2 papers
cs.LG2026
Can LLMs Beat Classical Hyperparameter Optimization Algorithms? A Study on autoresearch
Fabio Ferreira, Lucca Wobbe, Arjun Krishnakumar +2
The autoresearch repository enables an LLM agent to optimize hyperparameters by editing training code directly. We use it as a testbed to compare classical HPO algorithms against L…
cs.LG2026
GAMformer: Bridging Tabular Foundation Models and Interpretable Machine Learning
Andreas Mueller, Julien Siems, Harsha Nori +4
While interpretability is crucial for machine learning applications in safety-critical domains and for regulatory compliance, existing tabular foundation models like TabPFN lack tr…