3 papers
cs.CL2026
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…
cs.CL2026
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…
cs.CL2025
Towards a Perspectivist Turn in Argument Quality Assessment
Julia Romberg, Maximilian Maurer, Henning Wachsmuth +1
The assessment of argument quality depends on well-established logical, rhetorical, and dialectical properties that are unavoidably subjective: multiple valid assessments may exist…