Huaisheng Zhu

According to our database, Huaisheng Zhu authored at least 26 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Simple Denoising Diffusion Language Models.

Huaisheng Zhu, Zhengyu Chen, Shijie Zhou, Zhihui Xie, Yige Yuan, Zhimeng Guo, Siyuan Xu, Hangfan Zhang, Vasant G. Honavar, Teng Xiao

CoRR, October, 2025

The Path of Self-Evolving Large Language Models: Achieving Data-Efficient Learning via Intrinsic Feedback.

Hangfan Zhang, Siyuan Xu, Zhimeng Guo, Huaisheng Zhu, Shicheng Liu, Xinrun Wang, Qiaosheng Zhang, Yang Chen, Peng Ye, Lei Bai, Shuyue Hu

CoRR, October, 2025

Optimizing Token Choice for Code Watermarking: A RL Approach.

Zhimeng Guo, Huaisheng Zhu, Siyuan Xu, Hangfan Zhang, Teng Xiao, Minhao Cheng

CoRR, August, 2025

Multimodal LLMs as Customized Reward Models for Text-to-Image Generation.

Shijie Zhou, Ruiyi Zhang, Huaisheng Zhu, Branislav Kveton, Yufan Zhou, Jiuxiang Gu, Jian Chen, Changyou Chen

CoRR, July, 2025

SmGNN: Link Prediction in Sparse Layers of Multi-layer Graphs.

Huaisheng Zhu, Tianxiang Zhao, Zongyu Wu, Suhang Wang

Proceedings of the 17th ACM Web Science Conference 2025, 2025

DSPO: Direct Score Preference Optimization for Diffusion Model Alignment.

Huaisheng Zhu, Teng Xiao, Vasant G. Honavar

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability.

Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang

Mach. Intell. Res., December, 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

MolBind: Multimodal Alignment of Language, Molecules, and Proteins.

Teng Xiao, Chao Cui, Huaisheng Zhu, Vasant G. Honavar

CoRR, 2024

3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs.

Huaisheng Zhu, Teng Xiao, Vasant G. Honavar

CoRR, 2024

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment.

Teng Xiao, Yige Yuan, Huaisheng Zhu, Mingxiao Li, Vasant G. Honavar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective.

Teng Xiao, Mingxiao Li, Yige Yuan, Huaisheng Zhu, Chao Cui, Vasant G. Honavar

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules.

Teng Xiao, Chao Cui, Huaisheng Zhu, Vasant G. Honavar

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

AmGNN: A Framework for Adaptive Processing of Inter-layer Information in Multi-layer Graph.

Huaisheng Zhu, Zongyu Wu, Tianxiang Zhao, Suhang Wang

Proceedings of the Social Networks Analysis and Mining - 16th International Conference, 2024

Jailbreak Open-Sourced Large Language Models via Enforced Decoding.

Hangfan Zhang, Zhimeng Guo, Huaisheng Zhu, Bochuan Cao, Lu Lin, Jinyuan Jia, Jinghui Chen, Dinghao Wu

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Learning fair models without sensitive attributes: A generative approach.

Huaisheng Zhu, Enyan Dai, Hui Liu, Suhang Wang

Neurocomputing, December, 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, Jinyuan Jia, Jinghui Chen, Dinghao Wu

CoRR, 2023

Fairness-aware Message Passing for Graph Neural Networks.

Huaisheng Zhu, Guoji Fu, Zhimeng Guo, Zhiwei Zhang, Teng Xiao, Suhang Wang

CoRR, 2023

Self-Explainable Graph Neural Networks for Link Prediction.

Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang

CoRR, 2023

You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network.

Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2023

Simple and Asymmetric Graph Contrastive Learning without Augmentations.

Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Learning Fair Models without Sensitive Attributes: A Generative Approach.

Huaisheng Zhu, Suhang Wang

CoRR, 2022

2021

ImGAGN: Imbalanced Network Embedding via Generative Adversarial Graph Networks.

Liang Qu, Huaisheng Zhu, Ruiqi Zheng, Yuhui Shi, Hongzhi Yin

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2020

Continuous-Time Link Prediction via Temporal Dependent Graph Neural Network.

Liang Qu, Huaisheng Zhu, Qiqi Duan, Yuhui Shi

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

BSOGCN: Brain Storm Optimization Graph Convolutional Networks Based Heterogeneous Information Networks Embedding.

Liang Qu, Huaisheng Zhu, Yuhui Shi

Proceedings of the IEEE Congress on Evolutionary Computation, 2020