Speaker: Henning Wachsmuth (Leibniz University Hannover)
Title: Toward Argumentative Large Language Models
Date: Thursday, February 5, 2026 – 15:00
Summary: Today’s large language models (LLMs) are optimized toward giving helpful answers in response to prompts. In many situations, however, it may be preferable for an LLM to foster critical thinking rather than just following an instruction. While recent LLMs are said to ‘reason’, they barely build on established reasoning concepts known from argumentation theory. In this talk, I will give insights into recent efforts of my group in making LLMs more argumentative. Starting from basics of LLM training processes, I will present how to specialize LLMs for argumentation tasks via instruction fine-tuning as well as how to align the arguments they generate using reinforcement learning. From there, I will give an outlook on how to improve the actual reasoning capabilities of LLMs.
Bio: Henning Wachsmuth leads the Natural Language Processing Group at the Institute of Artificial Intelligence of Leibniz University Hannover. After receiving his PhD from Paderborn University in 2015, he worked as a PostDoc at Bauhaus-Universität Weimar and as a junior professor in Paderborn, before he became a full professor in Hannover in 2022. His group does basic research on large language models for computational argumentation, social bias detection and mitigation, as well as explainable and educational NLP. Henning’s main research interests include the generation of audience-aware text, the assessment of pragmatic text quality, and the modeling of bias and framing.
Registration: https://www.hitz.eus/webinar_i