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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 21 – 28 of 28 21 Knowledge distillation for quality estimation Specia, Lucia; Aletras, Nikolaos; Gajbhiye, Amit; Blain, Frederic; Fomicheva, Marina; Alva-Manchego, Fernando; Obamuyide, Abiola In: 5091 ; 5099 (2021) Abstract: © 2021 The Authors. Published by ACL. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://aclanthology.org/2021.findings-acl.452 ; Quality Estimation (QE) is the task of automatically predicting Machine Translation quality in the absence of reference translations, making it applicable in real-time settings, such as translating online social media conversations. Recent success in QE stems from the use of multilingual pre-trained representations, where very large models lead to impressive results. However, the inference time, disk and memory requirements of such models do not allow for wide usage in the real world. Models trained on distilled pre-trained representations remain prohibitively large for many usage scenarios. We instead propose to directly transfer knowledge from a strong QE teacher model to a much smaller model with a different, shallower architecture. We show that this approach, in combination with data augmentation, leads to light-weight QE models that perform competitively with distilled pre-trained representations with 8x fewer parameters. Keyword: knowledge distillation; machine translation; quality estimation URL: https://doi.org/10.18653/v1/2021.findings-acl.452 http://hdl.handle.net/2436/624102 BASE Hide details 22 Complaint Identification in Social Media with Transformer Networks ... Jin, Mali; Aletras, Nikolaos. - : arXiv, 2020 BASE Show details 23 Point-of-Interest Type Inference from Social Media Text ... Villegas, Danae Sánchez; Preoţiuc-Pietro, Daniel; Aletras, Nikolaos. - : arXiv, 2020 BASE Show details 24 Analyzing Political Parody in Social Media ... Maronikolakis, Antonis; Villegas, Danae Sanchez; Preotiuc-Pietro, Daniel. - : arXiv, 2020 BASE Show details 25 Complaint Identification in Social Media with Transformer Networks ... The 28th International Conference on Computational Linguistics 2020; Aletras, Nikolaos; Jin, Mali. - : Underline Science Inc., 2020 BASE Show details 26 Unsupervised quality estimation for neural machine translation Fomicheva, Marina; Guzmán, Francisco; Chaudhary, Vishrav... In: 8 ; 539 ; 555 (2020) BASE Show details 27 Automatically Identifying Complaints in Social Media ... Preotiuc-Pietro, Daniel; Gaman, Mihaela; Aletras, Nikolaos. - : arXiv, 2019 BASE Show details 28 PATHS: A System for Accessing Cultural Heritage Collections Aletras, Nikolaos; Goodale, Paula; Soroa, Aitor. - : Association for Computational Linguistics, 2013 BASE Show details Page: 1 2

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