Zhenlan Ji

Orcid: 0000-0003-3167-0480

According to our database1, Zhenlan Ji authored at least 12 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Links

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Bibliography

2024
SelfDefend: LLMs Can Defend Themselves against Jailbreaking in a Practical Manner.
CoRR, 2024

Testing and Understanding Erroneous Planning in LLM Agents through Synthesized User Inputs.
CoRR, 2024

Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning.
Proceedings of the 46th IEEE/ACM International Conference on Software Engineering, 2024

2023
InstructTA: Instruction-Tuned Targeted Attack for Large Vision-Language Models.
CoRR, 2023

Benchmarking and Explaining Large Language Model-based Code Generation: A Causality-Centric Approach.
CoRR, 2023

Enabling Runtime Verification of Causal Discovery Algorithms with Automated Conditional Independence Reasoning (Extended Version).
CoRR, 2023

Causality-Aided Trade-Off Analysis for Machine Learning Fairness.
Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, 2023

Perfce: Performance Debugging on Databases with Chaos Engineering-Enhanced Causality Analysis.
Proceedings of the 38th IEEE/ACM International Conference on Automated Software Engineering, 2023

CC: Causality-Aware Coverage Criterion for Deep Neural Networks.
Proceedings of the 45th IEEE/ACM International Conference on Software Engineering, 2023

2022
NoLeaks: Differentially Private Causal Discovery Under Functional Causal Model.
IEEE Trans. Inf. Forensics Secur., 2022

Unlearnable Examples: Protecting Open-Source Software from Unauthorized Neural Code Learning.
Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering, 2022

2020
An Empirical Study on Issue Knowledge Transfer from Python to R for Machine Learning Software.
Proceedings of the 32nd International Conference on Software Engineering and Knowledge Engineering, 2020


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