Short Bio

I am a final year PhD student at Hong Kong University of Science and Technology, supervised by Prof. Jing Tang. My research interests are developing Efficient Generative Models, and building Few-Step Text-to-Image/Video Diffusion Models for high-quality and real-time generation. I am also interested in Graph Neural Networks.

Academic Service: reviewer for ICML, ICLR, NeurIPS, CVPR, ICCV, etc.

If you’re interested in collaborating or exploring potential research opportunities, please don’t hesitate to reach out (带带哥们).

News

[03/2025] We release TDM, unifying the trajectory distillation and distribution. TDM can distill pre-trained DMs to a few-step generator with better performance with extremely low cost. In particular, TDM distills PixArt to a 4-step generator with 2 A800 hours and outperforms teacher regarding real user preference.
[03/2025] We release JDM, a method can add additional control unkown to teacher to one-step student. Moreover, JDM decouples the condition learning and fidelity learning, enabling improved usage of classifier-free guidance (CFG) and seamless integration of human feedback learning (HFL).
[01/2025] Two first/co-first author papers accepted to ICLR 2025.

Publications

(^* denotes co-first authors)

Learning Few-Step Diffusion Models by Trajectory Distribution Matching
Yihong Luo, Tianyang Hu, Jiacheng Sun, Yujun Cai, Jing Tang
Preprint, 2025
[Paper]

Adding Additional Control to One-Step Diffusion with Joint Distribution Matching
Yihong Luo, Tianyang Hu, Yifan Song, Jiacheng Sun, Zhenguo Li, Jing Tang
Preprint, 2025
[Paper]

You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs
Yihong Luo, Xiaolong Chen, Xinghua Qu, Tianyang Hu, Jing Tang
ICLR 2025
[Paper]

Decoupled Graph Energy-based Model for Node Out-of-Distribution Detection on Heterophilic Graphs
Yuhan Chen^*, Yihong Luo^*, Yifan Song, Pengwen Dai, Jing Tang, and Xiaochun Cao
ICLR 2025
[Paper]

Energy-Calibrated VAE with Test Time Free Lunch
Yihong Luo, Siya Qiu, Xingjian Tao, Yujun Cai, Jing Tang
ECCV 2024
[Paper]

Fast Graph Sharpness-Aware Minimization for Enhancing and Accelerating Few-Shot Node Classification
Yihong Luo^*, Yuhan Chen^*, Siya Qiu, Yiwei Wang, Chen Zhang, Yan Zhou, Xiaochun Cao, Jing Tang
NeurIPS 2024
[Paper]

TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed
Shian Du^*, Yihong Luo^*, Wei Chen^*, Jian Xu, Delu Zeng
CVPR 2022
[Paper]

LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity
Yuhan Chen^*, Yihong Luo^*, Jing Tang, Liang Yang, Siya Qiu, Chuan Wang, Xiaochun Cao
IJCAI 2023
[Paper]

SteadySeg: Improving Maritime Trajectory Staging by Steadiness Recognition
Siya Qiu, Yihong Luo, Qiong Luo, Jing Tang
Ocean Engineering (JCR Q1)
[Paper]

Education

2022 — 2025/12 (expected): Ph.D. in Data Science and Analytics, Hong Kong University of Science and Technology
2016 — 2020: B.Sc. in Information Management and Information System, South China University of Technology

Experience

Diffusion Distillation Research Intern, Huawei Noah's Ark Lab
Research Assistant, Hong Kong University of Science and Technology