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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 43 1 A Survey on Automated Fact-Checking Guo, Z; Schlichtkrull, M; Vlachos, Andreas. - : Department of Computer Science And Technology, 2022. : Transactions of the Association for Computational Linguistics, 2022 BASE Show details 2 Survival text regression for time-to-event prediction in conversations ... De Kock, C; Vlachos, Andreas. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 3 I beg to differ: A study of constructive disagreement in online conversations ... De Kock, C; Vlachos, Andreas. - : Apollo - University of Cambridge Repository, 2021 BASE Show details 4 I Beg to Differ: A study of constructive disagreement in online conversations ... de Kock, Christine; Vlachos, Andreas. - : arXiv, 2021 BASE Show details 5 Evidence-based Factual Error Correction ... 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; Throne, James; Vlachos, Andreas. - : Underline Science Inc., 2021 BASE Show details 6 The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Michael; Aly, Rami. - : Underline Science Inc., 2021 BASE Show details 7 Leveraging Type Descriptions for Zero-shot Named Entity Recognition and Classification ... 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; Aly, Rami; McDonald, Ryan. - : Underline Science Inc., 2021 BASE Show details 8 ProoFVer: Natural Logic Theorem Proving for Fact Verification ... Krishna, Amrith; Riedel, Sebastian; Vlachos, Andreas. - : arXiv, 2021 BASE Show details 9 Stance Detection in German News Articles Schneebeli, Christian; Ruzsics, Tatyana; Kadar, Cristina... In: Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER) (2021) BASE Show details 10 Evidence Selection as a Token-Level Prediction Task Stammbach, Dominik In: Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER) (2021) BASE Show details 11 I beg to differ: A study of constructive disagreement in online conversations de Kock, C; Vlachos, Andreas. - : Association for Computational Linguistics, 2021. : https://www.aclweb.org/anthology/2021.eacl-main.173, 2021. : EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, 2021 BASE Show details 12 Evidence-based factual error correction Thorne, J; Vlachos, Andreas. - : Association for Computational Linguistics, 2021. : https://aclanthology.org/2021.acl-long.256, 2021. : ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2021 BASE Show details 13 Leveraging type descriptions for zero-shot named entity recognition and classification Aly, R; Vlachos, Andreas; McDonald, R. - : Association for Computational Linguistics, 2021. : ACL-IJCNLP 2021 - 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2021 Abstract: A common issue in real-world applications of named entity recognition and classification (NERC) is the absence of annotated data for target entity classes during training. Zeroshot learning approaches address this issue by learning models that can transfer information from observed classes in the training data to unseen classes. This paper presents the first approach for zero-shot NERC, introducing a novel architecture that leverage the fact that textual descriptions for many entity classes occur naturally. Our architecture addresses the zero-shot NERC specific challenge that the not-an-entity class is not well defined, since different entity classes are considered in training and testing. For evaluation, we adapt two datasets, OntoNotes and MedMentions, emulating the difficulty of real-world zero-shot learning by testing models on the rarest entity classes. Our proposed approach outperforms baselines adapted from machine reading comprehension and zero-shot text classification. Furthermore, we assess the effect of different class descriptions for this task. URL: https://doi.org/10.17863/CAM.77922 https://www.repository.cam.ac.uk/handle/1810/330478 BASE Hide details 14 Elastic weight consolidation for better bias inoculation Thorne, J; Vlachos, Andreas. - : Association for Computational Linguistics, 2021. : https://www.aclweb.org/anthology/2021.eacl-main.82, 2021. : EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Proceedings of the Conference, 2021 BASE Show details 15 FANG-COVID: A new large-scale benchmark dataset for fake news detection in German Mattern, Justus; Qiao, Yu; Kerz, Elma. - : Association for Computational Linguistics (ACL), 2021 BASE Show details 16 Neural generative rhetorical structure parsing ... Mabona, A; Rimell, L; Clark, S. - : Apollo - University of Cambridge Repository, 2020 BASE Show details 17 Incorporating label dependencies in multilabel stance detection Ferreira, W; Vlachos, Andreas. - : Association for Computational Linguistics, 2020. : EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing, Proceedings of the Conference, 2020 BASE Show details 18 Neural generative rhetorical structure parsing Mabona, A; Rimell, L; Clark, S. - : Association for Computational Linguistics, 2020. : Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2020 BASE Show details 19 Model-agnostic meta-learning for relation classification with limited supervision Obamuyide, A; Vlachos, Andreas. - : ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, 2020 BASE Show details 20 Generating fact checking briefs Fan, A; Piktus, A; Petroni, F. - : Association for Computational Linguistics, 2020. : EMNLP 2020 - 2020 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference, 2020 BASE Show details Page: 1 2 3

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