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Dennis Assenmacher

2 accepted papers

2023

People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detection

EMNLP 2023long main

NLP models are used in a variety of critical social computing tasks, such as detecting sexist, racist, or otherwise hateful content. Therefore, it is imperative that these models are robust to spurious features. Past work has attempted to tackle such spurious features using training data augmentatio…

Cited by 0SourcecodeScholar
2021

$\texttt{RP-Mod}\ \&\ \texttt{RP-Crowd:}$ Moderator- and Crowd-Annotated German News Comment Datasets

NeurIPS 2021poster

Abuse and hate are penetrating social media and many comment sections of news media companies. To prevent losing readers who get appalled by inappropriate texts, these platform providers invest considerable efforts to moderate user-generated contributions. This is further enforced by legislative act…

Cited by 0SourceScholar