[{"publication_identifier":{"isbn":["979-8-4007-2492-3"]},"user_id":"89807","citation":{"apa":"Grimm, V., Rubart, J., Herder, E., &#38; Röcker, C. (2026). LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation. In W.-T. Balke, F. Plötzky, M. Spaniol, E. Herder, L. Manikonda, H. Liu, L.-D. Ibáñez, R. Rezapour, &#38; ACM Press (Eds.), <i>WebSci Companion ’26: Companion Publication of the 2026 18th ACM Web Science Conference</i> (pp. 110–116). ACM. <a href=\"https://doi.org/10.1145/3795513.3810452\">https://doi.org/10.1145/3795513.3810452</a>","short":"V. Grimm, J. Rubart, E. Herder, C. Röcker, LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation, ACM, New York, USA, 2026.","van":"Grimm V, Rubart J, Herder E, Röcker C. LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation. Balke WT, Plötzky F, Spaniol M, Herder E, Manikonda L, Liu H, et al., editors. WebSci Companion ’26: Companion Publication of the 2026 18th ACM Web Science Conference. New York, USA: ACM; 2026.","bjps":"<b>Grimm V <i>et al.</i></b> (2026) <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>, Balke W-T et al. (eds). New York, USA: ACM.","havard":"V. Grimm, J. Rubart, E. Herder, C. Röcker, LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation, ACM, New York, USA, 2026.","chicago-de":"Grimm, Valentin, Jessica Rubart, Eelco Herder und Carsten Röcker. 2026. <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>. Hg. von Wolf-Tilo Balke, Florian Plötzky, Marc Spaniol, Eelco Herder, Lydia Manikonda, Haiming Liu, Luis-Daniel Ibáñez, Rezvaneh Rezapour, und ACM Press. <i>WebSci Companion ’26: Companion Publication of the 2026 18th ACM Web Science Conference</i>. New York, USA: ACM. doi:<a href=\"https://doi.org/10.1145/3795513.3810452\">https://doi.org/10.1145/3795513.3810452</a>, .","mla":"Grimm, Valentin, et al. “LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation.” <i>WebSci Companion ’26: Companion Publication of the 2026 18th ACM Web Science Conference</i>, edited by Wolf-Tilo Balke et al., ACM, 2026, pp. 110–16, <a href=\"https://doi.org/10.1145/3795513.3810452\">https://doi.org/10.1145/3795513.3810452</a>.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Grimm, Valentin</span> ; <span style=\"font-variant:small-caps;\">Rubart, Jessica</span> ; <span style=\"font-variant:small-caps;\">Herder, Eelco</span> ; <span style=\"font-variant:small-caps;\">Röcker, Carsten</span> ; <span style=\"font-variant:small-caps;\"><span style=\"font-variant:small-caps;\">Balke, W.-T.</span> ; <span style=\"font-variant:small-caps;\">Plötzky, F.</span> ; <span style=\"font-variant:small-caps;\">Spaniol, M.</span> ; <span style=\"font-variant:small-caps;\">Herder, E.</span> ; <span style=\"font-variant:small-caps;\">Manikonda, L.</span> ; <span style=\"font-variant:small-caps;\">Liu, H.</span> ; <span style=\"font-variant:small-caps;\">Ibáñez, L.-D.</span> ; <span style=\"font-variant:small-caps;\">Rezapour, R.</span> ; u. a.</span> (Hrsg.): <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>. New York, USA : ACM, 2026","ama":"Grimm V, Rubart J, Herder E, Röcker C. <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>. (Balke WT, Plötzky F, Spaniol M, et al., eds.). ACM; 2026:110-116. doi:<a href=\"https://doi.org/10.1145/3795513.3810452\">https://doi.org/10.1145/3795513.3810452</a>","ieee":"V. Grimm, J. Rubart, E. Herder, and C. Röcker, <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>. New York, USA: ACM, 2026, pp. 110–116. doi: <a href=\"https://doi.org/10.1145/3795513.3810452\">https://doi.org/10.1145/3795513.3810452</a>.","ufg":"<b>Grimm, Valentin u. a.</b>: LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation, hg. von Balke, Wolf-Tilo u. a., New York, USA 2026.","chicago":"Grimm, Valentin, Jessica Rubart, Eelco Herder, and Carsten Röcker. <i>LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation</i>. Edited by Wolf-Tilo Balke, Florian Plötzky, Marc Spaniol, Eelco Herder, Lydia Manikonda, Haiming Liu, Luis-Daniel Ibáñez, Rezvaneh Rezapour, and ACM Press. <i>WebSci Companion ’26: Companion Publication of the 2026 18th ACM Web Science Conference</i>. New York, USA: ACM, 2026. <a href=\"https://doi.org/10.1145/3795513.3810452\">https://doi.org/10.1145/3795513.3810452</a>."