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Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking., and . CoRR, (2019)Rare Words: A Major Problem for Contextualized Embeddings and How to Fix it by Attentive Mimicking., and . AAAI, page 8766-8774. AAAI Press, (2020)Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification., , and . COLING, page 5569-5578. International Committee on Computational Linguistics, (2020)Atlas: Few-shot Learning with Retrieval Augmented Language Models, , , , , , , , , and . (2022)cite arxiv:2208.03299.LongForm: Optimizing Instruction Tuning for Long Text Generation with Corpus Extraction, , , and . (2023)EditEval: An Instruction-Based Benchmark for Text Improvements., , , , , , , , and . CoRR, (2022)Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor., , , and . ACL (1), page 14409-14428. Association for Computational Linguistics, (2023)MEAL: Stable and Active Learning for Few-Shot Prompting., , and . EMNLP (Findings), page 506-517. Association for Computational Linguistics, (2023)FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations., , and . CoRR, (2024)Augmented Language Models: a Survey., , , , , , , , , and 3 other author(s). Trans. Mach. Learn. Res., (2023)