collaborators

5 papers

cs.LG2026

Stochastic Heavy Ball with Polyak Step Size and Armijo Line Search: A General Convergence Analysis

Jiawei Zhang, Qitan Shi, Yuantao Gu

Polyak step size (PS) and Armijo line search (ALS) have received increasing attention in stochastic optimization, with encouraging empirical performance and theoretical guarantees.…

cs.CV2026

Quantization-Aware Kalman Estimation for Diffusion Sampling

Qitan Shi, Cheng Jin, Jiawei Zhang +1

Quantization offers a practical path to deploying diffusion models with reduced memory and computation, but aggressive compression can cause quantized outputs to deviate substantia…

cs.CV2026

Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling

Qitan Shi, Cheng Jin, Ziyuan Liu +1

Few-step distilled diffusion models generate high-quality images quickly, but often lose per-prompt diversity, producing near-identical samples across random seeds. Optimizing the…

cs.LG2025

Stage-wise Dynamics of Classifier-Free Guidance in Diffusion Models

Cheng Jin, Qitan Shi, Yuantao Gu

Classifier-Free Guidance (CFG) is widely used to improve conditional fidelity in diffusion models, but its impact on sampling dynamics remains poorly understood. Prior studies, oft…

cs.LG2025

ReTrack: Data Unlearning in Diffusion Models through Redirecting the Denoising Trajectory

Qitan Shi, Cheng Jin, Jiawei Zhang +1

Diffusion models excel at generating high-quality, diverse images but suffer from training data memorization, raising critical privacy and safety concerns. Data unlearning has emer…