2 papers
cs.LG2026
General and Efficient Steering of Diffusion Models
Qingsong Wang, Mikhail Belkin, Yusu Wang
Steering diffusion models toward conditions unseen during training typically requires either retraining with conditional inputs or per-step gradient computations, both of which inc…
cs.LG2025
The Features at Convergence Theorem: a first-principles alternative to the Neural Feature Ansatz for how networks learn representations
Enric Boix-Adsera, Neil Mallinar, James B. Simon +1
It is a central challenge in deep learning to understand how neural networks learn representations. A leading approach is the Neural Feature Ansatz (NFA) (Radhakrishnan et al. 2024…