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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 Hits 1 – 20 of 46 1 Is Information Density Uniform in Task-Oriented Dialogues? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Fernández, Raquel; Giulianelli, Mario. - : Underline Science Inc., 2021 BASE Show details 2 Analysing Human Strategies of Information Transmission as a Function of Discourse Context ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Fernández, Raquel; Giulianelli, Mario. - : Underline Science Inc., 2021 BASE Show details 3 Semantic shift in social networks ... 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; Fernández, Raquel; Larsson, Staffan. - : Underline Science Inc., 2021 BASE Show details 4 Syntactic Persistence in Language Models: Priming as a Window into Abstract Language Representations ... Sinclair, Arabella; Jumelet, Jaap; Zuidema, Willem. - : arXiv, 2021 BASE Show details 5 Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts ... Takmaz, Ece; Giulianelli, Mario; Pezzelle, Sandro. - : arXiv, 2020 BASE Show details 6 Words are the Window to the Soul: Language-based User Representations for Fake News Detection ... The 28th International Conference on Computational Linguistics 2020; Del Tredici, Marco; Fernández, Raquel. - : Underline Science Inc., 2020 BASE Show details 7 Analysing Lexical Semantic Change with Contextualised Word Representations ... Giulianelli, Mario; Del Tredici, Marco; Fernández, Raquel. - : arXiv, 2020 BASE Show details 8 DUPS: Diachronic Usage Pair Similarity ... Giulianelli, Mario; Del Tredici, Marco; Fernández, Raquel. - : Zenodo, 2020 BASE Show details 9 DUPS: Diachronic Usage Pair Similarity ... Giulianelli, Mario; Del Tredici, Marco; Fernández, Raquel. - : Zenodo, 2020 BASE Show details 10 DUPS: Diachronic Usage Pair Similarity ... Giulianelli, Mario; Del Tredici, Marco; Fernández, Raquel. - : Zenodo, 2020 BASE Show details 11 Disentangling dialects: a neural approach to Indo-Aryan historical phonology and subgrouping Cathcart, Chundra; Rama, Taraka In: Cathcart, Chundra; Rama, Taraka (2020). Disentangling dialects: a neural approach to Indo-Aryan historical phonology and subgrouping. In: Fernández, Raquel; Linzen, Tal. Proceedings of the 24th Conference on Computational Natural Language Learning. Online: Association for Computational Linguistics, 620-630. (2020) BASE Show details 12 Identifying robust markers of Parkinson's disease in typing behaviour using a CNN-LSTM network. Dhir, Neil; Bannard, Colin J; Stafford, Tom. - : Association for Computational Linguistics, 2020 BASE Show details 13 Evaluating the Representational Hub of Language and Vision Models ... Shekhar, Ravi; Takmaz, Ece; Fernández, Raquel. - : arXiv, 2019 BASE Show details 14 Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts ... Pezzelle, Sandro; Fernández, Raquel. - : arXiv, 2019 BASE Show details 15 MALeViC: Modeling Adjectives Leveraging Visual Contexts ... Pezzelle, Sandro; Fernández, Raquel. - : Zenodo, 2019 BASE Show details 16 MALeViC: Modeling Adjectives Leveraging Visual Contexts ... Pezzelle, Sandro; Fernández, Raquel. - : Zenodo, 2019 BASE Show details 17 You Shall Know a User by the Company It Keeps: Dynamic Representations for Social Media Users in NLP ... Del Tredici, Marco; Marcheggiani, Diego; Walde, Sabine Schulte im; Fernández, Raquel. - : arXiv, 2019 Abstract: Information about individuals can help to better understand what they say, particularly in social media where texts are short. Current approaches to modelling social media users pay attention to their social connections, but exploit this information in a static way, treating all connections uniformly. This ignores the fact, well known in sociolinguistics, that an individual may be part of several communities which are not equally relevant in all communicative situations. We present a model based on Graph Attention Networks that captures this observation. It dynamically explores the social graph of a user, computes a user representation given the most relevant connections for a target task, and combines it with linguistic information to make a prediction. We apply our model to three different tasks, evaluate it against alternative models, and analyse the results extensively, showing that it significantly outperforms other current methods. ... : To appear in Proceeding of EMNLP 2019 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1909.00412 https://dx.doi.org/10.48550/arxiv.1909.00412 BASE Hide details 18 Psycholinguistics meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering ... Greco, Claudio; Plank, Barbara; Fernández, Raquel. - : arXiv, 2019 BASE Show details 19 La adquisición del lenguaje de tres a seis años y sus posibles trastornos López Fernández, Raquel. - 2019 BASE Show details 20 Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat ... Shekhar, Ravi; Venkatesh, Aashish; Baumgärtner, Tim. - : arXiv, 2018 BASE Show details Page: 1 2 3

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