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mmT5: Modular Multilingual Pre-Training Solves Source Language Hallucinations.

, , , , , и . EMNLP (Findings), стр. 1978-2008. Association for Computational Linguistics, (2023)

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Structural Kernels and Neural Network Models for Question Answering Systems.. University of Trento, Italy, (2018)base-search.net (ftutrentophd:oai:eprints-phd.biblio.unitn.it:2886).Accurate Sentence Matching with Hybrid Siamese Networks., и . CIKM, стр. 2235-2238. ACM, (2017)Crossword Puzzle Resolution in Italian using Distributional Models for Clue Similarity., и . IIR, том 1653 из CEUR Workshop Proceedings, CEUR-WS.org, (2016)Semantic Linking in Convolutional Neural Networks for Answer Sentence Selection., и . EMNLP, стр. 1070-1076. Association for Computational Linguistics, (2018)QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English., , , , , , , , , и 3 other автор(ы). SemEval@NAACL-HLT, стр. 203-209. The Association for Computer Linguistics, (2015)Learning to Rank Answer Candidates for Automatic Resolution of Crossword Puzzles., , и . CoNLL, стр. 39-48. ACL, (2014)Question Answering and Knowledge Graphs., , , , , , , , , и 1 other автор(ы). Exploiting Linked Data and Knowledge Graphs in Large Organisations, Springer, (2017)Learning to Differentiate Better from Worse Translations., , , , , и . EMNLP, стр. 214-220. ACL, (2014)XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages., , , , , , , , , и 17 other автор(ы). EMNLP (Findings), стр. 1856-1884. Association for Computational Linguistics, (2023)Learning to Rank Aggregated Answers for Crossword Puzzles., , и . ECIR, том 9022 из Lecture Notes in Computer Science, стр. 556-561. (2015)