Ling Yang is currently a third-year Ph.D. student at Peking University, advised by Bin Cui, Luxia Zhang and Ming-Hsuan Yang. His research interests are Diffusion Models, Multimodal Learning, and AI for Science. He worked with Yang Song, Bernard Ghanem, Stefano Ermon and Jure Leskovec. He now serves as a program committee member or reviewer for international conferences and journals including TPAMI, ICML, ICLR, NeurIPS, CVPR, KDD, AAAI. Feel free to email me for potential collaborations or discussions. Alternatively, my WeChat ID: jifengjianhao_yl.

Research Interests

• Diffusion Models (NeurIPS 2023, ACM Computing Surveys 2023, ICLR 2024, CVPR 2024)
• Representation Learning (CVPR 2020, ICML 2022, KDE 2023, TNNLS 2023)
• AI for Science (AAAI 2024, ICLR 2024)

What's New

• One paper about general/molecular graph diffusion is accepted by TKDE 2024.
• One paper about improved training algorithm of Diffusion Transformers (DiT), DDPMs and Score SDEs is accepted by CVPR 2024.
• Release our SOTA LLM-controlled diffusion model, RPG-DiffusionMaster.
• Three papers about Diffusion Models, GNN, AI for Science are accepted by ICLR 2024.
• Our paper about protein-aware 3D molecular diffusion models is accepted by AAAI 2024.
• Our survey about Diffusion Models is accepted by ACM Computing Surveys 2023.
• One paper about text-to-image diffusion is accepted by NeurIPS 2023.
• I publish a book about Diffusion Models.
• One paper is accepted by TNNLS 2023.
• One paper is accepted by TKDE 2023.
• Two papers are accepted by ICML 2022.
• One paper is accepted by CVPR 2020.

Publications

[SOTA Diffusion] Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs

Author List: Ling Yang, Zhaochen Yu, Chenlin Meng, Minkai Xu, Stefano Ermon, Bin Cui

[CVPR 2024] Structure-Guided Adversarial Training of Diffusion Models

Author List: Ling Yang, Haotian Qian, Zhilong Zhang, Jingwei Liu, Bin Cui

[ICLR 2024] Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing

Author List: Ling Yang, Zhilong Zhang, Zhaochen Yu, Jingwei Liu, Minkai Xu, Stefano Ermon, Bin Cui

[ICLR 2024] Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models

Author List: Zhilin Huang*, Ling Yang*, Xiangxin Zhou, Zhilong Zhang, Wentao Zhang, Xiawu Zheng, Jie Chen, Yu Wang, Bin Cui, Wenming Yang

[ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs

Author List: Ling Yang, Ye Tian, Minkai Xu, Zhongyi Liu, Shenda Hong, Wei Qu, Wentao Zhang, Bin Cui, Muhan Zhang, Jure Leskovec

[ACM Computing Surveys 2023] Diffusion Models: A Comprehensive Survey of Methods and Applications

Author List: Ling Yang, Zhilong Zhang, Yang Song, Shenda Hong, Runsheng Xu, Yue Zhao, Yingxia Shao, Wentao Zhang, Bin Cui, Ming-Hsuan Yang

[NeurIPS 2023] Improving Diffusion-Based Image Synthesis with Context Prediction

Author List: Ling Yang, Jingwei Liu, Shenda Hong, Zhilong Zhang, Zhilin Huang, Zheming Cai, Wentao Zhang, Bin Cui

[AAAI 2024] Binding-Adaptive Diffusion Models for Structure-Based Drug Design

Author List: Zhilin Huang*, Ling Yang*, Zaixi Zhang, Xiangxin Zhou, Yu Bao, Xiawu Zheng, Yuwei Yang, Yu Wang, Wenming Yang

[TKDE 2024] Graphusion: Latent Diffusion for Graph Generation

Author List: Ling Yang, Zhilin Huang, Zhilong Zhang, Zhongyi Liu, Shenda Hong, Wentao Zhang, Wenming Yang, Bin Cui, Luxia Zhang

[ICML 2022] Omni-granular ego-semantic propagation for self-supervised graph representation learning

Author List: Ling Yang, Shenda Hong

[Arxiv 2022] Diffusion-Based Scene Graph to Image Generation with Masked Contrastive Pre-Training

Author List: Ling Yang, Zhilin Huang, Yang Song, Shenda Hong, Guohao Li, Wentao Zhang, Bin Cui, Bernard Ghanem, Ming-Hsuan Yang

[ICML 2022] Unsupervised time-series representation learning with iterative bilinear temporal-spectral fusion

Author List: Ling Yang, Shenda Hong

[CVPR 2020] Dpgn: Distribution propagation graph network for few-shot learning

Author List: Ling Yang, Liangliang Li, Zilun Zhang, Xinyu Zhou, Erjin Zhou, Yu Liu

[TKDE 2023] Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization

Author List: Ling Yang, Jiayi Zheng, Heyuan Wang, Zhongyi Liu, Zhilin Huang, Shenda Hong, Wentao Zhang, Bin Cui

[TNNLS 2023] Self-Supervised Time Series Representation Learning via Cross Reconstruction Transformer

Author List: Wenrui Zhang*, Ling Yang*, Shijia Geng, Shenda Hong

Awards

• Baidu Scholarship Nominee (20 People in the World), 2023
• National Scholarship for Ph.D student (Top 1% in PKU), 2022.
• Exceptional Award for Academic Innovation for Ph.D student (Top 1% in PKU), 2022.
• First-class Academic Scholarship, 2018, 2019, 2020.