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Efficient Large Scale Language Modeling with Mixtures of Experts, , , , , , , , , и 14 other автор(ы). (2021)cite arxiv:2112.10684Comment: EMNLP 2022.Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading., , , и . CoRR, (2023)Interactive Query-Assisted Summarization via Deep Reinforcement Learning., , , , и . NAACL-HLT, стр. 2551-2568. Association for Computational Linguistics, (2022)Efficient Large Scale Language Modeling with Mixtures of Experts., , , , , , , , , и 14 other автор(ы). EMNLP, стр. 11699-11732. Association for Computational Linguistics, (2022)Complementary Explanations for Effective In-Context Learning., , , , , и . ACL (Findings), стр. 4469-4484. Association for Computational Linguistics, (2023)Game-Based Video-Context Dialogue., и . EMNLP, стр. 125-136. Association for Computational Linguistics, (2018)AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning., , и . NAACL-HLT (1), стр. 3520-3531. Association for Computational Linguistics, (2019)Extending Multi-Document Summarization Evaluation to the Interactive Setting., , , , , и . NAACL-HLT, стр. 657-677. Association for Computational Linguistics, (2021)Towards Improving Abstractive Summarization via Entailment Generation., , и . NFiS@EMNLP, стр. 27-32. Association for Computational Linguistics, (2017)MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation., , , , и . ACL (Findings), стр. 11069-11090. Association for Computational Linguistics, (2023)