2 citations · 2 across the 3 of their papers we have counts for
4 papers
LLM-based Rewriting of Inappropriate Argumentation using Reinforcement Learning from Machine Feedback
Timon Ziegenbein, Gabriella Skitalinskaya, Alireza Bayat Makou +1
Ensuring that online discussions are civil and productive is a major challenge for social media platforms. Such platforms usually rely both on users and on automated detection tool…
To Revise or Not to Revise: Learning to Detect Improvable Claims for Argumentative Writing Support
Gabriella Skitalinskaya, Henning Wachsmuth
Optimizing the phrasing of argumentative text is crucial in higher education and professional development. However, assessing whether and how the different claims in a text should…
Claim Optimization in Computational Argumentation
Gabriella Skitalinskaya, Maximilian Spliethöver, Henning Wachsmuth
An optimal delivery of arguments is key to persuasion in any debate, both for humans and for AI systems. This requires the use of clear and fluent claims relevant to the given deba…
Learning From Revisions: Quality Assessment of Claims in Argumentation at Scale
Gabriella Skitalinskaya, Jonas Klaff, Henning Wachsmuth
Assessing the quality of arguments and of the claims the arguments are composed of has become a key task in computational argumentation. However, even if different claims share the…