12 citations · 12 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
Exploring LLM Prompting Strategies for Joint Essay Scoring and Feedback Generation
Maja Stahl, Leon Biermann, Andreas Nehring +1
Individual feedback can help students improve their essay writing skills. However, the manual effort required to provide such feedback limits individualization in practice. Automat…
A School Student Essay Corpus for Analyzing Interactions of Argumentative Structure and Quality
Maja Stahl, Nadine Michel, Sebastian Kilsbach +3
Learning argumentative writing is challenging. Besides writing fundamentals such as syntax and grammar, learners must select and arrange argument components meaningfully to create…