1 citations · 1 across the 4 of their papers we have counts for
4 papers
Do Language Models Need Sleep? Offline Recurrence for Improved Online Inference
Sangyun Lee, Sean McLeish, Tom Goldstein +1
Transformer-based large language models are increasingly used for long-horizon tasks; however, their attention mechanism scales poorly with context length. To handle this, we study…
BaNEL: Exploration Posteriors for Generative Modeling Using Only Negative Rewards
Sangyun Lee, Brandon Amos, Giulia Fanti
Today's generative models thrive with large amounts of supervised data and informative reward functions characterizing the quality of the generation. They work under the assumption…
Truncated Consistency Models
Sangyun Lee, Yilun Xu, Tomas Geffner +4
Consistency models have recently been introduced to accelerate sampling from diffusion models by directly predicting the solution (i.e., data) of the probability flow ODE (PF ODE)…
Improving the Training of Rectified Flows
Sangyun Lee, Zinan Lin, Giulia Fanti
Diffusion models have shown great promise for image and video generation, but sampling from state-of-the-art models requires expensive numerical integration of a generative ODE. On…