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Frame-oriented Summarization of Argumentative Discussions.

, , , , and . SIGDIAL, page 114-129. Association for Computational Linguistics, (2023)

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Wikipedia Text Reuse: Within and Without., , , , , , and . CoRR, (2018)Text Analysis Pipelines - Towards Ad-hoc Large-Scale Text Mining. Lecture Notes in Computer Science Springer, (2015)AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks., , , , , , , , , and 1 other author(s). CoRR, (2023)Modeling the Quality of Dialogical Explanations., , , , , and . CoRR, (2024)Dialogue-Based Requirement Compensation and Style-Adjusted Data-To-Text Generation, , , , and . page 65--84. (2023)Mining, Assessing, and Improving Arguments in NLP and the Social Sciences, , , and . Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, Association for Computational Linguistics (ACL), (May 2023)Funding Information: Gabriella Lapesa and Eva Maria Vecchi are funded by the Bundesministerium für Bildung und Forschung (BMBF), project E-DELIB (Powering up E-deliberation: towards AI-supported moderation). Serena Villata is supported by the French government, through the 3IA Côte d’Azur Investments in the Future project managed by the ANR with the reference number ANR-19-P3IA-0002.; 17th Conference of the European Chapter of the Associationfor Computational Linguistics, EACL 2023 ; Conference date: 02-05-2023 Through 04-05-2023.Identifying Feedback Types to Augment Feedback Comment Generation., and . INLG (Generation Challenges), page 31-36. Association for Computational Linguistics, (2023)Counter-Argument Generation by Attacking Weak Premises., , , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 1816-1827. Association for Computational Linguistics, (2021)Generating Informative Conclusions for Argumentative Texts., , , , and . ACL/IJCNLP (Findings), volume ACL/IJCNLP 2021 of Findings of ACL, page 3482-3493. Association for Computational Linguistics, (2021)Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models., and . IJCAI, page 552-559. ijcai.org, (2021)