I am currently a Postdoc Researcher at Princeton University, fortunately working with Prof. Mengdi Wang. My research focuses on advanced generative models, including both methodological development and real-world applications. I received my Ph.D. degree from Peking University, supervised by Prof. Bin Cui and Prof. Luxia Zhang. I was also fortunate to collaborate with Yang Song, Shuicheng Yan, Ming-Hsuan Yang, Bernard Ghanem, Stefano Ermon, and Jure Leskovec. I am opening to academic and industrial research opportunities. Please feel free to reach out for potential collaborations or discussions.
Email | WeChat | Personal Github | Group Github | Google Scholar | Twitter | HuggingFace

We have opening positions for PhDs, Masters and Research Interns (Princeton University and Peking University, available in-person and remote). Also, I am in charge of a reasearch team and have led a series of works on Diffusion Models and LLMs, including RPG-DiffusionMaster, MMaDA, Diffusion-Survey, Buffer of Thoughts, ReasonFlux/PRM/Coder, VideoTetris, Consistency Flow Matching, IterComp, Rectified Diffusion.

My research has been sponsored by leading companies including ByteDance, Ant Group, and Xiaomi. I welcome opportunities for collaboration and partnership discussions with additional enterprises and organizations.

Research Summary

My goal is to build powerful generative models capable of understanding, generating and reasoning with high-dimensional data across diverse modalities. I currently focus on developing advanced generative models, including their training methodologies, architecture design, alignment, inference efficiency and applications.

Generative Model Foundations

• Diffusion Model Foundations: RPG, MMaDA, ContextDiff, Consistency Flow Matching, Diffusion-Sharpening, Rectified Diffusion, ConPreDiff, SADM
• Language Model Innovations: Buffer of Thought, MMaDA, SuperCorrect, HermesFlow, ReasonFlux, ReasonFlux-Coder, ReasonFlux-PRM
• Large-Scale Reinforcement Learning: MMaDA, ReasonFlux-Coder, ReasonFlux-PRM
• Intelligent Agent Systems: Alita, AgentDistill, ScoreFlow, Multi-Actor Collaboration

Generative Applications

• Multimodal Content Generation (spanning image, 3D, and 4D synthesis): IterComp, VideoTetris, ScoreLiDAR, IPDreamer, EditWorld, Trans4D, WideRange4D
• AI for Scientific Discovery: IPDiff, IRDiff, BindDM, RL for Scientific Reasoning

Book Publication

“Diffusion Model: Theory, Application, and Code Practice of Generative AI Models”
Published by Electronics Industry Press (电子工业出版社), 2023
Purchase Link | Selected as Annual Outstanding Author

What's New

• 3 papers about LLMs and Agents are accepted by EMNLP 2025.
• 2 papers about diffusion are accepted by ACM MM 2025, including Inversion-DPO and EditWorld.
• I was selected as a finalist for the 2025 WAIC Yunfan Award.
• I was invited to participate in a roundtable forum at WAIC 2025, hosted by Prof. Dahua Lin.
• 2 papers about agent and diffusion are accepted by ICCV 2025, including one Oral Paper.
• 1 paper about LLMs is accepted by ACL 2025, including Multi-Actor Collaboration.
• I was invited as an Area Chair at NeurIPS 2025.
• 6 papers about LLMs and Diffusion Models are accepted by ICLR 2025, including SuperCorrect, Rectified Diffusion, IterComp and IPDreamer.
• I was invited to give a talk at Princeton AI Lab, hosted by Prof. Mengdi Wang.
• 5 papers about Diffusion Models and LLMs are accepted by NeurIPS 2024, including one Spotlight paper.
• 2 papers about Diffusion Models and AI for Science are accepted by ICML 2024.
• 1 paper about general/molecular graph diffusion is accepted by TKDE 2024.
• 1 paper about improved training algorithm of Diffusion Transformers (DiT), DDPMs and Score SDEs is accepted by CVPR 2024.
• 3 papers about Diffusion Models, GNN, AI for Science are accepted by ICLR 2024.
• 1 paper about molecular diffusion models is accepted by AAAI 2024.
• 1 paper about diffusion model survey collaborating with OpenAI is accepted by ACM Computing Surveys.
• 1 paper about diffusion models is accepted by NeurIPS 2023.
• I publish a book about Diffusion Models.
• 1 paper is accepted by TNNLS 2023.
• 1 paper is accepted by TKDE 2023.
• 2 papers are accepted as ICML 2022 Spotlight.
• 1 paper is accepted by CVPR 2020.

Selected Publications

For a complete list, see my Google Scholar profile

Recent Highlighted Work

• Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models
  Ling Yang, Zhaochen Yu, Tianjun Zhang, Shiyi Cao, Minkai Xu, Wentao Zhang, Joseph E Gonzalez, Bin Cui
  NeurIPS 2024 spotlight paper | code | tweet

• Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs
  Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui
  ICML 2024 paper | code | tweet

• MMaDA: Multimodal Large Diffusion Language Models
  Ling Yang, Ye Tian, Bowen Li, Xinchen Zhang, Ke Shen, Yunhai Tong, Mengdi Wang
  paper | code | tweet

• Distilling Diffusion Models to Efficient 3D LiDAR Scene Completion
  Shengyuan Zhang, An Zhao, Ling Yang, Zejian Li, Chenye Meng, Haoran Xu, Tianrun Chen, AnYang Wei, Perry Pengyun GU, Lingyun Sun
  ICCV 2025 oral paper | code

• ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates
  Ling Yang, Zhaochen Yu, Bin Cui, Mengdi Wang
  paper | code | tweet

• ReasonFlux-PRM: Trajectory-Aware PRMs for Long Chain-of-Thought Reasoning in LLMs
  Jiaru Zou, Ling Yang*, Jingwen Gu, Jiahao Qiu, Ke Shen, Jingrui He, Mengdi Wang
  paper | code | tweet

• SuperCorrect: Advancing Small LLM Reasoning with Thought Template Distillation and Self-Correction.
  Ling Yang, Zhaochen Yu, Tianjun Zhang, Minkai Xu, Joseph E. Gonzalez, Bin CUI, Shuicheng YAN
  ICLR 2025 paper | code

• Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning
  Yinjie Wang, Ling Yang*, Ye Tian, Ke Shen, Mengdi Wang
  paper | code | tweet

Core Contributions to Diffusion Models

• IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation
  Xinchen Zhang*, Ling Yang*, Guohao Li, Yaqi Cai, Jiake Xie, Yong Tang, Yujiu Yang, Mengdi Wang, Bin Cui
  ICLR 2025 paper | code | tweet

• Rectified Diffusion: Straightness Is Not Your Need in Rectified Flow
  Fu-Yun Wang, Ling Yang, Zhaoyang Huang, Mengdi Wang, Hongsheng Li
  ICLR 2025 paper | code

• Consistency Flow Matching: Defining Straight Flows with Velocity Consistency
  Ling Yang, Zixiang Zhang, Zhilong Zhang, Xingchao Liu, Minkai Xu, Wentao Zhang, Chenlin Meng, Stefano Ermon, Bin Cui
  paper | code | tweet

• Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing
  Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin CUI
  ICLR 2024 paper | code

• Structure-Guided Adversarial Training of Diffusion Models
  Ling Yang, Haotian Qian, Zhilong Zhang, Jingwei Liu, Bin CUI
  CVPR 2024 paper

• Improving Diffusion-Based Image Synthesis with Context Prediction
  Ling Yang, Jingwei Liu, Shenda Hong, Zhilong Zhang, Zhilin Huang, Zheming Cai, Wentao Zhang, Bin CUI
  NeurIPS 2024 paper

• Diffusion Models: A Comprehensive Survey of Methods and Applications
  Ling Yang, Zhilong Zhang, Yang Song (OpenAI), Shenda Hong, Runsheng Xu, Yue Zhao, Wentao Zhang, Bin CUI, Ming-Hsuan Yang
  ACM Computing Surveys 2023 paper | code

• VideoTetris: Towards Compositional Text-to-Video Generation
  Ye Tian*, Ling Yang*, Haotian Yang, Yuan Gao, Yufan Deng, Jingmin Chen, Xintao Wang, Zhaochen Yu, Xin Tao, Pengfei Wan, Di Zhang, Bin Cui
  NeurIPS 2024 paper | code | tweet

Additional Selected Publications

• VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
  Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec
  ICLR 2024 paper | code

• Dpgn: Distribution propagation graph network for few-shot learning
  Ling Yang, Liangliang Li, Zilun Zhang, Xinyu Zhou, Erjin Zhou, Yu Liu
  CVPR 2020 paper | code

• Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion
  Ling Yang, Shenda Hong
  ICML 2022 spotlight paper

Teaching & Mentoring

Zhaochen Yu (Incoming Ph.D. student at National University of Singapore)

Xinchen Zhang (Master student at Tsinghua University)

Ye Tian (Ph.D. student at Peking University)

Zhilin Huang (Ph.D. student at Tsinghua University)

Zhilong Zhang (Ph.D. student at Tsinghua University)

Yinjie Wang (Ph.D. student at The University of Chicago)

Jiaru Zou (Master student at University of Illinois Urbana-Champaign)

Jiacheng Guo (Ph.D. student at Princeton University)

Academic Services

• Area Chair:
  • NeurIPS 2025
• Program Committee or Reviewer:
  • ICML 2025, ICLR 2025, CVPR 2025, ICCV 2025, AAAI 2025
  • SIGGRAPH 2024, ICML 2024, ICLR 2024, NeurIPS 2024, CVPR 2024, AAAI 2024
  • ICML 2023, ICLR 2023, NeurIPS 2023, CVPR 2023, AAAI 2023
  • ICML 2022, ICLR 2022, NeurIPS 2022
• Journal Reviewer
  • ACM Computing Surveys (CSUR)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • Pattern Recognition (PR)

Honors & Awards

Academic Recognition

• 2025 WAIC Yunfan Award Finalist, 2025
• Outstanding Graduate, Peking University Ph.D., 2025
• KAUST Rising Stars in AI Symposium (24 selected worldwide), 2025
• WAIC AI Elite Forum (20 selected worldwide), 2024
• VALSE Distinguished Student Forum (8 selected in China), 2024
• Baidu Scholarship Nominee (20 selected worldwide), 2023

University Honors

• National Scholarship for Ph.D. students (Top 1% at PKU), 2022
• Exceptional Award for Academic Innovation (Top 1% at PKU), 2022
• First-class Academic Scholarship, 2018-2020

Industry Recognition

• TechBeat Influencers List (20 selected in China), 2023 & 2024
• Outstanding Author, Electronics Industry Press, 2023