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

, , , , , and . EMNLP (Findings), page 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).Crossword Puzzle Resolution in Italian using Distributional Models for Clue Similarity., and . IIR, volume 1653 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)Accurate Sentence Matching with Hybrid Siamese Networks., and . CIKM, page 2235-2238. ACM, (2017)Semantic Linking in Convolutional Neural Networks for Answer Sentence Selection., and . EMNLP, page 1070-1076. Association for Computational Linguistics, (2018)Question Answering and Knowledge Graphs., , , , , , , , , and 1 other author(s). Exploiting Linked Data and Knowledge Graphs in Large Organisations, Springer, (2017)Learning to Differentiate Better from Worse Translations., , , , , and . EMNLP, page 214-220. ACL, (2014)XTREME-UP: A User-Centric Scarce-Data Benchmark for Under-Represented Languages., , , , , , , , , and 17 other author(s). EMNLP (Findings), page 1856-1884. Association for Computational Linguistics, (2023)QCRI: Answer Selection for Community Question Answering - Experiments for Arabic and English., , , , , , , , , and 3 other author(s). SemEval@NAACL-HLT, page 203-209. The Association for Computer Linguistics, (2015)Learning to Rank Answer Candidates for Automatic Resolution of Crossword Puzzles., , and . CoNLL, page 39-48. ACL, (2014)Answering Conversational Questions on Structured Data without Logical Forms., , , , and . EMNLP/IJCNLP (1), page 5901-5909. Association for Computational Linguistics, (2019)