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Is writing style predictive of scientific fraud?, and . CoRR, (2017)Combining Natural and Artificial Examples to Improve Implicit Discourse Relation Identification., and . COLING, page 1694-1705. ACL, (2014)Investigation par méthodes d'apprentissage des spécificités langagières propres aux personnes avec schizophrénie (Investigating Learning Methods Applied to Language Specificity of Persons with Schizophrenia)., , , , , and . JEP-TALN-RECITAL (2), page 12-26. ATALA et AFCP, (2020)Which aspects of discourse relations are hard to learn? Primitive decomposition for discourse relation classification., , and . SIGdial, page 432-441. Association for Computational Linguistics, (2019)Multi-view and multi-task training of RST discourse parsers., , and . COLING, page 1903-1913. ACL, (2016)Zero-shot Learning for Multilingual Discourse Relation Classification., , , and . LREC/COLING, page 17858-17876. ELRA and ICCL, (2024)Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs., , , and . EMNLP/IJCNLP (1), page 4184-4194. Association for Computational Linguistics, (2019)Comparing Word Representations for Implicit Discourse Relation Classification., and . EMNLP, page 2201-2211. The Association for Computational Linguistics, (2015)Identifier les relations discursives implicites en combinant données naturelles et données artificielles., and . Trait. Autom. des Langues, 55 (1): 135-165 (2014)An Integrated Approach for Political Bias Prediction and Explanation Based on Discursive Structure., , and . ACL (Findings), page 11196-11211. Association for Computational Linguistics, (2023)