35 citations · 35 across the 4 of their papers we have counts for
5 papers · 1 filter
Amortizing Sequential Experimental Design in Reasoning LLMs
Anita Kriz, Antonin Berthon, Nicolás Astorga +1
Despite their extensive pretraining knowledge and strong reasoning capabilities, large language models (LLMs) struggle to adaptively gather information in experimental design tasks…
On-Policy or Off-Policy Learning? A Systematic Study of Distillation Dynamics
Julianna Piskorz, Antonin Berthon, Mihaela van der Schaar
On-policy learning has been argued to reduce catastrophic forgetting, produce sparser parameter updates, and improve generalisation. However, existing comparisons between supervise…
Skill Neologisms: Towards Skill-based Continual Learning
Antonin Berthon, Nicolas Astorga, Mihaela van der Schaar
Modern LLMs show mastery over an ever-growing range of skills, as well as the ability to compose them flexibly. However, extending model capabilities to new skills in a scalable ma…
G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
Samuel Holt, Max Ruiz Luyten, Antonin Berthon +1
Constructing robust simulators is essential for asking "what if?" questions and guiding policy in critical domains like healthcare and logistics. However, existing methods often st…
Confidence Scores Make Instance-dependent Label-noise Learning Possible
Antonin Berthon, Bo Han, Gang Niu +2
In learning with noisy labels, for every instance, its label can randomly walk to other classes following a transition distribution which is named a noise model. Well-studied noise…