[{"title":"TAME: Element-wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction","oa":"1","type":"working_paper","doi":"10.26434/chemrxiv.15008270/v2","year":"2026","author":[{"first_name":"Robert P.","last_name":"Schiller","full_name":"Schiller, Robert P."},{"id":"264138","full_name":"Weisser, Christoph","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0003-0616-1027/work/226396719","last_name":"Weisser","orcid":"0000-0003-0616-1027","first_name":"Christoph"},{"full_name":"Müller, Klaus-Robert","last_name":"Müller","first_name":"Klaus-Robert"},{"full_name":"Ochsenfeld, Christian","first_name":"Christian","last_name":"Ochsenfeld"},{"full_name":"Semnani, Parastoo","first_name":"Parastoo","last_name":"Semnani"}],"_id":"7152","citation":{"apa":"Schiller, R. P., Weisser, C., Müller, K.-R., Ochsenfeld, C., & Semnani, P. (2026). TAME: Element-wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction. https://doi.org/10.26434/chemrxiv.15008270/v2","chicago":"Schiller, Robert P., Christoph Weisser, Klaus-Robert Müller, Christian Ochsenfeld, and Parastoo Semnani. TAME: Element-Wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction, 2026. https://doi.org/10.26434/chemrxiv.15008270/v2.","ama":"Schiller RP, Weisser C, Müller K-R, Ochsenfeld C, Semnani P. TAME: Element-Wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction.; 2026. doi:10.26434/chemrxiv.15008270/v2","bibtex":"@book{Schiller_Weisser_Müller_Ochsenfeld_Semnani_2026, title={TAME: Element-wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction}, DOI={10.26434/chemrxiv.15008270/v2}, author={Schiller, Robert P. and Weisser, Christoph and Müller, Klaus-Robert and Ochsenfeld, Christian and Semnani, Parastoo}, year={2026} }","mla":"Schiller, Robert P., et al. TAME: Element-Wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction. 2026, doi:10.26434/chemrxiv.15008270/v2.","ieee":"R. P. Schiller, C. Weisser, K.-R. Müller, C. Ochsenfeld, and P. Semnani, TAME: Element-wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction. 2026.","alphadin":"Schiller, Robert P. ; Weisser, Christoph ; Müller, Klaus-Robert ; Ochsenfeld, Christian ; Semnani, Parastoo: TAME: Element-wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction, 2026","short":"R.P. Schiller, C. Weisser, K.-R. Müller, C. Ochsenfeld, P. Semnani, TAME: Element-Wise Mixture-of-Experts Fusion for Reliable and Interpretable Molecular Property Prediction, 2026."},"main_file_link":[{"open_access":"1"}],"language":[{"iso":"eng"}],"abstract":[{"lang":"eng","text":"Property prediction for molecules and materials is bottlenecked by label scarcity, and in this regime the operative failure mode is not a low mean but an unpredictable tail: individual training runs collapse. The three dominant molecular representations fail in complementary ways?physicochemical descriptors are exact but fixed, graph neural networks learn topology but degenerate under sparse supervision, and language models supply semantic context but cannot compute exact quantities? yet combining them is itself the learning problem, because modality-level scalar gating commits the whole model to one trust weight per source. We introduce TAME, a tri-modal encoder whose element-wise Mixture-of-Experts router assigns an independent modality mixture to every hidden coordinate, stabilized by a balance?entropy regularizer, a closed-form gate initialization (? = log τ ) that is intended to remove router burn-in, and two-stage self-supervised graph pretraining. On scaffold-split BACE (≈ 1.5k molecules, 100 seeds) we evaluate two fusion topologies, each against its own graph-only control. In both, adding the text and descriptor experts contracts the seed-to-seed distribution of the threshold-free metrics?ROC-AUC σ falls five-fold in the flat topology and 1.6-fold in the hierarchical one, whose control was already the tighter of the two?and the collapse tail reaching ROC-AUC ≈ 0.45 that the weaker single-modality configurations carry is absent from the fused models while accuracy is retained. Each comparison is matched on everything but the fusion stage, isolating its effect. The router allocates a distinct mixture to each coordinate, which no scalar