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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 Hits 1 – 20 of 28 1 How does the pre-training objective affect what large language models learn about linguistic properties? ... Alajrami, Ahmed; Aletras, Nikolaos. - : arXiv, 2022 BASE Show details 2 Automatic Identification and Classification of Bragging in Social Media ... Jin, Mali; Preoţiuc-Pietro, Daniel; Doğruöz, A. Seza. - : arXiv, 2022 BASE Show details 3 Analyzing Online Political Advertisements ... Villegas, Danae Sánchez; Mokaram, Saeid; Aletras, Nikolaos. - : arXiv, 2021 BASE Show details 4 Modeling the Severity of Complaints in Social Media ... Jin, Mali; Aletras, Nikolaos. - : arXiv, 2021 BASE Show details 5 Translation Error Detection as Rationale Extraction ... Fomicheva, Marina; Specia, Lucia; Aletras, Nikolaos. - : arXiv, 2021 Abstract: Recent Quality Estimation (QE) models based on multilingual pre-trained representations have achieved very competitive results when predicting the overall quality of translated sentences. Predicting translation errors, i.e. detecting specifically which words are incorrect, is a more challenging task, especially with limited amounts of training data. We hypothesize that, not unlike humans, successful QE models rely on translation errors to predict overall sentence quality. By exploring a set of feature attribution methods that assign relevance scores to the inputs to explain model predictions, we study the behaviour of state-of-the-art sentence-level QE models and show that explanations (i.e. rationales) extracted from these models can indeed be used to detect translation errors. We therefore (i) introduce a novel semi-supervised method for word-level QE and (ii) propose to use the QE task as a new benchmark for evaluating the plausibility of feature attribution, i.e. how interpretable model explanations are ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2108.12197 https://dx.doi.org/10.48550/arxiv.2108.12197 BASE Hide details 6 Knowledge Distillation for Quality Estimation ... Gajbhiye, Amit; Fomicheva, Marina; Alva-Manchego, Fernando. - : arXiv, 2021 BASE Show details 7 Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ... Yamaguchi, Atsuki; Chrysostomou, George; Margatina, Katerina. - : arXiv, 2021 BASE Show details 8 Analyzing Online Political Advertisements ... 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; Aletras, Nikolaos; Mokaram, Saeid. - : Underline Science Inc., 2021 BASE Show details 9 Improving the Faithfulness of Attention-based Explanations with Task-specific Information for Text 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; Aletras, Nikolaos; Chrysostomou, George. - : Underline Science Inc., 2021 BASE Show details 10 Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aletras, Nikolaos; Chrysostomou, George. - : Underline Science Inc., 2021 BASE Show details 11 Modeling the Severity of Complaints in Social Media ... NAACL 2021 2021; Aletras, Nikolaos; Jin, Mali. - : Underline Science Inc., 2021 BASE Show details 12 Active Learning by Acquiring Contrastive Examples ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aletras, Nikolaos; Barrault, Loïc. - : Underline Science Inc., 2021 BASE Show details 13 In Factuality: Efficient Integration of Relevant Facts for Visual Question Answering ... 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; Aletras, Nikolaos; Barrault, Loïc. - : Underline Science Inc., 2021 BASE Show details 14 Frustratingly Simple Pretraining Alternatives to Masked Language Modeling ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aletras, Nikolaos; Chrysostomou, George. - : Underline Science Inc., 2021 BASE Show details 15 Knowledge Distillation for Quality Estimation ... 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; Aletras, Nikolaos; Alva-Manchego, Fernando. - : Underline Science Inc., 2021 BASE Show details 16 Machine Extraction of Tax Laws from Legislative Texts Han, Luyang; Guillot, Malka; Ash, Elliott In: Proceedings of the Natural Legal Language Processing Workshop 2021 (2021) BASE Show details 17 Point-of-Interest Type Prediction using Text and Images ... Villegas, Danae Sánchez; Aletras, Nikolaos. - : arXiv, 2021 BASE Show details 18 Point-of-Interest Type Prediction using Text and Images ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aletras, Nikolaos; Sanchez Villegas, Danae. - : Underline Science Inc., 2021 BASE Show details 19 An Empirical Study on Leveraging Position Embeddings for Target-oriented Opinion Words Extraction ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Aletras, Nikolaos; Mensah, Samuel. - : Underline Science Inc., 2021 BASE Show details 20 Knowledge distillation for quality estimation Gajbhiye, Amit; Fomicheva, Marina; Alva-Manchego, Fernando. - : Association for Computational Linguistics, 2021 BASE Show details Page: 1 2

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