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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 58 1 Horse or pony? Visual Typicality and Lexical Frequency Affect Variability in Object Naming ... Gualdoni, Eleonora; Brochhagen, Thomas; Mädebach, Andreas. - : University of Massachusetts Amherst, 2022 BASE Show details 2 The interaction between cognitive ease and informativeness shapes the lexicons of natural languages ... Brochhagen, Thomas; Boleda, Gemma. - : University of Massachusetts Amherst, 2022 BASE Show details 3 Horse or pony? Visual Typicality and Lexical Frequency Affect Variability in Object Naming Gualdoni, Eleonora; Brochhagen, Thomas; Mädebach, Andreas... In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 4 The interaction between cognitive ease and informativeness shapes the lexicons of natural languages Brochhagen, Thomas; Boleda, Gemma In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 5 Does referent predictability affect the choice of referential form? A computational approach using masked coreference resolution ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aina, Laura; Boleda, Gemma. - : Underline Science Inc., 2021 BASE Show details 6 Does referent predictability affect the choice of referential form? A computational approach using masked coreference resolution ... Aina, Laura; Liao, Xixian; Boleda, Gemma. - : arXiv, 2021 BASE Show details 7 Deep daxes: Mutual exclusivity arises through both learning biases and pragmatic strategies in neural networks ... Gulordava, Kristina; Brochhagen, Thomas; Boleda, Gemma. - : arXiv, 2020 BASE Show details 8 A closer look at scalar diversity using contextualized semantic similarity Westera, Matthijs; Boleda, Gemma In: Sinn und Bedeutung; Bd. 24 Nr. 2 (2020): Proceedings of Sinn und Bedeutung 24; 439-454 ; Proceedings of Sinn und Bedeutung; Vol 24 No 2 (2020): Proceedings of Sinn und Bedeutung 24; 439-454 ; 2629-6055 (2020) BASE Show details 9 Recurrent Instance Segmentation using Sequences of Referring Expressions ... Herrera-Palacio, Alba; Ventura, Carles; Silberer, Carina. - : arXiv, 2019 BASE Show details 10 Don't Blame Distributional Semantics if it can't do Entailment ... Westera, Matthijs; Boleda, Gemma. - : arXiv, 2019 BASE Show details 11 What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue ... Aina, Laura; Silberer, Carina; Westera, Matthijs. - : arXiv, 2019 BASE Show details 12 Putting words in context: LSTM language models and lexical ambiguity ... Aina, Laura; Gulordava, Kristina; Boleda, Gemma. - : arXiv, 2019 BASE Show details 13 Instantiation ... Gupta, Abhijeet; Boleda, Gemma; Pado, Sebastian. - : arXiv, 2018 BASE Show details 14 Living a discrete life in a continuous world: Reference with distributed representations ... Boleda, Gemma; Padó, Sebastian; Pham, Nghia The. - : arXiv, 2017 BASE Show details 15 The LAMBADA dataset ... Paperno, Denis; Kruszewski, Germán; Lazaridou, Angeliki. - : Zenodo, 2016 BASE Show details 16 The LAMBADA dataset ... Paperno, Denis; Kruszewski, Germán; Lazaridou, Angeliki. - : Zenodo, 2016 BASE Show details 17 The LAMBADA dataset: Word prediction requiring a broad discourse context ... Paperno, Denis; Kruszewski, Germán; Lazaridou, Angeliki; Pham, Quan Ngoc; Bernardi, Raffaella; Pezzelle, Sandro; Baroni, Marco; Boleda, Gemma; Fernández, Raquel. - : arXiv, 2016 Abstract: We introduce LAMBADA, a dataset to evaluate the capabilities of computational models for text understanding by means of a word prediction task. LAMBADA is a collection of narrative passages sharing the characteristic that human subjects are able to guess their last word if they are exposed to the whole passage, but not if they only see the last sentence preceding the target word. To succeed on LAMBADA, computational models cannot simply rely on local context, but must be able to keep track of information in the broader discourse. We show that LAMBADA exemplifies a wide range of linguistic phenomena, and that none of several state-of-the-art language models reaches accuracy above 1% on this novel benchmark. We thus propose LAMBADA as a challenging test set, meant to encourage the development of new models capable of genuine understanding of broad context in natural language text. ... : 10 pages, Accepted as a long paper for ACL 2016 ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://arxiv.org/abs/1606.06031 https://dx.doi.org/10.48550/arxiv.1606.06031 BASE Hide details 18 "Show me the cup": Reference with Continuous Representations ... Boleda, Gemma; Padó, Sebastian; Baroni, Marco. - : arXiv, 2016 BASE Show details 19 Zipf’s Law for Word Frequencies: Word Forms versus Lemmas in Long Texts Corral, Álvaro; Boleda, Gemma; Ferrer-i-Cancho, Ramon. - : Public Library of Science, 2015 BASE Show details 20 Wikicorpus Boleda, Gemma. - : Centro de Tecnologías y Aplicaciones del Lenguaje y del Habla (TALP), 2014 BASE Show details Page: 1 2 3

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