gate can represent, and the entropy weight moves that allocation continuously between graded mixing and a near-binary regime in which each coordinate is claimed outright by one modality. Fused-representation alignment tracks encoder quality without supervision, shifting from text to topology once pretraining lifts the graph embedding out of rank-1 collapse. The same three experts map onto crystal graphs, composition?structure descriptors and literature-mined text. These three modalities recur unchanged across molecular and inorganic chemistry, so TAME is a single interpretable recipe for turning volatile low-data predictors into reliable, self-explaining ones, wherever data are scarce and every failed prediction costs a real experiment."}],"user_id":"220548","publication_status":"published","date_created":"2026-09-10T07:31:07Z","date_updated":"2026-09-11T08:11:21Z","status":"public"},{"user_id":"220548","language":[{"iso":"eng"}],"date_updated":"2026-08-21T12:29:02Z","publication":"Preprint","status":"public","publication_status":"published","date_created":"2026-06-01T14:03:54Z","author":[{"full_name":"Kumar, Manish","last_name":"Kumar","first_name":"Manish"},{"full_name":"Thielmann, Anton Frederik","first_name":"Anton Frederik","last_name":"Thielmann"},{"id":"264138","orcid":"0000-0003-0616-1027","last_name":"Weisser","first_name":"Christoph","full_name":"Weisser, Christoph","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0003-0616-1027/work/216498143"},{"full_name":"Säfken, Benjamin","first_name":"Benjamin","last_name":"Säfken"}],"main_file_link":[{"url":"https://arxiv.org/abs/2604.05635v1"}],"_id":"6958","citation":{"apa":"Kumar, M., Thielmann, A. F., Weisser, C., & Säfken, B. (2026). From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning. Preprint.","chicago":"Kumar, Manish, Anton Frederik Thielmann, Christoph Weisser, and Benjamin Säfken. “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning.” Preprint, 2026.","short":"M. Kumar, A.F. Thielmann, C. Weisser, B. Säfken, Preprint (2026).","alphadin":"Kumar, Manish ; Thielmann, Anton Frederik ; Weisser, Christoph ; Säfken, Benjamin: From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning. In: Preprint, Arxiv (2026)","mla":"Kumar, Manish, et al. “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning.” Preprint, Arxiv, 2026.","ieee":"M. Kumar, A. F. Thielmann, C. Weisser, and B. Säfken, “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning,” Preprint, 2026.","bibtex":"@article{Kumar_Thielmann_Weisser_Säfken_2026, title={From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning}, journal={Preprint}, publisher={Arxiv}, author={Kumar, Manish and Thielmann, Anton Frederik and Weisser, Christoph and Säfken, Benjamin}, year={2026} }","ama":"Kumar M, Thielmann AF, Weisser C, Säfken B. From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning. Preprint. 2026."},"type":"journal_article","publisher":"Arxiv","year":"2026","title":"From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning","related_material":{"link":[{"relation":"later_version","url":"https://www.hsbi.de/publikationsserver/record/7112"}]}},{"related_material":{"link":[{"relation":"earlier_version","url":"https://www.hsbi.de/publikationsserver/record/6958"}]},"title":"From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning","quality_controlled":"1","year":"2026","publisher":"arxiv","type":"journal_article","doi":"10.48550/arXiv.2604.05635","_id":"7112","citation":{"chicago":"Kumar, Manish, Anton Frederik Thielmann, Christoph Weisser, and Benjamin Säfken. “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning.” Transactions on Machine Learning Research, 2026. https://doi.org/10.48550/arXiv.2604.05635.","apa":"Kumar, M., Thielmann, A. F., Weisser, C., & Säfken, B. (2026). From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning. Transactions on Machine Learning Research. https://doi.org/10.48550/arXiv.2604.05635","bibtex":"@article{Kumar_Thielmann_Weisser_Säfken_2026, title={From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning}, DOI={10.48550/arXiv.2604.05635}, journal={Transactions on Machine Learning Research}, publisher={arxiv}, author={Kumar, Manish and Thielmann, Anton Frederik and Weisser, Christoph and Säfken, Benjamin}, year={2026} }","ama":"Kumar M, Thielmann AF, Weisser C, Säfken B. From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning. Transactions on Machine Learning Research. 