Kaijie Zhu

kaijiezhu@ucsb.edu
CA, US
I’m a first-year Ph.D student at UCSB, fortunately advised by Prof. William Wang and Prof. Wenbo Guo. Previous, I have spent time at Microsoft, advised by Prof. Jindong Wang and Prof. Xing Xie.
My current research interest lies in the development of trustworthy AI systems and evaluation of foundation models. In my spare time, I love playing tennis and hold’em.
- Trustworthy AI:
- Robustness (RiFT ICCV’23, PromptRobust CCS’24 LAMPS Workshop).
- Prompt Injection (MELON, ICML 2025)
- Evaluation of foundation models:
- Dynamic evaluation for test data contamination issue (DyVal ICLR’24, DyVal 2 ICML’24).
news
May 1, 2025 | MELON is accepted by ICML 2025. |
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Feb 25, 2025 | Hosting the AAAI 2025 Tutorial on Evaluating Large Language Models: Challenges and Methods with Prof. Jindong Wang, Dr. Linyi Yang, Prof. Yue Feng, and Prof. Yue Zhang. |
Jan 20, 2025 | Selected to present a talk at the KAUST Rising Stars in AI Symposium 2025. |
Aug 17, 2024 | PromptRobust is accepted by CCS LAMPS Workshop. |
May 2, 2024 | DyVal 2 is accepted by ICML 2024. |
selected publications
- MELON: Indirect Prompt Injection Defense via Masked Re-execution and Tool ComparisonICML, 2025
- DyVal: Graph-informed Dynamic Evaluation of Large Language ModelsICLR (Spotlight), 2024
- PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial PromptsCCS LAMPS Workshop, 2023
- Improving Generalization of Adversarial Training via Robust Critical Fine-TuningICCV, 2023
- DyVal 2: Dynamic Evaluation of Large Language Models by Meta Probing AgentsICML, 2024