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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 Hits 1 – 20 of 24 1 Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help? ... Saleh, Fahimeh; Buntine, Wray; Haffari, Gholamreza. - : arXiv, 2021 BASE Show details 2 Generalised Unsupervised Domain Adaptation of Neural Machine Translation with Cross-Lingual Data Selection ... Vu, Thuy-Trang; He, Xuanli; Phung, Dinh. - : arXiv, 2021 BASE Show details 3 Uncertainty-Aware Balancing for Multilingual and Multi-Domain Neural Machine Translation Training ... Wu, Minghao; Li, Yitong; Zhang, Meng. - : arXiv, 2021 BASE Show details 4 Cognition-aware Cognate Detection ... Kanojia, Diptesh; Sharma, Prashant; Ghodekar, Sayali. - : arXiv, 2021 BASE Show details 5 Harnessing Cross-lingual Features to Improve Cognate Detection for Low-resource Languages ... Kanojia, Diptesh; Dabre, Raj; Dewangan, Shubham. - : arXiv, 2021 BASE Show details 6 Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning ... Arthur, Philip; Cohn, Trevor; Haffari, Gholamreza. - : arXiv, 2020 BASE Show details 7 SummPip: Unsupervised Multi-Document Summarization with Sentence Graph Compression ... Zhao, Jinming; Liu, Ming; Gao, Longxiang. - : arXiv, 2020 BASE Show details 8 Leveraging Discourse Rewards for Document-Level Neural Machine Translation ... Unanue, Inigo Jauregi; Esmaili, Nazanin; Haffari, Gholamreza; Piccardi, Massimo. - : arXiv, 2020 Abstract: Document-level machine translation focuses on the translation of entire documents from a source to a target language. It is widely regarded as a challenging task since the translation of the individual sentences in the document needs to retain aspects of the discourse at document level. However, document-level translation models are usually not trained to explicitly ensure discourse quality. Therefore, in this paper we propose a training approach that explicitly optimizes two established discourse metrics, lexical cohesion (LC) and coherence (COH), by using a reinforcement learning objective. Experiments over four different language pairs and three translation domains have shown that our training approach has been able to achieve more cohesive and coherent document translations than other competitive approaches, yet without compromising the faithfulness to the reference translation. In the case of the Zh-En language pair, our method has achieved an improvement of 2.46 percentage points (pp) in LC and 1.17 pp ... : Accepted at COLING 2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2010.03732 https://arxiv.org/abs/2010.03732 BASE Hide details 9 Collective Wisdom: Improving Low-resource Neural Machine Translation using Adaptive Knowledge Distillation ... Saleh, Fahimeh; Buntine, Wray; Haffari, Gholamreza. - : arXiv, 2020 BASE Show details 10 Learning to Multi-Task Learn for Better Neural Machine Translation ... Zaremoodi, Poorya; Haffari, Gholamreza. - : arXiv, 2020 BASE Show details 11 Learning how to active learn by dreaming Liu, Ming; Phung, Dinh; Haffari, Gholamreza. - : Association for Computational Linguistics, 2019 BASE Show details 12 Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations ... Maruf, Sameen; Martins, André F. T.; Haffari, Gholamreza. - : arXiv, 2018 BASE Show details 13 Sequence to Sequence Mixture Model for Diverse Machine Translation ... He, Xuanli; Haffari, Gholamreza; Norouzi, Mohammad. - : arXiv, 2018 BASE Show details 14 Learning how to actively learn: a deep imitation learning approach Buntine, Wray; Haffari, Gholamreza; Liu, Ming. - : Association for Computational Linguistics, 2018 BASE Show details 15 Learning to actively learn neural machine translation Haffari, Gholamreza; Buntine, Wray; Liu, Ming. - : Association for Computational Linguistics, 2018 BASE Show details 16 Neural Machine Translation for Bilingually Scarce Scenarios: A Deep Multi-task Learning Approach ... Zaremoodi, Poorya; Haffari, Gholamreza. - : arXiv, 2018 BASE Show details 17 Phonemic transcription of low-resource tonal languages Adams, Oliver; Cohn, Trevor; Neubig, Graham... In: ISSN: 1834-7037 ; Australasian Language Technology Association Workshop 2017 ; https://halshs.archives-ouvertes.fr/halshs-01656683 ; Australasian Language Technology Association Workshop 2017, Dec 2017, Brisbane, Australia. pp.53-60 (2017) BASE Show details 18 Towards Decoding as Continuous Optimization in Neural Machine Translation ... Hoang, Cong Duy Vu; Haffari, Gholamreza; Cohn, Trevor. - : arXiv, 2017 BASE Show details 19 Leveraging linguistic resources for improving neural text classification Liu, Ming; Haffari, Gholamreza; Buntine, Wray. - : Australian Language Technology Association, 2017 BASE Show details 20 Phonemic transcription of low-resource tonal languages Adams, Oliver; Cohn, Trevor; Neubig, Graham... In: ISSN: 1834-7037 ; Australasian Language Technology Association Workshop 2017 ; https://halshs.archives-ouvertes.fr/halshs-01656683 ; Australasian Language Technology Association Workshop 2017, Dec 2017, Brisbane, Australia. pp.53-60 (2017) BASE Show details Page: 1 2

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