3 papers
cs.ET2026
A Framework for Stochastic Differentiable Programming
Guillaume Verdon, Leo Tyrpak, Owen Lockwood +5
We introduce Parametrized Stochastic Circuits (PSCs), a gate-based intermediate representation for programmable stochastic dynamics in which typed local stochastic kernels with tun…
cs.LG2026
Gradient Smoothing: Coupling Layer-wise Updates for Improved Optimization
Haoming Meng, Anton Sugolov, Vardan Papyan
Deep neural networks with repeated architectural blocks, such as transformers, often exhibit structured relationships across layers that emerge during training. Motivated by this o…
cs.LG2025
Transformer Block Coupling and its Correlation with Generalization in LLMs
Murdock Aubry, Haoming Meng, Anton Sugolov +1
Large Language Models (LLMs) have made significant strides in natural language processing, and a precise understanding of the internal mechanisms driving their success is essential…