3 papers
cs.CL2026
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…
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
ArgInstruct: Specialized Instruction Fine-Tuning for Computational Argumentation
Maja Stahl, Timon Ziegenbein, Joonsuk Park +1
Training large language models (LLMs) to follow instructions has significantly enhanced their ability to tackle unseen tasks. However, despite their strong generalization capabilit…