problem in Few-shot Named Entity Recognition., , , and . CoRR, (2024)Learning Meta-Embeddings by Using Ensembles of Embedding Sets, and . (2015)cite arxiv:1508.04257Comment: 10 pages, 6 figures.Toward Zero-Shot Instruction Following., and . EACL (Student Research Workshop), page 50-60. Association for Computational Linguistics, (2024)Adv-BERT: BERT is not robust on misspellings! Generating nature adversarial samples on BERT., , , , , , and . CoRR, (2020)Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims., , , , and . NAACL-HLT (1), page 542-557. Association for Computational Linguistics, (2019)