170 citations · 516 across the 41 of their papers we have counts for
5 papers · 1 filter
Cultural (In)Competence: Investigating Culture-Specific Stereotype Detection Capabilities of LLMs
Maximilian Spliethöver, Jannes Lötfering, Dominik Bachmann +4
Stereotypes are subjective constructs that are mediated by the cultural context in which they are viewed. Successfully modeling them thus also requires cultural competence. When us…
Generating Constructive Feedback on Stories via Reinforcement Learning
Maja Stahl, Timon Ziegenbein, Henning Wachsmuth
Constructive feedback is crucial for creative writers to refine their storytelling abilities. Since receiving feedback from human experts is often costly and time-intensive, large…
Attribute-Based Activation Steering of LLMs for Group-Specific Explanation Generation
Leandra Fichtel, Janek Prange, Henning Wachsmuth
To effectively enable people to understand new topics, explanations should be tailored to their backgrounds and abilities. Prompting alone has been shown to be insufficient for cre…
ArgBench: Benchmarking LLMs on Computational Argumentation Tasks
Yamen Ajjour, Carlotta Quensel, Nedim Lipka +1
Argumentation skills are an essential toolkit for large language models (LLMs). These skills are crucial in various use cases, including self-reflection, debating collaboratively f…
Teaching LLMs Human-Like Editing of Inappropriate Argumentation via Reinforcement Learning
Timon Ziegenbein, Maja Stahl, Henning Wachsmuth
Editing human-written text has become a standard use case of large language models (LLMs), for example, to make one's arguments more appropriate for a discussion. Comparing human t…