4 papers
FairPFN: A Tabular Foundation Model for Causal Fairness
Jake Robertson, Noah Hollmann, Samuel Müller +2
Machine learning (ML) systems are utilized in critical sectors, such as healthcare, law enforcement, and finance. However, these systems are often trained on historical data that c…
A Llama walks into the 'Bar': Efficient Supervised Fine-Tuning for Legal Reasoning in the Multi-state Bar Exam
Rean Fernandes, André Biedenkapp, Frank Hutter +1
Legal reasoning tasks present unique challenges for large language models (LLMs) due to the complexity of domain-specific knowledge and reasoning processes. This paper investigates…
A Human-in-the-Loop Fairness-Aware Model Selection Framework for Complex Fairness Objective Landscapes
Jake Robertson, Thorsten Schmidt, Frank Hutter +1
Fairness-aware Machine Learning (FairML) applications are often characterized by complex social objectives and legal requirements, frequently involving multiple, potentially confli…
FairPFN: Transformers Can do Counterfactual Fairness
Jake Robertson, Noah Hollmann, Noor Awad +1
Machine Learning systems are increasingly prevalent across healthcare, law enforcement, and finance but often operate on historical data, which may carry biases against certain dem…