--- _id: '61190' author: - first_name: Meghdut full_name: Sengupta, Meghdut id: '99459' last_name: Sengupta - first_name: 'Maximilian ' full_name: 'Muschalik, Maximilian ' last_name: Muschalik - first_name: Fabian full_name: Fumagalli, Fabian id: '93420' last_name: Fumagalli - first_name: Barbara full_name: Hammer, Barbara last_name: Hammer - first_name: 'Eyke ' full_name: 'Hüllermeier, Eyke ' last_name: Hüllermeier - first_name: Debanjan full_name: Ghosh, Debanjan last_name: Ghosh - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Sengupta M, Muschalik M, Fumagalli F, et al. Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions. In: Accepted in Findings . EMNLP ; 2025.' apa: Sengupta, M., Muschalik, M., Fumagalli, F., Hammer, B., Hüllermeier, E., Ghosh, D., & Wachsmuth, H. (2025). Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions. Accepted in Findings . Empirical Methods in Natural Language Processing (EMNLP 2025). bibtex: '@inproceedings{Sengupta_Muschalik_Fumagalli_Hammer_Hüllermeier_Ghosh_Wachsmuth_2025, title={Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions}, booktitle={Accepted in Findings }, publisher={EMNLP }, author={Sengupta, Meghdut and Muschalik, Maximilian and Fumagalli, Fabian and Hammer, Barbara and Hüllermeier, Eyke and Ghosh, Debanjan and Wachsmuth, Henning}, year={2025} }' chicago: Sengupta, Meghdut, Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke Hüllermeier, Debanjan Ghosh, and Henning Wachsmuth. “Investigating the Impact of Conceptual Metaphors on LLM-Based NLI through Shapley Interactions.” In Accepted in Findings . EMNLP , 2025. ieee: M. Sengupta et al., “Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions,” presented at the Empirical Methods in Natural Language Processing (EMNLP 2025), 2025. mla: Sengupta, Meghdut, et al. “Investigating the Impact of Conceptual Metaphors on LLM-Based NLI through Shapley Interactions.” Accepted in Findings , EMNLP , 2025. short: 'M. Sengupta, M. Muschalik, F. Fumagalli, B. Hammer, E. Hüllermeier, D. Ghosh, H. Wachsmuth, in: Accepted in Findings , EMNLP , 2025.' conference: end_date: 2025-11-09 name: Empirical Methods in Natural Language Processing (EMNLP 2025) start_date: 2025-11-04 date_created: 2025-09-11T09:27:10Z date_updated: 2025-09-11T09:28:23Z ddc: - '000' extern: '1' file: - access_level: closed content_type: application/pdf creator: meghdut date_created: 2025-09-11T09:26:18Z date_updated: 2025-09-11T09:26:18Z file_id: '61194' file_name: sengupta25-emnlp.pdf file_size: 2189153 relation: main_file success: 1 file_date_updated: 2025-09-11T09:26:18Z has_accepted_license: '1' language: - iso: eng project: - _id: '127' name: 'TRR 318; TP C04: Metaphern als Werkzeug des Erklärens' publication: 'Accepted in Findings ' publisher: 'EMNLP ' status: public title: Investigating the Impact of Conceptual Metaphors on LLM-based NLI through Shapley Interactions type: conference user_id: '99459' year: '2025' ... --- _id: '55338' abstract: - lang: eng text: Metaphorical language is a pivotal element inthe realm of political framing. Existing workfrom linguistics and the social sciences providescompelling evidence regarding the distinctivenessof conceptual framing for politicalideology perspectives. However, the nature andutilization of metaphors and the effect on audiencesof different political ideologies withinpolitical discourses are hardly explored. Toenable research in this direction, in this workwe create a dataset, originally based on newseditorials and labeled with their persuasive effectson liberals and conservatives and extend itwith annotations pertaining to metaphorical usageof language. To that end, first, we identifyall single metaphors and composite metaphors.Secondly, we provide annotations of the sourceand target domains for each metaphor. As aresult, our corpus consists of 300 news editorialsannotated with spans of texts containingmetaphors and the corresponding domains ofwhich these metaphors draw from. Our analysisshows that liberal readers are affected bymetaphors, whereas conservatives are resistantto them. Both ideologies are affected differentlybased on the metaphor source and targetcategory. For example, liberals are affected bymetaphors in the Darkness {&} Light (e.g., death)source domains, where as the source domain ofNature affects conservatives more significantly. author: - first_name: Meghdut full_name: Sengupta, Meghdut id: '99459' last_name: Sengupta - first_name: Roxanne full_name: El Baff, Roxanne last_name: El Baff - first_name: Milad full_name: Alshomary, Milad id: '73059' last_name: Alshomary - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Sengupta M, El Baff R, Alshomary M, Wachsmuth H. Analyzing the Use of Metaphors in News Editorials for Political Framing. In: Duh K, Gomez H, Bethard S, eds. Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). Association for Computational Linguistics; 2024:3621–3631.' apa: 'Sengupta, M., El Baff, R., Alshomary, M., & Wachsmuth, H. (2024). Analyzing the Use of Metaphors in News Editorials for Political Framing. In K. Duh, H. Gomez, & S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 3621–3631). Association for Computational Linguistics.' bibtex: '@inproceedings{Sengupta_El Baff_Alshomary_Wachsmuth_2024, place={Mexico City, Mexico}, title={Analyzing the Use of Metaphors in News Editorials for Political Framing}, booktitle={Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)}, publisher={Association for Computational Linguistics}, author={Sengupta, Meghdut and El Baff, Roxanne and Alshomary, Milad and Wachsmuth, Henning}, editor={Duh, Kevin and Gomez, Helena and Bethard, Steven}, year={2024}, pages={3621–3631} }' chicago: 'Sengupta, Meghdut, Roxanne El Baff, Milad Alshomary, and Henning Wachsmuth. “Analyzing the Use of Metaphors in News Editorials for Political Framing.” In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), edited by Kevin Duh, Helena Gomez, and Steven Bethard, 3621–3631. Mexico City, Mexico: Association for Computational Linguistics, 2024.' ieee: 'M. Sengupta, R. El Baff, M. Alshomary, and H. Wachsmuth, “Analyzing the Use of Metaphors in News Editorials for Political Framing,” in Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024, pp. 3621–3631.' mla: 'Sengupta, Meghdut, et al. “Analyzing the Use of Metaphors in News Editorials for Political Framing.” Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), edited by Kevin Duh et al., Association for Computational Linguistics, 2024, pp. 3621–3631.' short: 'M. Sengupta, R. El Baff, M. Alshomary, H. Wachsmuth, in: K. Duh, H. Gomez, S. Bethard (Eds.), Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), Association for Computational Linguistics, Mexico City, Mexico, 2024, pp. 3621–3631.' date_created: 2024-07-22T13:08:12Z date_updated: 2024-07-26T13:02:57Z department: - _id: '600' - _id: '660' editor: - first_name: Kevin full_name: Duh, Kevin last_name: Duh - first_name: Helena full_name: Gomez, Helena last_name: Gomez - first_name: Steven full_name: Bethard, Steven last_name: Bethard language: - iso: eng page: 3621–3631 place: Mexico City, Mexico project: - _id: '127' name: 'TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens' publication: 'Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)' publisher: Association for Computational Linguistics status: public title: Analyzing the Use of Metaphors in News Editorials for Political Framing type: conference user_id: '3900' year: '2024' ... --- _id: '55404' abstract: - lang: eng text: Explanations are pervasive in our lives. Mostly, they occur in dialogical form where an explainer discusses a concept or phenomenon of interest with an explainee. Leaving the explainee with a clear understanding is not straightforward due to the knowledge gap between the two participants. Previous research looked at the interaction of explanation moves, dialogue acts, and topics in successful dialogues with expert explainers. However, daily-life explanations often fail, raising the question of what makes a dialogue successful. In this work, we study explanation dialogues in terms of the interactions between the explainer and explainee and how they correlate with the quality of explanations in terms of a successful understanding on the explainee{’}s side. In particular, we first construct a corpus of 399 dialogues from the Reddit forum {Explain Like I am Five} and annotate it for interaction flows and explanation quality. We then analyze the interaction flows, comparing them to those appearing in expert dialogues. Finally, we encode the interaction flows using two language models that can handle long inputs, and we provide empirical evidence for the effectiveness boost gained through the encoding in predicting the success of explanation dialogues. author: - first_name: Milad full_name: Alshomary, Milad id: '73059' last_name: Alshomary - first_name: Felix full_name: Lange, Felix id: '67893' last_name: Lange - first_name: Meisam full_name: Booshehri, Meisam last_name: Booshehri - first_name: Meghdut full_name: Sengupta, Meghdut id: '99459' last_name: Sengupta - first_name: Philipp full_name: Cimiano, Philipp last_name: Cimiano - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Alshomary M, Lange F, Booshehri M, Sengupta M, Cimiano P, Wachsmuth H. Modeling the Quality of Dialogical Explanations. In: Calzolari N, Kan M-Y, Hoste V, Lenci A, Sakti S, Xue N, eds. