14 citations · 18 across the 10 of their papers we have counts for
4 papers · 1 filter
On the Limits of Latent Reuse in Diffusion Models
Yifeng Yu, Lu Yu
Diffusion models are often trained in low-dimensional latent spaces, which are then reused for related but shifted datasets. In this work, we study when such latent reuse remains r…
Kinetic Langevin Splitting Schemes for Constrained Sampling
Neil K. Chada, Lu Yu
Constrained sampling is an important and challenging task in computational statistics, concerned with generating samples from a distribution under certain constraints. There are nu…
Know What You Know: Metacognitive Entropy Calibration for Verifiable RL Reasoning
Qiannian Zhao, Chen Yang, Jinhao Jing +5
Large reasoning models (LRMs) have emerged as a powerful paradigm for solving complex real-world tasks. In practice, these models are predominantly trained via Reinforcement Learni…
Diffusion Models with Heavy-Tailed Targets: Score Estimation and Sampling Guarantees
Yifeng Yu, Lu Yu
Score-based diffusion models have become a powerful framework for generative modeling, with score estimation as a central statistical bottleneck. Existing guarantees for score esti…