1 citations · 1 across the 8 of their papers we have counts for
6 papers · 1 filter
Scalable Classification of Course Information Sheets Using Large Language Models: A Reusable Institutional Method for Academic Quality Assurance
Brecht Verbeken, Joke Van den Broeck, Inge De Cleyn +4
Purpose: Higher education institutions face increasing pressure to audit course designs for generative AI (GenAI) integration. This paper presents an end-to-end method for using la…
Probing the Trajectories of Reasoning Traces in Large Language Models
Marthe Ballon, Brecht Verbeken, Vincent Ginis +1
Large language models (LLMs) increasingly solve difficult problems by producing "reasoning traces" before emitting a final response. However, it remains unclear how accuracy and de…
Structurally Human, Semantically Biased: Detecting LLM-Generated References with Embeddings and GNNs
Melika Mobini, Vincent Holst, Floriano Tori +2
Large language models are increasingly used to curate bibliographies, raising the question: are their reference lists distinguishable from human ones? We build paired citation grap…
Estimating problem difficulty without ground truth using Large Language Model comparisons
Marthe Ballon, Andres Algaba, Brecht Verbeken +1
Recent advances in the finetuning of large language models (LLMs) have significantly improved their performance on established benchmarks, emphasizing the need for increasingly dif…
Decision-centric fairness: Evaluation and optimization for resource allocation problems
Simon De Vos, Jente Van Belle, Andres Algaba +2
Data-driven decision support tools play an increasingly central role in decision-making across various domains. In this work, we focus on binary classification models for predictin…
Flexible Counterfactual Explanations with Generative Models
Stig Hellemans, Andres Algaba, Sam Verboven +1
Counterfactual explanations provide actionable insights to achieve desired outcomes by suggesting minimal changes to input features. However, existing methods rely on fixed sets of…