BSOGCN: Brain Storm Optimization Graph Convolutional Networks Based Heterogeneous Information Networks Embedding. - Liang Qu; Huaisheng Zhu; Yuhui Shi (CEC, 2020)

Continuous-Time Link Prediction via Temporal Dependent Graph Neural Network. - Liang Qu; Huaisheng Zhu; Qiqi Duan; Yuhui Shi 001 (WWW, 2020)

ImGAGN: Imbalanced Network Embedding via Generative Adversarial Graph Networks. - Liang Qu; Huaisheng Zhu; Ruiqi Zheng; Yuhui Shi 001; Hongzhi Yin (KDD, 2021)

Learning Fair Models without Sensitive Attributes: A Generative Approach. - Huaisheng Zhu; Suhang Wang (CoRR, 2022)

Simple and Asymmetric Graph Contrastive Learning without Augmentations. - Teng Xiao; Huaisheng Zhu; Zhengyu Chen 001; Suhang Wang (NeurIPS, 2023)

You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. - Huaisheng Zhu; Xianfeng Tang; Tianxiang Zhao 001; Suhang Wang (PAKDD (2), 2023)

Self-Explainable Graph Neural Networks for Link Prediction. - Huaisheng Zhu; Dongsheng Luo; Xianfeng Tang; Junjie Xu; Hui Liu 031; Suhang Wang (CoRR, 2023)

Fairness-aware Message Passing for Graph Neural Networks. - Huaisheng Zhu; Guoji Fu; Zhimeng Guo; Zhiwei Zhang; Teng Xiao; Suhang Wang (CoRR, 2023)

On the Safety of Open-Sourced Large Language Models: Does Alignment Really Prevent Them From Being Misused? - Hangfan Zhang; Zhimeng Guo; Huaisheng Zhu; Bochuan Cao; Lu Lin 001; Jinyuan Jia 001; Jinghui Chen; Dinghao Wu (CoRR, 2023)

Learning fair models without sensitive attributes: A generative approach. - Huaisheng Zhu; Enyan Dai; Hui Liu 031; Suhang Wang (Neurocomputing, 2023)

Jailbreak Open-Sourced Large Language Models via Enforced Decoding. - Hangfan Zhang; Zhimeng Guo; Huaisheng Zhu; Bochuan Cao; Lu Lin 001; Jinyuan Jia 001; Jinghui Chen; Dinghao Wu (ACL (1), 2024)

AmGNN: A Framework for Adaptive Processing of Inter-layer Information in Multi-layer Graph. - Huaisheng Zhu; Zongyu Wu 001; Tianxiang Zhao 001; Suhang Wang (ASONAM (1), 2024)

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules. - Teng Xiao; Chao Cui; Huaisheng Zhu; Vasant G. Honavar (BIBM, 2024)

How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective. - Teng Xiao; Mingxiao Li 004; Yige Yuan; Huaisheng Zhu; Chao Cui; Vasant G. Honavar (EMNLP, 2024)

Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. - Teng Xiao; Huaisheng Zhu; Zhiwei Zhang; Zhimeng Guo; Charu C. Aggarwal; Suhang Wang; Vasant G. Honavar (ICML, 2024)

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment. - Teng Xiao; Yige Yuan; Huaisheng Zhu; Mingxiao Li 004; Vasant G. Honavar (NeurIPS, 2024)

3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs. - Huaisheng Zhu; Teng Xiao; Vasant G. Honavar (CoRR, 2024)

MolBind: Multimodal Alignment of Language, Molecules, and Proteins. - Teng Xiao; Chao Cui; Huaisheng Zhu; Vasant G. Honavar (CoRR, 2024)

Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements. - Shijie Zhou; Huaisheng Zhu; Rohan Sharma; Ruiyi Zhang; Kaiyi Ji; Changyou Chen (CoRR, 2024)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. - Enyan Dai; Tianxiang Zhao 001; Huaisheng Zhu; Junjie Xu; Zhimeng Guo; Hui Liu 031; Jiliang Tang; Suhang Wang (Mach. Intell. Res., 2024)

DSPO: Direct Score Preference Optimization for Diffusion Model Alignment. - Huaisheng Zhu; Teng Xiao; Vasant G. Honavar (ICLR, 2025)

SmGNN: Link Prediction in Sparse Layers of Multi-layer Graphs. - Huaisheng Zhu; Tianxiang Zhao 001; Zongyu Wu 001; Suhang Wang (WebSci, 2025)

Multimodal LLMs as Customized Reward Models for Text-to-Image Generation. - Shijie Zhou; Ruiyi Zhang 002; Huaisheng Zhu; Branislav Kveton; Yufan Zhou 001; Jiuxiang Gu; Jian Chen 043; Changyou Chen (CoRR, 2025)

Optimizing Token Choice for Code Watermarking: A RL Approach. - Zhimeng Guo; Huaisheng Zhu; Siyuan Xu; Hangfan Zhang; Teng Xiao; Minhao Cheng (CoRR, 2025)