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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 Hits 1 – 11 of 11 1 UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Iryna; ., Sebastian. - : Underline Science Inc., 2021 BASE Show details 2 MirrorWiC: On Eliciting Word-in-Context Representations from Pretrained Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Nigel; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 3 Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Nigel; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 4 SemEval-2020 Task 3: Graded Word Similarity in Context ... The 28th International Conference on Computational Linguistics 2020; Armendariz, Carlos; Ljubešić, Nikola. - : Underline Science Inc., 2020 BASE Show details 5 Emergent Communication Pretraining for Few-Shot Machine Translation ... The 28th International Conference on Computational Linguistics 2020; Korhonen, Anna; Li, Yaoyiran; Ponti, Edoardo; Vulić, Ivan. - : Underline Science Inc., 2020 Abstract: While state-of-the-art models that rely upon massively multilingual pretrained encoders achieve sample efficiency in downstream applications, they still require abundant amounts of unlabelled text. Nevertheless, most of the world's languages lack such resources. Hence, we investigate a more radical form of unsupervised knowledge transfer in the absence of linguistic data. In particular, for the first time we pretrain neural networks via emergent communication from referential games. Our key assumption is that grounding communication on images---as a crude approximation of real-world environments---inductively biases the model towards learning natural languages. On the one hand, we show that this substantially benefits machine translation in few-shot settings. On the other hand, this also provides an extrinsic evaluation protocol to probe the properties of emergent languages \textit{ex vitro}. Intuitively, the closer they are to natural languages, the higher the gains from pretraining on them should be. For ... Keyword: Computer and Information Science; Natural Language Processing; Neural Network URL: https://underline.io/lecture/6290-emergent-communication-pretraining-for-few-shot-machine-translation https://dx.doi.org/10.48448/13e8-dh54 BASE Hide details 6 Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ... The 28th International Conference on Computational Linguistics 2020; Korhonen, Anna; Majewska, Olga. - : Underline Science Inc., 2020 BASE Show details 7 SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ... The 28th International Conference on Computational Linguistics 2020; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2020 BASE Show details 8 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... The 28th International Conference on Computational Linguistics 2020; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2020 BASE Show details 9 A deep learning approach to bilingual lexicon induction in the biomedical domain. ... Heyman, Geert; Vulić, Ivan; Moens, Marie-Francine. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 10 A deep learning approach to bilingual lexicon induction in the biomedical domain. Heyman, Geert; Vulić, Ivan; Moens, Marie-Francine. - : Springer Science and Business Media LLC, 2018. : BMC Bioinformatics, 2018 BASE Show details 11 Bio-SimVerb and Bio-SimLex: wide-coverage evaluation sets of word similarity in biomedicine. Chiu, Billy; Pyysalo, Sampo; Vulić, Ivan. - : BioMed Central, 2018. : BMC bioinformatics, 2018 BASE Show details

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