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2020 – today
- 2025
[c7]Yiteng Peng, Daoyuan Wu, Zhibo Liu, Dongwei Xiao, Zhenlan Ji, Juergen Rahmel, Shuai Wang:
Testing and Understanding Deviation Behaviors in FHE-Hardened Machine Learning Models. ICSE 2025: 2251-2263- [i11]Xunguang Wang, Wenxuan Wang, Zhenlan Ji, Zongjie Li, Pingchuan Ma, Daoyuan Wu, Shuai Wang:
STShield: Single-Token Sentinel for Real-Time Jailbreak Detection in Large Language Models. CoRR abs/2503.17932 (2025) - [i10]Yanbo Dai, Zhenlan Ji, Zongjie Li, Shuai Wang:
NAMET: Robust Massive Model Editing via Noise-Aware Memory Optimization. CoRR abs/2505.11876 (2025) - [i9]Liwen Wang, Wenxuan Wang, Shuai Wang, Zongjie Li, Zhenlan Ji, Zongyi Lyu, Daoyuan Wu, Shing-Chi Cheung:
IP Leakage Attacks Targeting LLM-Based Multi-Agent Systems. CoRR abs/2505.12442 (2025) - [i8]Xunguang Wang, Zhenlan Ji, Wenxuan Wang, Zongjie Li, Daoyuan Wu, Shuai Wang:
SoK: Evaluating Jailbreak Guardrails for Large Language Models. CoRR abs/2506.10597 (2025) - 2024
- [c6]Pingchuan Ma
, Zhenlan Ji, Peisen Yao, Shuai Wang, Kui Ren:
Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning. ICSE 2024: 30:1-30:13 - [i7]Zhenlan Ji, Daoyuan Wu, Pingchuan Ma, Zongjie Li, Shuai Wang:
Testing and Understanding Erroneous Planning in LLM Agents through Synthesized User Inputs. CoRR abs/2404.17833 (2024) - [i6]Xunguang Wang, Daoyuan Wu, Zhenlan Ji, Zongjie Li, Pingchuan Ma, Shuai Wang, Yingjiu Li, Yang Liu, Ning Liu, Juergen Rahmel:
SelfDefend: LLMs Can Defend Themselves against Jailbreaking in a Practical Manner. CoRR abs/2406.05498 (2024) - 2023
- [c5]Zhenlan Ji, Pingchuan Ma, Yuanyuan Yuan, Shuai Wang:
CC: Causality-Aware Coverage Criterion for Deep Neural Networks. ICSE 2023: 1788-1800 - [c4]Zhenlan Ji, Pingchuan Ma, Shuai Wang, Yanhui Li:
Causality-Aided Trade-Off Analysis for Machine Learning Fairness. ASE 2023: 371-383 - [c3]Zhenlan Ji, Pingchuan Ma, Shuai Wang:
Perfce: Performance Debugging on Databases with Chaos Engineering-Enhanced Causality Analysis. ASE 2023: 1454-1466 - [i5]Zhenlan Ji, Pingchuan Ma, Shuai Wang, Yanhui Li:
Causality-Aided Trade-off Analysis for Machine Learning Fairness. CoRR abs/2305.13057 (2023) - [i4]Pingchuan Ma, Zhenlan Ji, Peisen Yao, Shuai Wang, Kui Ren:
Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning (Extended Version). CoRR abs/2309.05264 (2023) - [i3]Zhenlan Ji, Pingchuan Ma, Zongjie Li, Shuai Wang:
Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach. CoRR abs/2310.06680 (2023) - [i2]Xunguang Wang, Zhenlan Ji, Pingchuan Ma, Zongjie Li, Shuai Wang:
InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language Models. CoRR abs/2312.01886 (2023) - 2022
- [j1]Pingchuan Ma, Zhenlan Ji, Qi Pang, Shuai Wang:
NoLeaks: Differentially Private Causal Discovery Under Functional Causal Model. IEEE Trans. Inf. Forensics Secur. 17: 2324-2338 (2022) - [c2]Zhenlan Ji, Pingchuan Ma, Shuai Wang:
Unlearnable Examples: Protecting Open-Source Software from Unauthorized Neural Code Learning. SEKE 2022: 525-530 - [i1]Zhenlan Ji, Pingchuan Ma, Shuai Wang:
PerfCE: Performance Debugging on Databases with Chaos Engineering-Enhanced Causality Analysis. CoRR abs/2207.08369 (2022) - 2020
- [c1]Wen-Chin Huang, Zhenlan Ji, Yanhui Li:
An Empirical Study on Issue Knowledge Transfer from Python to R for Machine Learning Software. SEKE 2020: 168-173
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