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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 1 – 20 of 69 1 Transformer Grammars: Augmenting Transformer Language Models with Syntactic Inductive Biases at Scale ... Sartran, Laurent; Barrett, Samuel; Kuncoro, Adhiguna. - : arXiv, 2022 BASE Show details 2 Diverse Pretrained Context Encodings Improve Document Translation ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Donato, Domenic; Dyer, Chris. - : Underline Science Inc., 2021 BASE Show details 3 Better {C}hinese Sentence Segmentation with Reinforcement Learning ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Dyer, Chris; Srinivasan, Srivatsan. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.findings-acl.25 Abstract: A long-standing challenge in Chinese–English machine translation is that sentence boundaries are ambiguous in Chinese orthography, but inferring good splits is necessary for obtaining high quality translations. To solve this, we use reinforcement learning to train a segmentation policy that splits Chinese texts into segments that can be independently translated so as to maximise the overall translation quality. We compare to a variety of segmentation strategies and find that our approach improves the baseline BLEU score on the WMT2020 Chinese–English news translation task by +0.3 BLEU overall and improves the score on input segments that contain more than 60 words by +3 BLEU. ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://underline.io/lecture/26116-better-chinese-sentence-segmentation-with-reinforcement-learning https://dx.doi.org/10.48448/600m-w705 BASE Hide details 4 Learning Robust and Multilingual Speech Representations ... Kawakami, Kazuya; Wang, Luyu; Dyer, Chris. - : arXiv, 2020 BASE Show details 5 Better Document-Level Machine Translation with Bayes’ Rule Yu, Lei; Sartran, Laurent; Stokowiec, Wojciech... In: Transactions of the Association for Computational Linguistics, Vol 8, Pp 346-360 (2020) (2020) BASE Show details 6 Learning and Evaluating General Linguistic Intelligence ... Yogatama, Dani; d'Autume, Cyprien de Masson; Connor, Jerome. - : arXiv, 2019 BASE Show details 7 Shallow Syntax in Deep Water ... Swayamdipta, Swabha; Peters, Matthew; Roof, Brendan. - : arXiv, 2019 BASE Show details 8 Unsupervised Bilingual POS Tagging with Markov Random Fields ... Desai Chen; Dyer, Chris; Cohen, Shay B.. - : Figshare, 2018 BASE Show details 9 Unsupervised Bilingual POS Tagging with Markov Random Fields ... Desai Chen; Dyer, Chris; Cohen, Shay B.. - : Figshare, 2018 BASE Show details 10 Knowledge-Rich Morphological Priors for Bayesian Language Models ... Chahuneau, Victor; Smith, Noah A.; Dyer, Chris. - : Figshare, 2018 BASE Show details 11 Learning to Discover, Ground and Use Words with Segmental Neural Language Models ... Kawakami, Kazuya; Dyer, Chris; Blunsom, Phil. - : arXiv, 2018 BASE Show details 12 Paraphrase-Supervised Models of Compositionality ... Saluja, Avneesh; Dyer, Chris; Ruvini, Jean-David. - : arXiv, 2018 BASE Show details 13 From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042) Cho, Kyunghyun; Dyer, Chris; Blunsom, Phil. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, 2017. : Dagstuhl Reports. Dagstuhl Reports, Volume 7, Issue 1, 2017 BASE Show details 14 Learning to Create and Reuse Words in Open-Vocabulary Neural Language Modeling ... Kawakami, Kazuya; Dyer, Chris; Blunsom, Phil. - : arXiv, 2017 BASE Show details 15 From Characters to Understanding Natural Language (C2NLU): Robust End-to-End Deep Learning for NLP (Dagstuhl Seminar 17042) ... Blunsom, Phil; Cho, Kyunghyun; Dyer, Chris. - : Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik GmbH, Wadern/Saarbruecken, Germany, 2017 BASE Show details 16 Ontology-Aware Token Embeddings for Prepositional Phrase Attachment ... Dasigi, Pradeep; Ammar, Waleed; Dyer, Chris. - : arXiv, 2017 BASE Show details 17 Massively Multilingual Word Embeddings ... Ammar, Waleed; Mulcaire, George; Tsvetkov, Yulia. - : arXiv, 2016 BASE Show details 18 Many Languages, One Parser ... Ammar, Waleed; Mulcaire, George; Ballesteros, Miguel. - : arXiv, 2016 BASE Show details 19 Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning ... Tsvetkov, Yulia; Manaal Faruqui; Ling, Wang. - : Carnegie Mellon University, 2016 BASE Show details 20 Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning ... Tsvetkov, Yulia; Manaal Faruqui; Ling, Wang. - : Carnegie Mellon University, 2016 BASE Show details Page: 1 2 3 4

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