3 papers
cs.LG2026
Transmuting prompts into weights
Hanna Mazzawi, Benoit Dherin, Michael Munn +3
A growing body of research has demonstrated that the behavior of large language models can be effectively controlled at inference time by directly modifying their internal states,…
cs.CL2026
Learning without training: The implicit dynamics of in-context learning
Benoit Dherin, Michael Munn, Hanna Mazzawi +2
One of the most striking features of Large Language Models (LLMs) is their ability to learn in-context. Namely at inference time an LLM is able to learn new patterns without any ad…
cs.LG2025
Learning by solving differential equations
Benoit Dherin, Michael Munn, Hanna Mazzawi +3
Modern deep learning algorithms use variations of gradient descent as their main learning methods. Gradient descent can be understood as the simplest Ordinary Differential Equation…