Built with and by Teycir Ben Soltane•
How to Use•FAQ•GitHub•arXiv.org•
Share:
ArXivCSExplorer
☆☆Bookmarks🏆RSSHow to UseFAQ
Home/Authors/Jie Wen

Jie Wen

2 indexed papers

Recent (6 mo)
2
With code
0
Influential cites
0
Benchmarked
0

Publications per year

2
26

Top categories

Crypto×2AI×2Distributed×1

Frequent co-authors

Lijia Lv1×
Xuehai Tang1×
Jizhong Han1×
Songlin Hu1×
Zhaoting Gong1×
Ran Ran1×

Research Timeline

2026
AEGIS: Scaling Long-Sequence Homomorphic Encrypted Transformer Inference via Hybrid Parallelism on Multi-GPU Systems

AEGIS is a novel system that significantly improves the scalability of running large, long-sequence Transformer models under Fully Homomorphic Encryption (FHE) on multi-GPU systems by optimizing data placement and communication.

Structured Security Auditing and Robustness Enhancement for Untrusted Agent Skills

The paper introduces SkillGuard-Robust, a novel framework for robust, cross-file security auditing of untrusted agent skills, achieving high accuracy on large-scale package evaluations.

Highlighted terms show continued research focus across papers

Papers

cs.CRcs.AIRecentApr 28, 2026

Structured Security Auditing and Robustness Enhancement for Untrusted Agent Skills

Lijia Lv, Xuehai Tang, Jie Wen, Jizhong Han +1 more

The paper introduces SkillGuard-Robust, a novel framework for robust, cross-file security auditing of untrusted agent skills, achieving high accuracy on large-scale package evaluations.

View →
cs.CRcs.AIcs.DCRecentApr 3, 2026

AEGIS: Scaling Long-Sequence Homomorphic Encrypted Transformer Inference via Hybrid Parallelism on Multi-GPU Systems

Zhaoting Gong, Ran Ran, Fan Yao, Wujie Wen

AEGIS is a novel system that significantly improves the scalability of running large, long-sequence Transformer models under Fully Homomorphic Encryption (FHE) on multi-GPU systems by optimizing data…

View →