Abstract
Natural language processing (NLP) has recently got into the center of public attention to AI, due to the impressive capabilities of large language models (LLM) such as the one underlying ChatGPT. LLMs cannot only generate text that is barely distinguishable from human-written anymore, but the most recent LLMs can even tackle problems successfully that they have never seen before. In this talk, I start from the general functionalities of LLMs, before I presented insights from selected research of my group involving LLMs to reconstruct, optimize, and create natural language text for specific NLP tasks. On this basis, I look at the recent breakthroughs that caused the success of ChatGPT-like technologies and the paradigm shift that comes with it.
Bio Henning Wachsmuth
Henning Wachsmuth leads the Natural Language Processing Group at the Institute of Artificial Intelligence of Leibniz University Hannover since 2022. After receiving his PhD from Paderborn University in 2015, he worked as a PostDoc at Bauhaus-Universität Weimar, before he returned to Paderborn as a junior professor from 2018 to 2022. His group studies how intentions and views of people are reflected in language and how machines can understand and imitate this with large language models. Henning’s main research interests include computational argumentation, the mitigation of social bias and media bias, and the construction of human-like explanations for educational and explainable NLP.
