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:
- Reinforce the robustness of foundation models to unexpected inputs (RiFT ICCV’23, PromptRobust CCS’24 LAMPS Workshop).
- Evaluation of foundation models:
- Dynamic evaluation for test data contamination issue (DyVal ICLR’24, DyVal 2 ICML’24).
news
| Aug 17, 2024 | PromptRobust is accepted by CCS LAMPS Workshop. |
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| May 2, 2024 | DyVal 2 is accepted by ICML 2024. |
| Jan 17, 2024 | DyVal is accepted by ICLR 2024 as a spotlight paper! |
| Jul 18, 2023 | Our paper “Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning” is accepted by ICCV 2023! |
selected publications
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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
