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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 – 6 of 6 1 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 2 Uncovering Main Causalities for Long-tailed Information Extraction ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Guo, Zhijiang; Lu, Wei; Nan, Guoshun; Qiao, Rui; Zeng, Jiaqi. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.763/ Abstract: Information Extraction (IE) aims to extract structural information from unstructured texts. In practice, long-tailed distributions caused by the selection bias of a dataset, may lead to incorrect correlations, also known as spurious correlations, between entities and labels in the conventional likelihood models. This motivates us to propose counterfactual IE (CFIE), a novel framework that aims to uncover the main causalities behind data in the view of causal inference. Specifically, 1) we first introduce a unified structural causal model (SCM) for various IE tasks, describing the relationships among variables; 2) with our SCM, we then generate counterfactuals based on an explicit language structure to better calculate the direct causal effect during the inference stage; 3) we further propose a novel debiasing approach to yield more robust predictions. Experiments on three IE tasks across five public datasets show the effectiveness ... Keyword: Computational Linguistics; Information Extraction; Machine Learning; Machine Learning and Data Mining; Natural Language Processing URL: https://underline.io/lecture/37638-uncovering-main-causalities-for-long-tailed-information-extraction https://dx.doi.org/10.48448/53zx-4546 BASE Hide details 3 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 4 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 5 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 6 Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning Guo, Zhijiang; Zhang, Yan; Teng, Zhiyang... In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 297-312 (2019) (2019) BASE Show details

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