},"_id":"13730","status":"public","editor":[{"last_name":"Balke","full_name":"Balke, Wolf-Tilo","first_name":"Wolf-Tilo"},{"last_name":"Plötzky","first_name":"Florian","full_name":"Plötzky, Florian"},{"last_name":"Spaniol","full_name":"Spaniol, Marc","first_name":"Marc"},{"last_name":"Herder","first_name":"Eelco","full_name":"Herder, Eelco"},{"last_name":"Manikonda","full_name":"Manikonda, Lydia","first_name":"Lydia"},{"first_name":"Haiming","full_name":"Liu, Haiming","last_name":"Liu"},{"last_name":"Ibáñez","first_name":"Luis-Daniel","full_name":"Ibáñez, Luis-Daniel"},{"last_name":"Rezapour","full_name":"Rezapour, Rezvaneh","first_name":"Rezvaneh"}],"date_created":"2026-05-05T16:16:34Z","year":"2026","language":[{"iso":"eng"}],"date_updated":"2026-07-02T10:16:02Z","doi":"https://doi.org/10.1145/3795513.3810452","author":[{"full_name":"Grimm, Valentin","first_name":"Valentin","id":"74000","last_name":"Grimm"},{"orcid":"0000-0003-0937-3551","id":"45672","full_name":"Rubart, Jessica","first_name":"Jessica","last_name":"Rubart"},{"first_name":"Eelco","full_name":"Herder, Eelco","last_name":"Herder"},{"first_name":"Carsten","full_name":"Röcker, Carsten","id":"61525","last_name":"Röcker"}],"place":"New York, USA","abstract":[{"lang":"eng","text":"This paper introduces an LLM-mediated AI Advisor that contextualizes and synthesizes heterogeneous explainable AI (XAI) outputs to support fast and calibrated misinformation judgments in time-sensitive social media settings. We define LLM-mediated XAI as a process in which a large language model aggregates, prioritizes, and translates heterogeneous XAI outputs into a context-sensitive explanation tailored to the user’s decision situation. Semantic features, XAI modules and LLM-based summarization and synthesis enable the generation of explanations that are adapted in three ways: compressed for time-efficient decisions, translated into non-technical language, and progressively expandable for deeper inspection. Through a mixed-methods user study, including a quantitative study and a qualitative study, we analyze how users interpret, challenge and strategically rely on LLM-mediated explanations during real-world misinformation assessment tasks. The findings indicate that the approach reduces time-to-decision and supports critical inspection without inducing over-reliance. Progressive disclosure and different techniques to present information favored different user needs while conversational functionality was rarely used due to unclear benefits and fear of confusion."}],"publisher":"ACM","keyword":["Large Language Model Mediation","Explainable AI","Decision Co- Pilot Systems","Misinformation Detection"],"corporate_editor":["ACM Press"],"title":"LLM-Mediated XAI Explanations: An AI Advisor for Fast and Calibrated Judgments on Potential Misinformation","type":"conference_editor_article","conference":{"end_date":"2026-05-26","location":"Braunschweig","name":"18th ACM Web Science Conference ; WebSci Companion '26","start_date":"2026-05-26"},"publication_status":"published","publication":"WebSci Companion '26: Companion Publication of the 2026 18th ACM Web Science Conference","page":"110-116","quality_controlled":"1","department":[{"_id":"DEP5023"},{"_id":"DEP8008"},{"_id":"DEP5027"}]},{"date_updated":"2026-07-02T10:24:17Z","language":[{"iso":"eng"}],"date_created":"2025-01-21T13:23:17Z","year":"2024","_id":"12383","user_id":"89807","citation":{"ama":"Grimm V, Rubart J, Söhlke P. <i>Conversational Data Stories</i>. (Atzenbeck C, Rubart J, ACM, eds.). ACM; 2024:6. doi:<a href=\"https://doi.org/10.1145/3679058.3688631\">10.1145/3679058.3688631</a>","ieee":"V. Grimm, J. Rubart, and P. Söhlke, <i>Conversational Data Stories</i>. New York: ACM, 2024, p. 6. doi: <a href=\"https://doi.org/10.1145/3679058.3688631\">10.1145/3679058.3688631</a>.","ufg":"<b>Grimm, Valentin/Rubart, Jessica/Söhlke, Patrick</b>: Conversational Data Stories, hg. von Atzenbeck, Claus/Rubart, Jessica, ACM, New York 2024.","chicago":"Grimm, Valentin, Jessica Rubart, and Patrick Söhlke. <i>Conversational Data Stories</i>. Edited by Claus Atzenbeck, Jessica Rubart, and ACM. <i>Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN’24)</i>. New York: ACM, 2024. <a href=\"https://doi.org/10.1145/3679058.3688631\">https://doi.org/10.1145/3679058.3688631</a>.","apa":"Grimm, V., Rubart, J., &#38; Söhlke, P. (2024). Conversational Data Stories. In C. Atzenbeck, J. Rubart, &#38; ACM (Eds.), <i>Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN’24)</i> (p. 6). ACM. <a href=\"https://doi.org/10.1145/3679058.3688631\">https://doi.org/10.1145/3679058.3688631</a>","short":"V. Grimm, J. Rubart, P. Söhlke, Conversational Data Stories, ACM, New York, 2024.","van":"Grimm V, Rubart J, Söhlke P. Conversational Data Stories. Atzenbeck C, Rubart J, ACM, editors. Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN’24). New York: ACM; 2024.","bjps":"<b>Grimm V, Rubart J and Söhlke P</b> (2024) <i>Conversational Data Stories</i>, Atzenbeck C, Rubart J, and ACM (eds). New York: ACM.","havard":"V. Grimm, J. Rubart, P. Söhlke, Conversational Data Stories, ACM, New York, 2024.","chicago-de":"Grimm, Valentin, Jessica Rubart und Patrick Söhlke. 2024. <i>Conversational Data Stories</i>. Hg. von Claus Atzenbeck, Jessica Rubart, und ACM. <i>Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN’24)</i>. New York: ACM. doi:<a href=\"https://doi.org/10.1145/3679058.3688631\">10.1145/3679058.3688631</a>, .","mla":"Grimm, Valentin, et al. “Conversational Data Stories.” <i>Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN’24)</i>, edited by Claus Atzenbeck et al., ACM, 2024, p. 6, <a href=\"https://doi.org/10.1145/3679058.3688631\">https://doi.org/10.1145/3679058.3688631</a>.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Grimm, Valentin</span> ; <span style=\"font-variant:small-caps;\">Rubart, Jessica</span> ; <span style=\"font-variant:small-caps;\">Söhlke, Patrick</span> ; <span style=\"font-variant:small-caps;\">Atzenbeck, C.</span> ; <span style=\"font-variant:small-caps;\">Rubart, J.</span> ; <span style=\"font-variant:small-caps;\">ACM</span> (Hrsg.): <i>Conversational Data Stories</i>. New York : ACM, 2024"},"editor":[{"last_name":"Atzenbeck","full_name":"Atzenbeck, Claus","first_name":"Claus"},{"orcid":"0000-0003-0937-3551","first_name":"Jessica","full_name":"Rubart, Jessica","id":"45672","last_name":"Rubart"}],"status":"public","publication_identifier":{"isbn":["979-8-4007-1120-6"]},"page":"6","publication":"Proceedings of the 7th Workshop on Human Factors in Hypertext (HUMAN'24)","department":[{"_id":"DEP8008"}],"publication_status":"published","conference":{"location":"Poznan Poland","name":"7th Workshop on Human Factors in Hypertext (HUMAN)","start_date":"2024-09-10","end_date":"2024-09-13"},"type":"conference_editor_article","corporate_editor":["ACM"],"keyword":["Data Storytelling","Conversational Assistant","Conversational Data Storytelling","Explainable AI"],"publisher":"ACM","title":"Conversational Data Stories","author":[{"last_name":"Grimm","full_name":"Grimm, Valentin","first_name":"Valentin","id":"74000"},{"last_name":"Rubart","first_name":"Jessica","full_name":"Rubart, Jessica","id":"45672","orcid":"0000-0003-0937-3551"},{"full_name":"Söhlke, Patrick","first_name":"Patrick","last_name":"Söhlke"}],"doi":"10.1145/3679058.3688631","abstract":[{"lang":"eng","text":"Data stories are about revealing and communicating insights from complex data. In this paper, we propose conversational data stories, which support end users in understanding the key findings of the data analysis at hand by natural language conversation. Creating these stories manually means to put a lot of effort into understanding the data and crafting visuals. With increasingly powerful generative large language models (LLMs), natural language processing as well as automating the creation of data stories is a promising field. We present a concept for a conversational data storytelling system that integrates LLMs as well as explainable AI. We present the collected requirements for our system concept and how the requirements are addressed. To show the potential of our approach, we provide a use case scenario and a discussion in this paper. This is supposed to serve as a basis for future research that will aim at investigating the technical reliability and the user experience of such a system."}],"place":"New York"}]