2026. doi:10.48550/arXiv.2604.05635","alphadin":"Kumar, Manish ; Thielmann, Anton Frederik ; Weisser, Christoph ; Säfken, Benjamin: From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning. In: Transactions on Machine Learning Research, arxiv (2026)","ieee":"M. Kumar, A. F. Thielmann, C. Weisser, and B. Säfken, “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning,” Transactions on Machine Learning Research, 2026.","mla":"Kumar, Manish, et al. “From Uniform to Learned Knots: A Study of Spline-Based Numerical Encodings for Tabular Deep Learning.” Transactions on Machine Learning Research, arxiv, 2026, doi:10.48550/arXiv.2604.05635.","short":"M. Kumar, A.F. Thielmann, C. Weisser, B. Säfken, Transactions on Machine Learning Research (2026)."},"author":[{"full_name":"Kumar, Manish","last_name":"Kumar","first_name":"Manish"},{"full_name":"Thielmann, Anton Frederik","last_name":"Thielmann","first_name":"Anton Frederik"},{"last_name":"Weisser","orcid":"0000-0003-0616-1027","first_name":"Christoph","full_name":"Weisser, Christoph","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0003-0616-1027/work/224483678","id":"264138"},{"first_name":"Benjamin","last_name":"Säfken","full_name":"Säfken, Benjamin"}],"date_created":"2026-08-20T17:25:46Z","status":"public","date_updated":"2026-08-21T12:28:04Z","publication":"Transactions on Machine Learning Research","language":[{"iso":"eng"}],"user_id":"220548"},{"user_id":"220548","doi":"10.48550/arXiv.2608.11753 ","type":"journal_article","language":[{"iso":"eng"}],"date_updated":"2026-08-21T12:16:32Z","publication":"arXiv:2608.11753","status":"public","year":"2026","date_created":"2026-08-20T17:19:49Z","title":"LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification","author":[{"first_name":"Michael","last_name":"Schlee","full_name":"Schlee, Michael"},{"first_name":"Fabian","last_name":"Lukassen","full_name":"Lukassen, Fabian"},{"last_name":"Weisser","orcid":"0000-0003-0616-1027","first_name":"Christoph","full_name":"Weisser, Christoph","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0003-0616-1027/work/224400435","id":"264138"}],"citation":{"short":"M. Schlee, F. Lukassen, C. Weisser, ArXiv:2608.11753 (2026).","mla":"Schlee, Michael, et al. “LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification.” ArXiv:2608.11753, 2026, doi:10.48550/arXiv.2608.11753 .","ieee":"M. Schlee, F. Lukassen, and C. Weisser, “LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification,” arXiv:2608.11753, 2026.","alphadin":"Schlee, Michael ; Lukassen, Fabian ; Weisser, Christoph: LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification. In: arXiv:2608.11753 (2026)","ama":"Schlee M, Lukassen F, Weisser C. LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification. arXiv:260811753. 2026. doi:10.48550/arXiv.2608.11753 ","bibtex":"@article{Schlee_Lukassen_Weisser_2026, title={LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification}, DOI={10.48550/arXiv.2608.11753 }, journal={arXiv:2608.11753}, author={Schlee, Michael and Lukassen, Fabian and Weisser, Christoph}, year={2026} }","chicago":"Schlee, Michael, Fabian Lukassen, and Christoph Weisser. “LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification.” ArXiv:2608.11753, 2026. https://doi.org/10.48550/arXiv.2608.11753 .","apa":"Schlee, M., Lukassen, F., & Weisser, C. (2026). LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification. ArXiv:2608.11753. https://doi.org/10.48550/arXiv.2608.11753 "},"_id":"7110"},{"year":"2026","doi":"10.48550/arXiv.2607.10380","type":"journal_article","publisher":"arxiv","title":"CAFE: A Compound-AI Factorial Evaluation Framework","date_updated":"2026-07-17T07:51:15Z","publication":"Preprint","status":"public","date_created":"2026-07-16T11:47:16Z","user_id":"220548","language":[{"iso":"eng"}],"citation":{"ama":"Lukassen F, Weisser C, Kneib T, Silbersdorff A. CAFE: A Compound-AI Factorial Evaluation Framework. Preprint. 