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Wei Shen I'm a Ph.D. student at The Hong Kong Polytechnic University, under the supervision of Prof. Qiang Yang. Before that, I obtained my M.S. degree from Wuhan University in 2026. My research interests lie in Federated Learning, Large Language Models and AI Safety. |
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Selected Publications |
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DecepChain: Inducing Deceptive Reasoning in Large Language Models
[paper] [project] Wei Shen+, Han Wang+, Haoyu Li+, Huan Zhang Forty-Third International Conference on Machine Learning (ICML), 2026 We investigate the intriguing deceptive behavior in existing LLMs where CoTs are incorrect but look plausible for human users. |
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MARS-VFL: A Unified Benchmark for Vertical Federated Learning with Realistic Evaluation (Spotlight)
[paper] [codes] Wei Shen, Weiqi Liu, Mingde Chen, Wenke Huang, Mang Ye The 39th Conference on Neural Information Processing Systems (NeurIPS), 2025 We propose a unified benchmark for realistic VFL evaluation that integrates data from practical applications. |
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Label-Free Backdoor Attacks in Vertical Federated Learning
[paper] [codes] Wei Shen+, Wenke Huang+, Guancheng Wan, Mang Ye The 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025 We propose a backdoor paradigm for VFL that operates without explicit label information. |
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Resisting Over-Smoothing in Graph Neural Networks via Dual-Dimensional Decoupling
[paper] [codes] Wei Shen, Mang Ye, Wenke Huang ACM Multimedia (ACM MM), 2024 We address the oversmoothing issue in GNNs by leveraging both instance-level and dimension-level cues. |
Service
Conference Reviewer: ICLR 2025/2026/2027, NeurIPS 2026, CVPR 2024/2025/2026, AAAI 2026/2027.
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