9 papers
Soft Specialists: -Rényi Ensembles for Uncertainty-Aware LLM Post-Training
Paula Cordero-Encinar, Georgy Tyukin, Andrew B. Duncan
Existing training approaches for large language models learn a single set of parameters, based on large volumes of data, which is typically heterogeneous, conflicting and often out…
Diffusion Path Samplers via Sequential Monte Carlo
James Matthew Young, Paula Cordero-Encinar, Sebastian Reich +2
We develop diffusion-based samplers for target distributions known up to a normalising constant. To this end, we rely on the well-known diffusion path that smoothly interpolates be…
Weak Functional Inequalities for Perturbed Measures
Patrick Cattiaux, Paula Cordero-Encinar, Arnaud Guillin
This paper is a follow up to an article by two of the authors dedicated to the study of Poincaré and logarithmic Sobolev inequalities for measures of the form wh…
Diffusion annealed Langevin dynamics: a theoretical study
Patrick Cattiaux, Paula Cordero-Encinar, Arnaud Guillin
In this work we study the diffusion annealed Langevin dynamics, a score-based diffusion process recently introduced in the theory of generative models and which is an alternative t…
Sampling by averaging: A multiscale approach to score estimation
Paula Cordero-Encinar, Andrew B. Duncan, Sebastian Reich +1
We introduce a novel framework for efficient sampling from complex, unnormalised target distributions by exploiting multiscale dynamics. Traditional score-based sampling methods ei…
Certified Self-Consistency: Statistical Guarantees and Test-Time Training for Reliable Reasoning in LLMs
Paula Cordero-Encinar, Andrew B. Duncan
Recent advances such as self-consistency and test-time reinforcement learning (TTRL) improve the reliability of large language models (LLMs) without additional supervision, yet the…