2026. doi:10.48550/arXiv.2607.10380","bibtex":"@article{Lukassen_Weisser_Kneib_Silbersdorff_2026, title={CAFE: A Compound-AI Factorial Evaluation Framework}, DOI={10.48550/arXiv.2607.10380}, journal={Preprint}, publisher={arxiv}, author={Lukassen, Fabian and Weisser, Christoph and Kneib, Thomas and Silbersdorff, Alexander}, year={2026} }","ieee":"F. Lukassen, C. Weisser, T. Kneib, and A. Silbersdorff, “CAFE: A Compound-AI Factorial Evaluation Framework,” Preprint, 2026.","mla":"Lukassen, Fabian, et al. “CAFE: A Compound-AI Factorial Evaluation Framework.” Preprint, arxiv, 2026, doi:10.48550/arXiv.2607.10380.","alphadin":"Lukassen, Fabian ; Weisser, Christoph ; Kneib, Thomas ; Silbersdorff, Alexander: CAFE: A Compound-AI Factorial Evaluation Framework. In: Preprint, arxiv (2026)","short":"F. Lukassen, C. Weisser, T. Kneib, A. Silbersdorff, Preprint (2026).","apa":"Lukassen, F., Weisser, C., Kneib, T., & Silbersdorff, A. (2026). CAFE: A Compound-AI Factorial Evaluation Framework. Preprint. https://doi.org/10.48550/arXiv.2607.10380","chicago":"Lukassen, Fabian, Christoph Weisser, Thomas Kneib, and Alexander Silbersdorff. “CAFE: A Compound-AI Factorial Evaluation Framework.” Preprint, 2026. https://doi.org/10.48550/arXiv.2607.10380."},"_id":"7066","author":[{"full_name":"Lukassen, Fabian","first_name":"Fabian","last_name":"Lukassen"},{"id":"264138","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0003-0616-1027/work/220971488","full_name":"Weisser, Christoph","first_name":"Christoph","last_name":"Weisser","orcid":"0000-0003-0616-1027"},{"last_name":"Kneib","first_name":"Thomas","full_name":"Kneib, Thomas"},{"full_name":"Silbersdorff, Alexander","last_name":"Silbersdorff","first_name":"Alexander"}]},{"user_id":"220548","publication_identifier":{"eissn":["1863-8163"],"issn":["1863-8155"]},"abstract":[{"lang":"ger","text":"Das Positionspapier formuliert neun Thesen zur Weiterentwicklung der Statistikausbildung im Kontext von Data Science und Künstlicher Intelligenz. Im Zentrum stehen Data & Statistical Literacy, Datenqualität und -ethik, die Verbindung von Statistik und Machine Learning sowie die Stärkung einer eigenständigen Statistikdidaktik.\r\n\r\nDie Diskussionsbeiträge erweitern diese Perspektiven: Christina Elmer betont Wissenschaftskommunikation und AI Literacy, Helmut Küchenhoff projektbasiertes Lernen und Datenschutz, Christoph Weisser die industrielle Praxis und organisationsweite Datenkompetenz, Göran Kauermann die Verzahnung von Statistik und Data Science, und Rolf Biehler sowie Karin Binder die didaktische und institutionelle Weiterentwicklung.\r\n\r\nDie Replik greift diese Impulse auf und unterstreicht die interdisziplinäre Verantwortung für eine zukunftsfähige Statistikausbildung."},{"lang":"eng","text":"The position paper formulates nine theses on the future development of statistics education in the context of Data Science and Artificial Intelligence. It emphasizes Data & Statistical Literacy, data quality and ethics, the integration of statistics and machine learning, and the strengthening of an independent didactics of statistics.\r\n\r\nThe discussion contributions broaden these perspectives: Christina Elmer highlights science communication and AI literacy; Helmut Küchenhoff emphasizes project-based learning and data protection; Christoph Weisser stresses industrial practice and organization-wide data competence; Göran Kauermann reflects on the interplay between statistics and data science; and Rolf Biehler and Karin Binder focus on didactical and institutional development.\r\n\r\nThe rejoinder takes up these impulses and underlines the interdisciplinary responsibility for shaping future-oriented statistics education."