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.
- Trustworthy AI:
- Robustness (RiFT ICCV’23, PromptRobust CCS’24 LAMPS Workshop).
- Prompt Injection (MELON)
- Evaluation of foundation models:
- Dynamic evaluation for test data contamination issue (DyVal ICLR’24, DyVal 2 ICML’24).
news
| 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. |
| Jan 17, 2024 | DyVal is accepted by ICLR 2024 as a spotlight paper. |
selected publications
-
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-TuningIn ICCV, 2023 -
DyVal 2: Dynamic Evaluation of Large Language Models by Meta Probing AgentsIn , 2024
