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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 4 5...7 Hits 1 – 20 of 135 1 Pushing the right buttons: adversarial evaluation of quality estimation Specia, Lucia; Fomicheva, Marina; Ranasinghe, Tharindu... In: Proceedings of the Sixth Conference on Machine Translation ; 625 ; 638 (2022) BASE Show details 2 Translation Error Detection as Rationale Extraction ... Fomicheva, Marina; Specia, Lucia; Aletras, Nikolaos. - : arXiv, 2021 BASE Show details 3 Knowledge Distillation for Quality Estimation ... Gajbhiye, Amit; Fomicheva, Marina; Alva-Manchego, Fernando. - : arXiv, 2021 BASE Show details 4 BERTGEN: Multi-task Generation through BERT ... Mitzalis, Faidon; Caglayan, Ozan; Madhyastha, Pranava. - : arXiv, 2021 BASE Show details 5 Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications ... Sun, Shuo; El-Kishky, Ahmed; Chaudhary, Vishrav. - : arXiv, 2021 BASE Show details 6 A Generative Framework for Simultaneous Machine Translation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Blunsom, Phil; Miao, Yishu. - : Underline Science Inc., 2021 BASE Show details 7 Continual Quality Estimation with Online Bayesian Meta-Learning ... 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; Fomicheva, Marina; Obamuyide, Abiola. - : Underline Science Inc., 2021 BASE Show details 8 SentSim: Crosslingual Semantic Evaluation of Machine Translation ... NAACL 2021 2021; Song, Yurun; Specia, Lucia. - : Underline Science Inc., 2021 BASE Show details 9 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 10 BERTGen: Multi-task Generation through BERT ... 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; Caglayan, Ozan; Madhyastha, Pranava. - : Underline Science Inc., 2021 BASE Show details 11 What Makes a Scientific Paper be Accepted for Publication? ... Fytas, Panagiotis; Rizos, Georgios; Specia, Lucia. - : arXiv, 2021 BASE Show details 12 MultiSubs: A Large-scale Multimodal and Multilingual Dataset ... Wang, Josiah; Madhyastha, Pranava; Figueiredo, Josiel. - : arXiv, 2021 BASE Show details 13 Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning for NLP Vaidhya, Tejas; Sachan, Mrinmaya; von Kügelgen, Julius... In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021) BASE Show details 14 Classifying Dyads for Militarized Conflict Analysis Torroba Hennigen, Lucas; Stoehr, Niklas; West, Robert; Cotterell, Ryan; Ahbab, Samin In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021) Abstract: Understanding the origins of militarized conflict is a complex, yet important undertaking. Existing research seeks to build this understanding by considering bi-lateral relationships between entity pairs (dyadic causes) and multi-lateral relationships among multiple entities (systemic causes). The aim of this work is to compare these two causes in terms of how they correlate with conflict between two entities. We do this by devising a set of textual and graph-based features which represent each of the causes. The features are extracted from Wikipedia and modeled as a large graph. Nodes in this graph represent entities connected by labeled edges representing ally or enemy-relationships. This allows casting the problem as an edge classification task, which we term dyad classification. We propose and evaluate classifiers to determine if a particular pair of entities are allies or enemies. Our results suggest that our systemic features might be slightly better correlates of conflict. Further, we find that Wikipedia articles of allies are semantically more similar than enemies. URL: https://doi.org/10.3929/ethz-b-000518996 https://hdl.handle.net/20.500.11850/518996 BASE Hide details 15 Efficient Sampling of Dependency Structure Vieira, Tim; Zmigrod, Ran; Cotterell, Ryan In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021) BASE Show details 16 Searching for More Efficient Dynamic Programs Cotterell, Ryan; Eisner, Jason; Vieira, Tim In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021) BASE Show details 17 “Let Your Characters Tell Their Story”: A Dataset for Character-Centric Narrative Understanding Zhao, Chao; Sachan, Mrinmaya; Tafjord, Oyvind... In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021) BASE Show details 18 A Bayesian Framework for Information-Theoretic Probing Cotterell, Ryan; Pimentel, Tiago In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021) BASE Show details 19 Findings of the WMT 2021 Shared Task on Quality Estimation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Blain, Frédéric; Chaudhary, Vishrav. - : Underline Science Inc., 2021 BASE Show details 20 Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Tharindu; Blain, Frédéric. - : Underline Science Inc., 2021 BASE Show details Page: 1 2 3 4 5...7

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