News
- [Feb 14, 2025] Our paper, zkVC , was accepted to DAC 2025.
- [Jan 22, 2025] Our paper, CipherPrune , was accepted to ICLR 2025.
- [Oct 13, 2024] I participated in the 7th HomomorphicEncryption.org Standards Meeting.
- [Sep 25, 2024] Our paper, Encrypted Data Pruning , was accepted to NeurIPS 2024.
- [Aug 29, 2024] Our paper, HEBridge, was accepted to CCS WAHC 2024.
- [May 13, 2024] I started my internship at Samsung Research America.
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E3D-Bench: A Benchmark for End-to-End 3D Geometric Foundation Models
Wenyan Cong, Yiqing Liang, Yancheng Zhang, Ziyi Yang, Yan Wang, Boris Ivanovic, Marco Pavone, Chen Chen, Zhangyang Wang, Zhiwen Fan
Preprint, 2025
This work benchmarks 3D geometric foundation models (GFMs), offering in-depth evaluation of their spatial intelligence capabilities and insights for future research.
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zkVC: Fast Zero-Knowledge Proof for Private and Verifiable Computing
Yancheng Zhang, Mengxin Zheng, Xun Chen, Jingtong Hu, Weidong Shi, Lei Ju, Yan Solihin, Qian Lou
DAC, 2025
This work enhances the efficiency of Zero-Knowledge Proof (ZKP) protocols for matrix multiplication.
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CipherPrune: Efficient and Scalable Private Transformer Inference
Yancheng Zhang, Jiaqi Xue, Mengxin Zheng, Mimi Xie, Mingzhe Zhang, Lei Jiang, Qian Lou
ICLR, 2025
This work improves the efficiency of private Transformer inference in the secure two-party computation (2PC) setting.
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DataSeal: Ensuring the Verifiability of Private Computation on Encrypted Data
Muhammad Husni Santriaji, Jiaqi Xue, Yancheng Zhang, Qian Lou, Yan Solihin
IEEE S&P, 2025
This work enhances the verifiability and integrity of private computation in FHE by incorporating algorithm-based fault tolerance.
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HEBridge: Connecting arithmetic and logic operations in FV-style HE schemes
Yancheng Zhang, Xun Chen and Qian Lou
ACM CCS WAHC, 2024
This work enables the continuous evaluation of linear and non-linear operations within the BGV/BFV FHE schemes, enhancing their universality.
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CryptoTrain: Fast Secure Training on Encrypted Dataset
Jiaqi Xue, Yancheng Zhang, Yanshan Wang, Xueqiang Wang, Hao Zheng, Qian Lou
ACM CCS LAMPS, 2024
This work accelerates FHE/MPC-based private training through correlation-aware polynomial convolution.
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Encrypted Data Pruning for Confidential Training of Deep Neural Networks
Yancheng Zhang, Mengxin Zheng, Yuzhang Shang, Xun Chen, Qian Lou
NeurIPS, 2024
This work enhances FHE-based private training by incorporating and optimizing dynamic dataset pruning in the encrypted state.
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CR-UTP: Certified Robustness against Universal Text Perturbations
Qian Lou, Xin Liang, Jiaqi Xue, Yancheng Zhang, Rui Xie, Mengxin Zheng
ACL, 2024
This work improves the certified robustness of language models against universal text perturbations through prompt search and ensemble methods.
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Pure graph-guided multi-view subspace clustering
Hongjie Wu, Shudong Huang, Chenwei Tang, Yancheng Zhang, Jiancheng LV
Pattern Recognition, 2023
This work improves multi-view subspace clustering by leveraging the sparsity and connectivity of affinity graphs.
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Services
Conference Reviewer: ICLR 2025.
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