Teaching LLMs Human-Like Editing of Inappropriate Argumentation via Reinforcement Learning

ArXi:2604.12770v1 Announce Type: new Editing human-written text has become a standard use case of large language models (LLMs), for example, to make one's arguments appropriate for a discussion. Comparing human to LLM-generated edits, however, we observe a mismatch in editing strategies: While LLMs often perform multiple scattered edits and tend to change meaning notably, humans rather encapsulate dependent changes in self-contained, meaning-preserving edits.