3 papers
cs.LG2026
Biased Generalization in Diffusion Models
Jerome Garnier-Brun, Luca Biggio, Davide Beltrame +2
Generalization in generative modeling is defined as the ability to learn an underlying distribution from a finite dataset and produce novel samples, with evaluation largely driven…
astro-ph.CO2025
Measuring the Dark Matter Self-Interaction Cross-Section with Deep Compact Clustering for Robust Machine Learning Inference
Ethan Tregidga, David Harvey, Luca Biggio +1
We have developed a machine learning algorithm capable of detecting ``out-of-domain data'' for trustworthy cosmological inference. By using data from two separate suites of cosmolo…
cs.CL2025
On the Bias of Next-Token Predictors Toward Systematically Inefficient Reasoning: A Shortest-Path Case Study
Riccardo Alberghi, Elizaveta Demyanenko, Luca Biggio +1
Recent advances in natural language processing highlight two key factors for improving reasoning in large language models (LLMs): (i) allocating more test-time compute tends to hel…