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20242026
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stat.ML2026

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…

stat.ML2026

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…

stat.ML2025

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…

stat.ML2025

Non-asymptotic Analysis of Diffusion Annealed Langevin Monte Carlo for Generative Modelling

Paula Cordero-Encinar, O. Deniz Akyildiz, Andrew B. Duncan

We investigate the theoretical properties of general diffusion (interpolation) paths and their Langevin Monte Carlo implementation, referred to as diffusion annealed Langevin Monte…

stat.ML2024

Deep Optimal Sensor Placement for Black Box Stochastic Simulations

Paula Cordero-Encinar, Tobias Schröder, Peter Yatsyshin +1

Selecting cost-effective optimal sensor configurations for subsequent inference of parameters in black-box stochastic systems faces significant computational barriers. We propose a…