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024). ELRA and ICCL; 2024:11523–11536.' apa: Alshomary, M., Lange, F., Booshehri, M., Sengupta, M., Cimiano, P., & Wachsmuth, H. (2024). Modeling the Quality of Dialogical Explanations. In N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, & N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) (pp. 11523–11536). ELRA and ICCL. bibtex: '@inproceedings{Alshomary_Lange_Booshehri_Sengupta_Cimiano_Wachsmuth_2024, place={Torino, Italia}, title={Modeling the Quality of Dialogical Explanations}, booktitle={Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)}, publisher={ELRA and ICCL}, author={Alshomary, Milad and Lange, Felix and Booshehri, Meisam and Sengupta, Meghdut and Cimiano, Philipp and Wachsmuth, Henning}, editor={Calzolari, Nicoletta and Kan, Min-Yen and Hoste, Veronique and Lenci, Alessandro and Sakti, Sakriani and Xue, Nianwen}, year={2024}, pages={11523–11536} }' chicago: 'Alshomary, Milad, Felix Lange, Meisam Booshehri, Meghdut Sengupta, Philipp Cimiano, and Henning Wachsmuth. “Modeling the Quality of Dialogical Explanations.” In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), edited by Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, and Nianwen Xue, 11523–11536. Torino, Italia: ELRA and ICCL, 2024.' ieee: M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, and H. Wachsmuth, “Modeling the Quality of Dialogical Explanations,” in Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), 2024, pp. 11523–11536. mla: Alshomary, Milad, et al. “Modeling the Quality of Dialogical Explanations.” Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), edited by Nicoletta Calzolari et al., ELRA and ICCL, 2024, pp. 11523–11536. short: 'M. Alshomary, F. Lange, M. Booshehri, M. Sengupta, P. Cimiano, H. Wachsmuth, in: N. Calzolari, M.-Y. Kan, V. Hoste, A. Lenci, S. Sakti, N. Xue (Eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ELRA and ICCL, Torino, Italia, 2024, pp. 11523–11536.' date_created: 2024-07-26T13:04:25Z date_updated: 2024-12-17T11:30:25Z department: - _id: '600' - _id: '660' editor: - first_name: Nicoletta full_name: Calzolari, Nicoletta last_name: Calzolari - first_name: Min-Yen full_name: Kan, Min-Yen last_name: Kan - first_name: Veronique full_name: Hoste, Veronique last_name: Hoste - first_name: Alessandro full_name: Lenci, Alessandro last_name: Lenci - first_name: Sakriani full_name: Sakti, Sakriani last_name: Sakti - first_name: Nianwen full_name: Xue, Nianwen last_name: Xue language: - iso: eng page: 11523–11536 place: Torino, Italia project: - _id: '118' name: 'TRR 318 - INF: TRR 318 - Project Area INF' publication: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) publisher: ELRA and ICCL quality_controlled: '1' status: public title: Modeling the Quality of Dialogical Explanations type: conference user_id: '67893' year: '2024' ... --- _id: '55406' abstract: - lang: eng text: Metaphorical language, such as {“}spending time together{”}, projects meaning from a source domain (here, $money$) to a target domain ($time$). Thereby, it highlights certain aspects of the target domain, such as the $effort$ behind the time investment. Highlighting aspects with metaphors (while hiding others) bridges the two domains and is the core of metaphorical meaning construction. For metaphor interpretation, linguistic theories stress that identifying the highlighted aspects is important for a better understanding of metaphors. However, metaphor research in NLP has not yet dealt with the phenomenon of highlighting. In this paper, we introduce the task of identifying the main aspect highlighted in a metaphorical sentence. Given the inherent interaction of source domains and highlighted aspects, we propose two multitask approaches - a joint learning approach and a continual learning approach - based on a finetuned contrastive learning model to jointly predict highlighted aspects and source domains. We further investigate whether (predicted) information about a source domain leads to better performance in predicting the highlighted aspects, and vice versa. Our experiments on an existing corpus suggest that, with the corresponding information, the performance to predict the other improves in terms of model accuracy in predicting highlighted aspects and source domains notably compared to the single-task baselines. author: - first_name: Meghdut full_name: Sengupta, Meghdut id: '99459' last_name: Sengupta - first_name: Milad full_name: Alshomary, Milad id: '73059' last_name: Alshomary - first_name: Ingrid full_name: Scharlau, Ingrid id: '451' last_name: Scharlau orcid: 0000-0003-2364-9489 - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Sengupta M, Alshomary M, Scharlau I, Wachsmuth H. Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. In: Bouamor H, Pino J, Bali K, eds. Findings of the Association for Computational Linguistics: EMNLP 2023. Association for Computational Linguistics; 2023:4636–4659. doi:10.18653/v1/2023.findings-emnlp.308' apa: 'Sengupta, M., Alshomary, M., Scharlau, I., & Wachsmuth, H. (2023). Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms. In H. Bouamor, J. Pino, & K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023 (pp. 4636–4659). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.findings-emnlp.308' bibtex: '@inproceedings{Sengupta_Alshomary_Scharlau_Wachsmuth_2023, place={Singapore}, title={Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms}, DOI={10.18653/v1/2023.findings-emnlp.308}, booktitle={Findings of the Association for Computational Linguistics: EMNLP 2023}, publisher={Association for Computational Linguistics}, author={Sengupta, Meghdut and Alshomary, Milad and Scharlau, Ingrid and Wachsmuth, Henning}, editor={Bouamor, Houda and Pino, Juan and Bali, Kalika}, year={2023}, pages={4636–4659} }' chicago: 'Sengupta, Meghdut, Milad Alshomary, Ingrid Scharlau, and Henning Wachsmuth. “Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms.” In Findings of the Association for Computational Linguistics: EMNLP 2023, edited by Houda Bouamor, Juan Pino, and Kalika Bali, 4636–4659. Singapore: Association for Computational Linguistics, 2023. https://doi.org/10.18653/v1/2023.findings-emnlp.308.' ieee: 'M. Sengupta, M. Alshomary, I. Scharlau, and H. Wachsmuth, “Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms,” in Findings of the Association for Computational Linguistics: EMNLP 2023, 2023, pp. 4636–4659, doi: 10.18653/v1/2023.findings-emnlp.308.' mla: 'Sengupta, Meghdut, et al. “Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms.” Findings of the Association for Computational Linguistics: EMNLP 2023, edited by Houda Bouamor et al., Association for Computational Linguistics, 2023, pp. 4636–4659, doi:10.18653/v1/2023.findings-emnlp.308.' short: 'M. Sengupta, M. Alshomary, I. Scharlau, H. Wachsmuth, in: H. Bouamor, J. Pino, K. Bali (Eds.), Findings of the Association for Computational Linguistics: EMNLP 2023, Association for Computational Linguistics, Singapore, 2023, pp. 4636–4659.' date_created: 2024-07-26T13:09:20Z date_updated: 2024-07-26T13:19:53Z department: - _id: '600' - _id: '660' doi: 10.18653/v1/2023.findings-emnlp.308 editor: - first_name: Houda full_name: Bouamor, Houda last_name: Bouamor - first_name: Juan full_name: Pino, Juan last_name: Pino - first_name: Kalika full_name: Bali, Kalika last_name: Bali language: - iso: eng page: 4636–4659 place: Singapore project: - _id: '127' name: 'TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens' publication: 'Findings of the Association for Computational Linguistics: EMNLP 2023' publisher: Association for Computational Linguistics status: public title: Modeling Highlighting of Metaphors in Multitask Contrastive Learning Paradigms type: conference user_id: '3900' year: '2023' ... --- _id: '34067' author: - first_name: Meghdut full_name: Sengupta, Meghdut id: '99459' last_name: Sengupta - first_name: Milad full_name: Alshomary, Milad id: '73059' last_name: Alshomary - first_name: Henning full_name: Wachsmuth, Henning id: '3900' last_name: Wachsmuth citation: ama: 'Sengupta M, Alshomary M, Wachsmuth H. Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. In: Proceedings of the 2022 Workshop on Figurative Language Processing. ; 2022.' apa: 'Sengupta, M., Alshomary, M., & Wachsmuth, H. (2022). Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning. Proceedings of the 2022 Workshop on Figurative Language Processing.' bibtex: '@inproceedings{Sengupta_Alshomary_Wachsmuth_2022, title={Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning}, booktitle={Proceedings of the 2022 Workshop on Figurative Language Processing}, author={Sengupta, Meghdut and Alshomary, Milad and Wachsmuth, Henning}, year={2022} }' chicago: 'Sengupta, Meghdut, Milad Alshomary, and Henning Wachsmuth. “Back to the Roots: Predicting the Source Domain of Metaphors Using Contrastive Learning.” In Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.' ieee: 'M. Sengupta, M. Alshomary, and H. Wachsmuth, “Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning,” 2022.' mla: 'Sengupta, Meghdut, et al. “Back to the Roots: Predicting the Source Domain of Metaphors Using Contrastive Learning.” Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.' short: 'M. Sengupta, M. Alshomary, H. Wachsmuth, in: Proceedings of the 2022 Workshop on Figurative Language Processing, 2022.' date_created: 2022-11-14T08:49:07Z date_updated: 2024-07-26T13:08:46Z department: - _id: '600' - _id: '660' language: - iso: eng project: - _id: '127' name: 'TRR 318 - C4: TRR 318 - Subproject C4 - Metaphern als Werkzeug des Erklärens' publication: Proceedings of the 2022 Workshop on Figurative Language Processing status: public title: 'Back to the Roots: Predicting the Source Domain of Metaphors using Contrastive Learning' type: conference user_id: '3900' year: '2022' ...