| 2026 | AAAI | False Positives Matter: Multidimensional Localization Evaluation and Training-Free Explainable Adversarial Patch Defense. | Lihua Jing, Rui Wang, Jinwen Zhong, Runbo Li, Zixuan Zhu |
| 2026 | ISCAS | PacViT: An Efficient ViT Accelerator with Native Dynamic Pruning and Sliding Cache Attention. | Jun Gong, Zixuan Zhu, Li Tian, Yongxin Zhu |
| 2026 | WWW | Unveiling the Resilience of LLM-Enhanced Search Engines against Black-Hat SEO Manipulation. | Pei Chen, Geng Hong, Xinyi Wu, Mengying Wu, Zixuan Zhu, Mingxuan Liu, Baojun Liu, Mi Zhang, Min Yang |
| 2025 | CVPR | EntropyMark: Towards More Harmless Backdoor Watermark via Entropy-based Constraint for Open-source Dataset Copyright Protection. | Ming Sun, Rui Wang, Zixuan Zhu, Lihua Jing, Yuanfang Guo |
| 2025 | FOCS | Optimal 4-Approximation for the Correlated Pandora's Problem. | Nikhil Bansal, Zhiyi Huang, Zixuan Zhu |
| 2025 | ICASSP | GPT-C: Generative PrompT Compression. | Lijun Liu, Rui Wang, Lihua Jing, Feixiao Lv, Zixuan Zhu |
| 2025 | ICRA | Multi-Task Robustness Enhancement Framework against Various Adversarial Patches. | Lihua Jing, Rui Wang, Runbo Li, Zixuan Zhu, Xingxing Wei |
| 2025 | NAACL | CuriousLLM: Elevating Multi-Document Question Answering with LLM-Enhanced Knowledge Graph Reasoning. | Zukang Yang, Zixuan Zhu, Jennifer Zhu |
| 2024 | COCOON | MPMD on Two Sources with Lookahead. | Enze Sun, Bo Wang, Quan Xue, Mengshi Zhao, Zixuan Zhu |
| 2024 | ECAI | MakeupAttack: Feature Space Black-Box Backdoor Attack on Face Recognition via Makeup Transfer. | Ming Sun, Lihua Jing, Zixuan Zhu, Rui Wang |
| 2024 | ESA | Laminar Matroid Secretary: Greedy Strikes Back. | Zhiyi Huang, Zahra Parsaeian, Zixuan Zhu |
| 2023 | ICCV | The Victim and The Beneficiary: Exploiting a Poisoned Model to Train a Clean Model on Poisoned Data. | Zixuan Zhu, Rui Wang, Cong Zou, Lihua Jing |
| 2021 | ISCAS | Energy-Efficient Spin-Orbit Torque MRAM Operations for Neural Network Processor. | Liang Chang, Zixuan Zhu, Zhen Zhu, Siqi Yang, Weihang Li, Jun Zhou |
| 2021 | MICRO | Distilling Bit-level Sparsity Parallelism for General Purpose Deep Learning Acceleration. | Hang Lu, Liang Chang, Chenglong Li, Zixuan Zhu, Shengjian Lu, Yanhuan Liu, Mingzhe Zhang |
| 2021 | WWW | Large-scale Comb-K Recommendation. | Houye Ji, Junxiong Zhu, Chuan Shi, Xiao Wang, Bai Wang, Chaoyu Zhang, Zixuan Zhu, Feng Zhang, Yanghua Li |