3 citations · 5 across the 7 of their papers we have counts for
9 papers
Cultural (In)Competence: Investigating Culture-Specific Stereotype Detection Capabilities of LLMs
Maximilian Spliethöver, Jannes Lötfering, Dominik Bachmann +4
Stereotypes are subjective constructs that are mediated by the cultural context in which they are viewed. Successfully modeling them thus also requires cultural competence. When us…
Dynamic Priors in Bayesian Optimization for Hyperparameter Optimization
Lukas Fehring, Marcel Wever, Maximilian Spliethöver +3
Bayesian optimization (BO) is a widely used approach to hyperparameter optimization (HPO). However, most existing HPO methods only incorporate expert knowledge during initializatio…
Investigating Co-Constructive Behavior of Large Language Models in Explanation Dialogues
Leandra Fichtel, Maximilian Spliethöver, Eyke Hüllermeier +9
The ability to generate explanations that are understood by explainees is the quintessence of explainable artificial intelligence. Since understanding depends on the explainee's ba…
Adaptive Prompting: Ad-hoc Prompt Composition for Social Bias Detection
Maximilian Spliethöver, Tim Knebler, Fabian Fumagalli +4
Recent advances on instruction fine-tuning have led to the development of various prompting techniques for large language models, such as explicit reasoning steps. However, the suc…
Disentangling Dialect from Social Bias via Multitask Learning to Improve Fairness
Maximilian Spliethöver, Sai Nikhil Menon, Henning Wachsmuth
Dialects introduce syntactic and lexical variations in language that occur in regional or social groups. Most NLP methods are not sensitive to such variations. This may lead to unf…
No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media
Maximilian Spliethöver, Maximilian Keiff, Henning Wachsmuth
News articles both shape and reflect public opinion across the political spectrum. Analyzing them for social bias can thus provide valuable insights, such as prevailing stereotypes…
Key Point Analysis via Contrastive Learning and Extractive Argument Summarization
Milad Alshomary, Timon Gurcke, Shahbaz Syed +5
Key point analysis is the task of extracting a set of concise and high-level statements from a given collection of arguments, representing the gist of these arguments. This paper p…
Argument from Old Man's View: Assessing Social Bias in Argumentation
Maximilian Spliethöver, Henning Wachsmuth
Social bias in language - towards genders, ethnicities, ages, and other social groups - poses a problem with ethical impact for many NLP applications. Recent research has shown tha…
Is It Worth the Attention? A Comparative Evaluation of Attention Layers for Argument Unit Segmentation
Maximilian Spliethöver, Jonas Klaff, Hendrik Heuer
Attention mechanisms have seen some success for natural language processing downstream tasks in recent years and generated new State-of-the-Art results. A thorough evaluation of th…