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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 22 1 BUSINESS MEETING ... 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; Bender, Emily M.; Callison-Burch, Chris. - : Underline Science Inc., 2021 BASE Show details 2 MassiveSumm: a very large-scale, very multilingual, news summarisation dataset ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Schluter, Natalie; Varab, Daniel. - : Underline Science Inc., 2021 BASE Show details 3 SemEval-2021 Task 12: Learning with Disagreements Uma, Alexandra; Fornaciari, Tommaso; Dumitrache, Anca. - : Association for Computational Linguistics, 2021 BASE Show details 4 IAPUCP at SemEval-2021 task 1: Stacking fine-tuned transformers is almost all you need for lexical complexity prediction Rivas Rojas, Kervy; Alva-Manchego, Fernando. - : Association for Computational Linguistics, 2021 BASE Show details 5 Speakers Enhance Contextually Confusable Words Meinhardt, Eric; Bakovic, Eric; Bergen, Leon. - : eScholarship, University of California, 2020 BASE Show details 6 Predicting Declension Class from Form and Meaning Cotterell, Ryan; Blix, Hagen; Pimentel, Tiago... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 7 The Paradigm Discovery Problem Wu, Shijie; Habash, Nizar; Elsner, Micha... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 8 A Tale of a Probe and a Parser Valvoda, Josef; Hall Maudslay, Rowan; Williams, Adina... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 9 A Corpus for Large-Scale Phonetic Typology Chodroff, Eleanor; Cotterell, Ryan; Wiesner, Matthew... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 10 Information-Theoretic Probing for Linguistic Structure Pimentel, Tiago; Zmigrod, Ran; Cotterell, Ryan... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 11 It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information Mielke, Sabrina J.; Okazaki, Naoaki; Anastasopoulos, Antonios... In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020) BASE Show details 12 ASSET: A dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations Alva Manchego, Fernando; Martin, Louis; Bordes, Antoine; Scarton, Carolina; Sagot, Benoît; Specia, Lucia. - : ACL, 2020 Abstract: In order to simplify a sentence, human editors perform multiple rewriting transformations: they split it into several shorter sentences, paraphrase words (i.e. replacing complex words or phrases by simpler synonyms), reorder components, and/or delete information deemed unnecessary. Despite these varied range of possible text alterations, current models for automatic sentence simplification are evaluated using datasets that are focused on a single transformation, such as lexical paraphrasing or splitting. This makes it impossible to understand the ability of simplification models in more realistic settings. To alleviate this limitation, this paper introduces ASSET, a new dataset for assessing sentence simplification in English. ASSET is a crowdsourced multi-reference corpus where each simplification was produced by executing several rewriting transformations. Through quantitative and qualitative experiments, we show that simplifications in ASSET are better at capturing characteristics of simplicity when compared to other standard evaluation datasets for the task. Furthermore, we motivate the need for developing better methods for automatic evaluation using ASSET, since we show that current popular metrics may not be suitable when multiple simplification transformations are performed. URL: https://orca.cardiff.ac.uk/147261/ https://doi.org/10.18653/v1/2020.acl-main.424 BASE Hide details 13 Non-linear instance-based cross-lingual mapping for non-isomorphic embedding spaces Glavaš, Goran; Vulić, Ivan. - : Association for Computational Linguistics, 2020 BASE Show details 14 Classification-based self-learning for weakly supervised bilingual lexicon induction Vulić, Ivan; Korhonen, Anna; Glavaš, Goran. - : Association for Computational Linguistics, 2020 BASE Show details 15 On the limitations of cross-lingual encoders as exposed by reference-free machine translation evaluation Zhao, Wei; Glavaš, Goran; Peyrard, Maxime. - : Association for Computational Linguistics, 2020 BASE Show details 16 Baselines and test data for cross-lingual inference ... Agić, Željko; Schluter, Natalie. - : arXiv, 2017 BASE Show details 17 Multilingual Projection for Parsing Truly Low-Resource Languageš Agic, Zeljko; Johannsen, Anders; Plank, Barbara... In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01426754 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2016 (2016) BASE Show details 18 Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources Schluter, Natalie. - : Dublin City University. National Centre for Language Technology (NCLT), 2011. : Dublin City University. School of Computing, 2011 In: Schluter, Natalie (2011) Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources. PhD thesis, Dublin City University. (2011) BASE Show details 19 Dependency parsing resources for French: Converting acquired lexical functional grammar F-Structure annotations and parsing F-Structures directly Schluter, Natalie; van Genabith, Josef In: Schluter, Natalie and van Genabith, Josef orcid:0000-0003-1322-7944 (2009) Dependency parsing resources for French: Converting acquired lexical functional grammar F-Structure annotations and parsing F-Structures directly. In: Nodalida 2009 Conference, 14 - 16 May 2009, Odense, Denmark. (2009) BASE Show details 20 Treebank-based acquisition of LFG parsing resources for French Schluter, Natalie; van Genabith, Josef In: Schluter, Natalie and van Genabith, Josef (2008) Treebank-based acquisition of LFG parsing resources for French. In: the Sixth International Language Resources and Evaluation Conference (LREC'08), May 28-30, 2008, Marrakech, Morocco. (2008) BASE Show details Page: 1 2

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