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…
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…
cond-mat.dis-nn2025
Isolating the hard core of phaseless inference: the Phase selection formulation
Davide Straziota, Luca Saglietti
Real-valued Phase retrieval is a non-convex continuous inference problem, where a high-dimensional signal is to be reconstructed from a dataset of signless linear measurements. Foc…