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Learning Context-Specific Word/Character Embeddings., , , , и . AAAI, стр. 3393-3399. AAAI Press, (2017)Context-Specific and Multi-Prototype Character Representations., , , и . IJCAI, стр. 3007-3013. IJCAI/AAAI Press, (2016)In-Context Learning with Many Demonstration Examples., , , , , , и . CoRR, (2023)The Volctrans GLAT System: Non-autoregressive Translation Meets WMT21., , , , , , , , , и . WMT@EMNLP, стр. 187-196. Association for Computational Linguistics, (2021)Counter-Interference Adapter for Multilingual Machine Translation., , , , и . EMNLP (Findings), стр. 2812-2823. Association for Computational Linguistics, (2021)DiffuSeq-v2: Bridging Discrete and Continuous Text Spaces for Accelerated Seq2Seq Diffusion Models., , , , и . EMNLP (Findings), стр. 9868-9875. Association for Computational Linguistics, (2023)DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models., , , , и . ICLR, OpenReview.net, (2023)Geometric Relationship between Word and Context Representations., и . AAAI, стр. 5102-5109. AAAI Press, (2018)ZeroGen: Efficient Zero-shot Learning via Dataset Generation., , , , , , , и . EMNLP, стр. 11653-11669. Association for Computational Linguistics, (2022)ProGen: Progressive Zero-shot Dataset Generation via In-context Feedback., , , , , и . EMNLP (Findings), стр. 3671-3683. Association for Computational Linguistics, (2022)