Zhimeng Guo

According to our database, Zhimeng Guo authored at least 21 papers between 2021 and 2026.

Collaborative distances:

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

2026

Do Audio LLMs Really LISTEN, or Just Transcribe? Measuring Lexical vs. Acoustic Emotion Cues Reliance.

Jingyi Chen, Zhimeng Guo, Jiyun Chun, Pichao Wang, Andrew Perrault, Micha Elsner

Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026

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

Counterfactual Learning on Graphs: A Survey.

Zhimeng Guo, Zongyu Wu, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang

Mach. Intell. Res., February, 2025

Simple Distillation for One-Step Diffusion Models.

Huaisheng Zhu, Teng Xiao, Shijie Zhou, Zhimeng Guo, Hangfan Zhang, Siyuan Xu, Vasant G. Honavar

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Reinforcement Learning for Large Language Models via Group Preference Reward Shaping.

Huaisheng Zhu, Siyuan Xu, Hangfan Zhang, Teng Xiao, Zhimeng Guo, Shijie Zhou, Shuyue Hu, Vasant G. Honavar

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 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

Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark.

Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 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

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

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

Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective.

Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, 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

Counterfactual Learning on Graphs: A Survey.

Zhimeng Guo, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang

CoRR, 2023

Towards Fair Graph Neural Networks via Graph Counterfactual.

Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Link Prediction on Heterophilic Graphs via Disentangled Representation Learning.

Shijie Zhou, Zhimeng Guo, Charu C. Aggarwal, Xiang Zhang, Suhang Wang

CoRR, 2022

Decoupled Self-supervised Learning for Non-Homophilous Graphs.

Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

CoRR, 2022

Decoupled Self-supervised Learning for Graphs.

Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Label-Wise Graph Convolutional Network for Heterophilic Graphs.

Enyan Dai, Shijie Zhou, Zhimeng Guo, Suhang Wang

Proceedings of the Learning on Graphs Conference, 2022

2021

Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs.

Enyan Dai, Zhimeng Guo, Suhang Wang

CoRR, 2021