4 citations · 5 across the 20 of their papers we have counts for
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One-Step Generative Modeling via Wasserstein Gradient Flows
Jiaqi Han, Puheng Li, Qiushan Guo +3
Diffusion models and flow-based methods have shown impressive generative capability, especially for images, but their sampling is expensive because it requires many iterative updat…
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer
Wenda Chu, Bingliang Zhang, Jiaqi Han +4
Autoregressive image modeling relies on visual tokenizers to compress images into compact latent representations. We design an end-to-end training pipeline that jointly optimizes r…
Beyond Pairwise Preferences: Listwise Reward-Aware Alignment for Diffusion Models
Austin Wang, Jiaqi Han, Stefano Ermon +1
Preference optimization has emerged as an efficient alternative to online reinforcement learning from human feedback (RLHF) for aligning text-to-image diffusion models. However, ex…
Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics
Aniketh Iyengar, Jiaqi Han, Pengwei Sun +3
Generating molecular dynamics (MD) trajectories using deep generative models has attracted increasing attention, yet remains inherently challenging due to the limited availability…
Adaptive Spectral Feature Forecasting for Diffusion Sampling Acceleration
Jiaqi Han, Juntong Shi, Puheng Li +3
Diffusion models have become the dominant tool for high-fidelity image and video generation, yet are critically bottlenecked by their inference speed due to the numerous iterative…