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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 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 Grammatical Profiling for Semantic Change Detection ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Giulianelli, Mario; Kutuzov, Andrey. - : Underline Science Inc., 2021 BASE Show details 4 Refer, Reuse, Reduce: Generating Subsequent References in Visual and Conversational Contexts ... Takmaz, Ece; Giulianelli, Mario; Pezzelle, Sandro; Sinclair, Arabella; Fernández, Raquel. - : arXiv, 2020 Abstract: Dialogue participants often refer to entities or situations repeatedly within a conversation, which contributes to its cohesiveness. Subsequent references exploit the common ground accumulated by the interlocutors and hence have several interesting properties, namely, they tend to be shorter and reuse expressions that were effective in previous mentions. In this paper, we tackle the generation of first and subsequent references in visually grounded dialogue. We propose a generation model that produces referring utterances grounded in both the visual and the conversational context. To assess the referring effectiveness of its output, we also implement a reference resolution system. Our experiments and analyses show that the model produces better, more effective referring utterances than a model not grounded in the dialogue context, and generates subsequent references that exhibit linguistic patterns akin to humans. ... : In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) ... Keyword: Computation and Language cs.CL; Computer Vision and Pattern Recognition cs.CV; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2011.04554 https://arxiv.org/abs/2011.04554 BASE Hide details 5 UiO-UvA at SemEval-2020 Task 1: Contextualised Embeddings for Lexical Semantic Change Detection ... Kutuzov, Andrey; Giulianelli, Mario. - : arXiv, 2020 BASE Show details 6 Analysing Lexical Semantic Change with Contextualised Word Representations ... Giulianelli, Mario; Del Tredici, Marco; Fernández, Raquel. - : arXiv, 2020 BASE Show details 7 DUPS: Diachronic Usage Pair Similarity ... Giulianelli, Mario; Del Tredici, Marco; Fernández, Raquel. - : Zenodo, 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 Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information ... Giulianelli, Mario; Harding, Jacqueline; Mohnert, Florian. - : arXiv, 2018 BASE Show details 11 Semi-supervised emotion lexicon expansion with label propagation and specialized word embeddings ... Giulianelli, Mario. - : arXiv, 2017 BASE Show details

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