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Learning to Refine Source Representations for Neural Machine Translation., , , , , и . CoRR, (2018)Context-aware Self-Attention Networks for Natural Language Processing., , , , и . Neurocomputing, (2021)GPT4Video: A Unified Multimodal Large Language Model for lnstruction-Followed Understanding and Safety-Aware Generation., , , , , , , , , и . CoRR, (2023)Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modelling., , , , , , , , , и . CoRR, (2023)Benchmarking LLMs via Uncertainty Quantification., , , , , , , и . CoRR, (2024)Semantics-Enhanced Task-Oriented Dialogue Translation: A Case Study on Hotel Booking., , , , , и . IJCNLP (System Demonstrations), стр. 33-36. Association for Computational Linguistics, (2017)Learning to refine source representations for neural machine translation., , , , , , и . Int. J. Mach. Learn. Cybern., 13 (8): 2199-2212 (2022)GuoFeng: A Benchmark for Zero Pronoun Recovery and Translation., , , , , , , и . EMNLP, стр. 11266-11278. Association for Computational Linguistics, (2022)Exploiting Cross-Sentence Context for Neural Machine Translation., , , и . EMNLP, стр. 2826-2831. Association for Computational Linguistics, (2017)On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation., , , , , , и . EMNLP (Findings), стр. 2900-2907. Association for Computational Linguistics, (2021)