8 citations · 11 across the 7 of their papers we have counts for
8 papers
Composition and Control with Distilled Energy Diffusion Models and Sequential Monte Carlo
James Thornton, Louis Bethune, Ruixiang Zhang +3
Diffusion models may be formulated as a time-indexed sequence of energy-based models, where the score corresponds to the negative gradient of an energy function. As opposed to lear…
Mechanisms of Projective Composition of Diffusion Models
Arwen Bradley, Preetum Nakkiran, David Berthelot +2
We study the theoretical foundations of composition in diffusion models, with a particular focus on out-of-distribution extrapolation and length-generalization. Prior work has show…
Classifier-Free Guidance is a Predictor-Corrector
Arwen Bradley, Preetum Nakkiran
We investigate the theoretical foundations of classifier-free guidance (CFG). CFG is the dominant method of conditional sampling for text-to-image diffusion models, yet unlike othe…
Step-by-Step Diffusion: An Elementary Tutorial
Preetum Nakkiran, Arwen Bradley, Hattie Zhou +1
We present an accessible first course on diffusion models and flow matching for machine learning, aimed at a technical audience with no diffusion experience. We try to simplify the…
What Algorithms can Transformers Learn? A Study in Length Generalization
Hattie Zhou, Arwen Bradley, Etai Littwin +5
Large language models exhibit surprising emergent generalization properties, yet also struggle on many simple reasoning tasks such as arithmetic and parity. This raises the questio…
Vanishing Gradients in Reinforcement Finetuning of Language Models
Noam Razin, Hattie Zhou, Omid Saremi +5
Pretrained language models are commonly aligned with human preferences and downstream tasks via reinforcement finetuning (RFT), which refers to maximizing a (possibly learned) rewa…
Shift-Curvature, SGD, and Generalization
Arwen V. Bradley, Carlos Alberto Gomez-Uribe, Manish Reddy Vuyyuru
A longstanding debate surrounds the related hypotheses that low-curvature minima generalize better, and that SGD discourages curvature. We offer a more complete and nuanced view in…
Cinematic-L1 Video Stabilization with a Log-Homography Model
Arwen Bradley, Jason Klivington, Joseph Triscari +1
We present a method for stabilizing handheld video that simulates the camera motions cinematographers achieve with equipment like tripods, dollies, and Steadicams. We formulate a c…