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Large language models are not zero-shot communicators

, , , , , и . (2022)cite arxiv:2210.14986.

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Large language models are not zero-shot communicators, , , , , и . (2022)cite arxiv:2210.14986.Multitask Prompted Training Enables Zero-Shot Task Generalization, , , , , , , , , и 30 other автор(ы). International Conference on Learning Representations, (2022)Fooling MOSS Detection with Pretrained Language Models., и . CIKM, стр. 2933-2943. ACM, (2022)RWKV: Reinventing RNNs for the Transformer Era., , , , , , , , , и 22 other автор(ы). EMNLP (Findings), стр. 14048-14077. Association for Computational Linguistics, (2023)Lessons from the Trenches on Reproducible Evaluation of Language Models., , , , , , , , , и 20 other автор(ы). CoRR, (2024)Why Has Predicting Downstream Capabilities of Frontier AI Models with Scale Remained Elusive?, , , , , , , , и . CoRR, (2024)What Language Model to Train if You Have One Million GPU Hours?, , , , , , , , , и 8 other автор(ы). EMNLP (Findings), стр. 765-782. Association for Computational Linguistics, (2022)Pitfalls in Machine Learning Research: Reexamining the Development Cycle., и . ICBINB@NeurIPS, том 137 из Proceedings of Machine Learning Research, стр. 106-117. PMLR, (2020)Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets., , , , , , , , , и 42 other автор(ы). Trans. Assoc. Comput. Linguistics, (2022)The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset., , , , , , , , , и 44 other автор(ы). NeurIPS, (2022)