🔗 Who cites «Attention Strategies for Multi-Source Sequence-to-Sequence Learning»

79 papers of our library cite it (of the 141,840 whose bibliographies we read) · 7 with a page here, the most cited first · ← back to «Attention Strategies for Multi-Source Sequence-to-Sequence Learning»

TaBERT: Pretraining for Joint Understanding of Textual and Tabular DataAnnual Meeting of the Association for Computational Linguistics (ACL)Pengcheng Yin, Graham Neubig, Wen-tau Yih, et al.2020 · 690 citations
1. Evaluating Discourse Phenomena in Neural Machine TranslationarXiv:1711.00513Rachel Bawden, Rico Sennrich, Alexandra Birch, et al.2017 · 252 citations
   Probing the Need for Visual Context in Multimodal Machine TranslationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Ozan Caglayan, Pranava Madhyastha, Lucia Specia, et al.2019 · 215 citations
   Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image DescriptionConference on Machine Translation (WMT)Desmond Elliott, Stella Frank, Loïc Barrault, et al.2017 · 134 citations
   Good for Misconceived Reasons: An Empirical Revisiting on the Need for Visual Context in Multimodal Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyong Wu, Lingpeng Kong, Wei Bi, et al.2021 · 119 citations
2. Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOMarXiv:2303.01911Rachel Bawden, François Yvon2023 · 85 citations
3. Factorising AMR generation through syntaxKris Cao, Stephen Clark2019 · 28 citations

72 more papers of our library cite it; they have no page here yet.

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