}],"language":[{"iso":"ger"}],"status":"public","publication":"AStA Wirtschafts- und Sozialstatistisches Archiv","date_updated":"2026-07-16T15:20:37Z","date_created":"2026-05-28T11:24:42Z","publication_status":"published","author":[{"full_name":"Berger, Ursula","last_name":"Berger","first_name":"Ursula"},{"last_name":"Biehler","first_name":"Rolf","full_name":"Biehler, Rolf"},{"last_name":"Binder","first_name":"Karin","full_name":"Binder, Karin"},{"first_name":"Christina","last_name":"Elmer","full_name":"Elmer, Christina"},{"full_name":"Ertz, Florian","first_name":"Florian","last_name":"Ertz"},{"full_name":"Hotz, Thomas","last_name":"Hotz","first_name":"Thomas"},{"first_name":"Sarah","last_name":"Huber","full_name":"Huber, Sarah"},{"full_name":"Ickstadt, Katja","last_name":"Ickstadt","first_name":"Katja"},{"first_name":"Göran","last_name":"Kauermann","full_name":"Kauermann, Göran"},{"full_name":"Küchenhoff, Helmut","last_name":"Küchenhoff","first_name":"Helmut"},{"full_name":"Lübke, Karsten","last_name":"Lübke","first_name":"Karsten"},{"last_name":"Münnich","first_name":"Ralf","full_name":"Münnich, Ralf"},{"last_name":"Schüller","first_name":"Katharina","full_name":"Schüller, Katharina"},{"full_name":"Skill, Thomas","last_name":"Skill","first_name":"Thomas"},{"first_name":"Claus","last_name":"Weihs","full_name":"Weihs, Claus"},{"full_name":"Weinert, Henrike","first_name":"Henrike","last_name":"Weinert"},{"id":"264138","first_name":"Christoph","orcid":"0000-0003-0616-1027","last_name":"Weisser","full_name":"Weisser, Christoph"}],"main_file_link":[{"open_access":"1"}],"citation":{"apa":"Berger, U., Biehler, R., Binder, K., Elmer, C., Ertz, F., Hotz, T., … Weisser, C. (2026). Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung. AStA Wirtschafts- und Sozialstatistisches Archiv. https://doi.org/10.1007/s11943-026-00372-0","chicago":"Berger, Ursula, Rolf Biehler, Karin Binder, Christina Elmer, Florian Ertz, Thomas Hotz, Sarah Huber, et al. “Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung.” AStA Wirtschafts- und Sozialstatistisches Archiv, 2026. https://doi.org/10.1007/s11943-026-00372-0.","short":"U. Berger, R. Biehler, K. Binder, C. Elmer, F. Ertz, T. Hotz, S. Huber, K. Ickstadt, G. Kauermann, H. Küchenhoff, K. Lübke, R. Münnich, K. Schüller, T. Skill, C. Weihs, H. Weinert, C. Weisser, AStA Wirtschafts- und Sozialstatistisches Archiv (2026).","alphadin":"Berger, Ursula ; Biehler, Rolf ; Binder, Karin ; Elmer, Christina ; Ertz, Florian ; Hotz, Thomas ; Huber, Sarah ; Ickstadt, Katja ; u. a.: Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung. In: AStA Wirtschafts- und Sozialstatistisches Archiv, Springer (2026)","ieee":"U. Berger et al., “Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung,” AStA Wirtschafts- und Sozialstatistisches Archiv, 2026.","mla":"Berger, Ursula, et al. “Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung.” AStA Wirtschafts- und Sozialstatistisches Archiv, Springer, 2026, doi:10.1007/s11943-026-00372-0.","bibtex":"@article{Berger_Biehler_Binder_Elmer_Ertz_Hotz_Huber_Ickstadt_Kauermann_Küchenhoff_et al._2026, title={Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung}, DOI={10.1007/s11943-026-00372-0}, journal={AStA Wirtschafts- und Sozialstatistisches Archiv}, publisher={Springer}, author={Berger, Ursula and Biehler, Rolf and Binder, Karin and Elmer, Christina and Ertz, Florian and Hotz, Thomas and Huber, Sarah and Ickstadt, Katja and Kauermann, Göran and Küchenhoff, Helmut and et al.}, year={2026} }","ama":"Berger U, Biehler R, Binder K, et al. Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung. AStA Wirtschafts- und Sozialstatistisches Archiv. 2026. doi:10.1007/s11943-026-00372-0"},"_id":"6924","type":"journal_article","alternative_id":["7067"],"doi":"10.1007/s11943-026-00372-0","publisher":"Springer","article_type":"letter_note","year":"2026","oa":"1","title":"Daten, Künstliche Intelligenz und Evidenz - neue Anforderungen an die Statistikausbildung an Hochschulen: Diskussion und Erwiderung","quality_controlled":"1"},{"main_file_link":[{"open_access":"1"}],"citation":{"short":"A.P. Amorin, A. Python, C. Weisser, LREC 2026 - The Fifteenth Biennial Language Resources and Evaluation Conference - Financial Narrative Processing (FNP) Workshop (2026).","alphadin":"Amorin, Alvaro Paredes ; Python, Andre ; Weisser, Christoph: Not All News Is Equal: Topic- and Event-Conditional Sentiment From Finetuned LLMs for Aluminum Price Forecasting. In: LREC 2026 - The Fifteenth biennial Language Resources and Evaluation Conference - Financial Narrative Processing (FNP) Workshop (2026)","ieee":"A. P. Amorin, A. Python, and C. 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