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    • Glavaš, Goran (8)
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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 – 8 of 8 1 Crossing the Conversational Chasm: A Primer on Natural Language Processing for Multilingual Task-Oriented Dialogue Systems ... Razumovskaia, Evgeniia; Glavaš, Goran; Majewska, Olga. - : arXiv, 2021 BASE Show details 2 Verb Knowledge Injection for Multilingual Event Processing ... 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; Glavaš, Goran; Korhonen, Anna. - : Underline Science Inc., 2021 BASE Show details 3 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ... Ponti, Edoardo Maria; Glavaš, Goran; Majewska, Olga. - : arXiv, 2020 BASE Show details 4 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning ... Ponti, Edoardo; Glavaš, Goran; Majewska, Olga. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 5 Verb Knowledge Injection for Multilingual Event Processing ... Majewska, Olga; Vulić, Ivan; Glavaš, Goran; Ponti, Edoardo M.; Korhonen, Anna. - : arXiv, 2020 Abstract: In parallel to their overwhelming success across NLP tasks, language ability of deep Transformer networks, pretrained via language modeling (LM) objectives has undergone extensive scrutiny. While probing revealed that these models encode a range of syntactic and semantic properties of a language, they are still prone to fall back on superficial cues and simple heuristics to solve downstream tasks, rather than leverage deeper linguistic knowledge. In this paper, we target one such area of their deficiency, verbal reasoning. We investigate whether injecting explicit information on verbs' semantic-syntactic behaviour improves the performance of LM-pretrained Transformers in event extraction tasks -- downstream tasks for which accurate verb processing is paramount. Concretely, we impart the verb knowledge from curated lexical resources into dedicated adapter modules (dubbed verb adapters), allowing it to complement, in downstream tasks, the language knowledge obtained during LM-pretraining. We first demonstrate ... : 19 pages, 1 figure, 8 tables ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2012.15421 https://dx.doi.org/10.48550/arxiv.2012.15421 BASE Hide details 6 XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning Liu, Qianchu; Korhonen, Anna-Leena; Majewska, Olga. - : Association for Computational Linguistics, 2020. : Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2020), 2020 BASE Show details 7 Common sense or world knowledge? Investigating adapter-based knowledge injection into pretrained transformers Lauscher, Anne; Majewska, Olga; Ribeiro, Leonardo F. R.. - : Association for Computational Linguistics, 2020 BASE Show details 8 XCOPA: A multilingual dataset for causal commonsense reasoning Ponti, Edoardo Maria; Majewska, Olga; Liu, Qianchu. - : Association for Computational Linguistics, 2020 BASE Show details

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