Minhua Lin

According to our database, Minhua Lin authored at least 32 papers between 2020 and 2026.

Collaborative distances:

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

2026

Harness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM Agents.

Minhua Lin, Juncheng Wu, Zijun Wang, Zhan Shi, Yisi Sang, Bing He, Zewen Liu, Tianxin Wei, Zongyu Wu, Zhiwei Zhang, Dakuo Wang, Xiang Zhang, Benoît Dumoulin, Cihang Xie, Yuyin Zhou, Suhang Wang, Hanqing Lu

CoRR, May, 2026

MemMA: Coordinating the Memory Cycle through Multi-Agent Reasoning and In-Situ Self-Evolution.

Minhua Lin, Zhiwei Zhang, Hanqing Lu, Hui Liu, Xianfeng Tang, Qi He, Xiang Zhang, Suhang Wang

CoRR, March, 2026

How Far Are LLMs from Professional Poker Players? Revisiting Game-Theoretic Reasoning with Agentic Tool Use.

Minhua Lin, Enyan Dai, Hui Liu, Xianfeng Tang, Yuliang Yan, Zhenwei Dai, Jingying Zeng, Zhiwei Zhang, Fali Wang, Hongcheng Gao, Chen Luo, Xiang Zhang, Qi He, Suhang Wang

CoRR, February, 2026

Position: Agentic Evolution is the Path to Evolving LLMs.

Minhua Lin, Hanqing Lu, Zhan Shi, Bing He, Rui Mao, Zhiwei Zhang, Zongyu Wu, Xianfeng Tang, Hui Liu, Zhenwei Dai, Xiang Zhang, Suhang Wang, Benoît Dumoulin, Jian Pei

CoRR, February, 2026

Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models.

Zongyu Wu, Minhua Lin, Zhiwei Zhang, Fali Wang, Xianren Zhang, Xiang Zhang, Suhang Wang

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

Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation.

Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu, Junxiang Wang, Xiang Zhang, Suhang Wang, Haifeng Chen

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2026, 2026

2025

Unlocking the Power of Multi-Agent LLM for Reasoning: From Lazy Agents to Deliberation.

Zhiwei Zhang, Xiaomin Li, Yudi Lin, Hui Liu, Ramraj Chandradevan, Linlin Wu, Minhua Lin, Fali Wang, Xianfeng Tang, Qi He, Suhang Wang

CoRR, November, 2025

A Comprehensive Survey on Reinforcement Learning-based Agentic Search: Foundations, Roles, Optimizations, Evaluations, and Applications.

Minhua Lin, Zongyu Wu, Zhichao Xu, Hui Liu, Xianfeng Tang, Qi He, Charu C. Aggarwal, Hui Liu, Xiang Zhang, Suhang Wang

CoRR, October, 2025

Pixels, Patterns, but No Poetry: To See The World like Humans.

Hongcheng Gao, Zihao Huang, Lin Xu, Jingyi Tang, Xinhao Li, Yue Liu, Haoyang Li, Taihang Hu, Minhua Lin, Xinlong Yang, Ge Wu, Balong Bi, Hongyu Chen, Wentao Zhang

CoRR, July, 2025

Bradley-Terry and Multi-Objective Reward Modeling Are Complementary.

Zhiwei Zhang, Hui Liu, Xiaomin Li, Zhenwei Dai, Jingying Zeng, Fali Wang, Minhua Lin, Ramraj Chandradevan, Zheng Li, Chen Luo, Xianfeng Tang, Qi He, Suhang Wang

CoRR, July, 2025

How Explanations Leak the Decision Logic: Stealing Graph Neural Networks via Explanation Alignment.

Bin Ma, Yuyuan Feng, Minhua Lin, Enyan Dai

CoRR, June, 2025

Protap: A Benchmark for Protein Modeling on Realistic Downstream Applications.

