About Me

I am a research scientist specializing in generative AI at the Institute of Artificial Intelligence (TeleAI), China Telecom. I received my Ph.D. from the University of Technology Sydney in 2024, advised by Dr. Linchao Zhu and Prof. Yi Yang.

I received a Master's degree from Xi'an Jiaotong University in 2020 and was a member of the SMILES LAB, advised by Prof. Xueming Qian and Prof. Li Zhu.

My research focuses on generative AI with an emphasis on post-training, alignment, and structured world understanding built on large-scale data-driven foundations. I am interested in how models develop coherent internal representations, respect real-world structure, and refine their behavior through principled signals—including physical priors, aesthetic objectives, and human-aligned guidance. The aim is to move toward generative systems that remain grounded in data while becoming more reliable, structurally consistent, and capable of progressive self-improvement.

More broadly, I am interested in learning frameworks where generative models improve through simulation, interaction, and self-directed refinement rather than static supervision alone. This includes the use of world models, controlled training environments, and structured feedback to provide richer learning signals—enabling models to test hypotheses, adapt, and grow through experience. The long-term goal is to support a trajectory toward generative intelligence that is grounded, aligned, and continuously advancing through both data and experience.

Work Experience

• Jul 2021 - Dec 2021, Alibaba DAMO Academy
• Research intern working on virtual human synthesis.
• Jul 2020 - Jul 2021, Baidu Research
• Research intern working on visual knowledge embedding, object recognition, and multi-modal representation.
• Mar 2020 - Jun 2020, JD AI Research
• Research intern working on product recognition.
• Aug 2018 - Jun 2019, JD AI Research
• Research intern working on visual-language representation learning.

Selected Honors

• First place in AliProducts Challenge @ CVPR 2020 the RetailVision workshop.
• First place in iMat Product Competition @ CVPR 2019 FGVC6 workshop.
• First place in in Fieldguide Challenge: Moths & Butterflies @ CVPR 2019 FGVC6 workshop.
• Second place in iFood Competition @ CVPR 2019 FGVC6 workshop.
• Second place in iMet2020 Fine-grained Attributes Classification Competition @ CVPR 2020 FGVC7 workshop.
• Kaggle Silver Medal in Deepfake Detection Challenge 2020.

Important Preprints

Seeing What Matters: Visual Preference Policy Optimization for Visual Generation
Ziqi Ni*, Yuanzhi Liang, Rui Li, Yi Zhou, Haibing Huang, Chi Zhang, Xuelong Li.
Arxiv, 2025

Growing with the Generator: Self-paced GRPO for Video Generation
Rui Li*, Yuanzhi Liang, Ziqi Ni, Haibing Huang, Chi Zhang, Xuelong Li.
Arxiv, 2025

Learning What to Trust: Bayesian Prior-Guided Optimization for Visual Generation
Ruiying Liu*, Yuanzhi Liang, Haibin Huang, Tianshu Yu, Chi Zhang.
Arxiv, 2025

Free3D: 3D Human Motion Emerges from Single-View 2D Supervision
Sheng Liu*, Yuanzhi Liang, Sidan Du.
Arxiv, 2025

VAST 1.0: A Unified Framework for Controllable and Consistent Video Generation.
Chi Zhang, Yuanzhi Liang, Xi Qiu, Fangqiu Yi, Xuelong Li.
Arxiv, 2024

Selected Publications

Uni-Inter: Unifying 3D Human Motion Synthesis Across Diverse Interaction Contexts
Sheng Liu*, Yuanzhi Liang, Jiepeng Wang, Sidan Du, Chi Zhang, Xuelong Li.
Accepted by SIGGRAPH Asia 2025

Intersyn: Interleaved learning for dynamic motion synthesis in the wild
Yiyi Ma*, Yuanzhi Liang, Xiu Li, Chi Zhang, Xuelong Li.
Accepted by ICCV 2025

MAAL: Multimodality-Aware Autoencoder-based Affordance Learning for 3D Articulated Objects.
Yuanzhi Liang, Xiaohan Wang, Linchao Zhu, Yi Yang.
Accepted by ICCV 2023

A Simple Episodic Linear Probe Improves Visual Recognition in the Wild.
Yuanzhi Liang, Linchao Zhu, Xiaohan Wang, Yi Yang.
Accepted by CVPR 2022 (Score 1/2/2)

SEEG: Semantic Energized Co-speech Gesture Generation.
Yuanzhi Liang, Qianyu Feng, Linchao Zhu, Li Hu, Pan Pan, Yi Yang.
Accepted by CVPR 2022

VrR-VG: Refocusing Visually-Relevant Relationships.
Yuanzhi Liang, Yalong Bai, Wei Zhang, Xueming Qian, Li Zhu, Tao Mei.
Accepted by ICCV 2019

IcoCap: Improving Video Captioning by Compounding Images.
Yuanzhi Liang, Linchao Zhu, Xiaohan Wang, Yi Yang.
Accepted by TMM 2023

Penalizing the Hard Example But Not Too Much: A Strong Baseline for Fine-Grained Visual Classification.
Yuanzhi Liang, Linchao Zhu, Xiaohan Wang, Yi Yang.
Accepted by TNNLS 2022

Towards Better Railway Service: Passengers Counting in Railway Compartment.
Yuanzhi Liang, Zhu Li, Xueming Qian.
Accepted by TCSVT 2020

Freelong: Training-free long video generation with spectralblend temporal attention.
Yu Lu, Yuanzhi Liang, Linchao Zhu, Yi Yang.
Accepted by NeurIPS 2024

Removing Raindrops and Rain Streaks in One Go.
Ruijie Quan, Xin Yu, Yuanzhi Liang, Yi Yang.
Accepted by CVPR 2021

Food and Ingredient Joint Learning for Fine-Grained Recognition.
Chengxu Liu, Yuanzhi Liang, Yao Xue, Xueming Qian, Jianlong Fu.
Accepted by TCSVT 2020

Note *: interns that I mentored.

Journal Reviewer

Reviewer for TPAMI and TIP.

Conference Reviewer / Program Committee Member

Reviewer for ICCV, CVPR, ICLR, NeurIPS, ECCV, MM, AAAI, IJCAI, ICME, and CAAI.

Others

Member of MNBVC (Massive Never-ending BT Vast Chinese corpus).