Vivek F. Farias

Pruning reasoning steps can slash generation length by up to 60% without sacrificing accuracy, revolutionizing how LLMs approach complex tasks.

Matching the full posterior covariance in Gaussian DDPMs slashes path KL error and unlocks faster, higher-quality sampling with a surprisingly simple Lanczos-based method.