Shuo Yan, Yuliang Yan, Bin Ma, Chenao Li, Haochun Tang, Jiahua Lu, Minhua Lin, Yuyuan Feng, Hui Xiong, Enyan Dai

CoRR, June, 2025

How Far are LLMs from Real Search? A Comprehensive Study on Efficiency, Completeness, and Inherent Capabilities.

Minhua Lin, Hui Liu, Xianfeng Tang, Jingying Zeng, Zhenwei Dai, Chen Luo, Zheng Li, Xiang Zhang, Qi He, Suhang Wang

CoRR, February, 2025

LanP: Rethinking the Impact of Language Priors in Large Vision-Language Models.

Zongyu Wu, Yuwei Niu, Hongcheng Gao, Minhua Lin, Zhiwei Zhang, Zhifang Zhang, Qi Shi, Yilong Wang, Sike Fu, Junjie Xu, Junjie Ao, Enyan Dai, Lei Feng, Xiang Zhang, Suhang Wang

CoRR, February, 2025

Fairness-aware Prompt Tuning for Graph Neural Networks.

Zhengpin Li, Minhua Lin, Jian Wang, Suhang Wang

Proceedings of the ACM on Web Conference 2025, 2025

A Survey on Small Language Models in the Era of Large Language Models: Architecture, Capabilities, and Trustworthiness.

Fali Wang, Minhua Lin, Yao Ma, Hui Liu, Qi He, Xianfeng Tang, Jiliang Tang, Jian Pei, Suhang Wang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks.

Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang, Xiang Zhang, Suhang Wang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Stealing Training Graphs from Graph Neural Networks.

Minhua Lin, Enyan Dai, Junjie Xu, Jinyuan Jia, Xiang Zhang, Suhang Wang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep IP Protection.

Enyan Dai, Minhua Lin, Suhang Wang

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Robustness Inspired Graph Backdoor Defense.

Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

xTime: Extreme Event Prediction with Hierarchical Knowledge Distillation and Expert Fusion.

Quan Li, Wenchao Yu, Suhang Wang, Minhua Lin, Lingwei Chen, Wei Cheng, Haifeng Chen

Proceedings of the IEEE International Conference on Data Mining, 2025

LLM and GNN Are Complementary: Distilling LLM for Multimodal Graph Learning.

Junjie Xu, Zongyu Wu, Minhua Lin, Xiang Zhang, Suhang Wang

Proceedings of the IEEE International Conference on Big Data, 2025

2024

Trojan Prompt Attacks on Graph Neural Networks.

Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang, Xiang Zhang, Suhang Wang

CoRR, 2024

Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Networks.

Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang

CoRR, 2024

PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection.

Enyan Dai, Minhua Lin, Suhang Wang

CoRR, 2024

Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function.

Binghui Wang, Minhua Lin, Tianxiang Zhou, Pan Zhou, Ang Li, Meng Pang, Hai Helen Li, Yiran Chen

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective.

Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Adversarial Robustness in Graph Neural Networks: Recent Advances and New Frontier.

Zhichao Hou, Minhua Lin, MohamadAli Torkamani, Suhang Wang, Xiaorui Liu

Proceedings of the 11th IEEE International Conference on Data Science and Advanced Analytics, 2024

2023

Unnoticeable Backdoor Attacks on Graph Neural Networks.

Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang

Proceedings of the ACM Web Conference 2023, 2023

Certifiably Robust Graph Contrastive Learning.

Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang

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

2021

A Hybrid Hesitant 2-Tuple IVSF Decision Making Approach to Analyze PERT-Based Critical Paths of New Service Development Process for Renewable Energy Investment Projects.

Fei Cheng, Minhua Lin, Serhat Yüksel, Hasan Dinçer, Hakan Kalkavan

IEEE Access, 2021

2020

Evasion Attacks to Graph Neural Networks via Influence Function.

Binghui Wang, Tianxiang Zhou, Minhua Lin, Pan Zhou, Ang Li, Meng Pang, Cai Fu, Hai Li, Yiran Chen

CoRR, 2020