18 citations · 27 across the 15 of their papers we have counts for
5 papers · 1 filter
Controllably Efficient Language Models
Jatin Prakash, Aahlad Puli, Rajesh Ranganath
The substantial inference costs of attention in transformers motivated the development of efficient sequence mixers: namely sparse and sliding window attention, convolutions and li…
KL-Regularized Reinforcement Learning is Designed to Mode Collapse
Anthony GX-Chen, Jatin Prakash, Jeff Guo +2
It is commonly believed that optimizing the reverse KL divergence results in "mode seeking", while optimizing forward KL results in "mass covering", with the latter being preferred…
Three Forms of Stochastic Injection for Improved Distribution-to-Distribution Generative Modeling
Shiye Su, Yuhui Zhang, Linqi Zhou +2
Modeling transformations between arbitrary data distributions is a fundamental scientific challenge, arising in applications like drug discovery and evolutionary simulation. While…
Rethinking Reasoning with MDLMs: Early Exits, Post-hoc Reasoning, and Beyond
Zachary Horvitz, Raghav Singhal, Hao Zou +4
The reasoning paradigm, where language models reason before answering, has enabled breakthroughs on tasks such as mathematical problem-solving. While current tooling for reasoning…
A General Framework for Inference-time Scaling and Steering of Diffusion Models
Raghav Singhal, Zachary Horvitz, Ryan Teehan +4
Diffusion models produce impressive results in modalities ranging from images and video to protein design and text. However, generating samples with user-specified properties remai…