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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 BASE Show details 6 Knowledge Distillation for Quality Estimation ... Gajbhiye, Amit; Fomicheva, Marina; Alva-Manchego, Fernando; Blain, Frédéric; Obamuyide, Abiola; Aletras, Nikolaos; Specia, Lucia. - : arXiv, 2021 Abstract: Quality Estimation (QE) is the task of automatically predicting Machine Translation quality in the absence of reference translations, making it applicable in real-time settings, such as translating online social media conversations. Recent success in QE stems from the use of multilingual pre-trained representations, where very large models lead to impressive results. However, the inference time, disk and memory requirements of such models do not allow for wide usage in the real world. Models trained on distilled pre-trained representations remain prohibitively large for many usage scenarios. We instead propose to directly transfer knowledge from a strong QE teacher model to a much smaller model with a different, shallower architecture. We show that this approach, in combination with data augmentation, leads to light-weight QE models that perform competitively with distilled pre-trained representations with 8x fewer parameters. ... : ACL Findings 2021 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2107.00411 https://arxiv.org/abs/2107.00411 BASE Hide 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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