STAR Group
Safe & Trustworthy AI Resarch (STAR) group studies AI safety and trustworthiness. We are part of the CAS Key Laboratory of AI Safety.
At STAR Group, we believe interpretability is a key to building safe and trustworthy AI. Our research focuses on the knowledge mechanisms of AI models—how they learn, memorize, recall, update/edit, and forget knowledge. We also explore the security and privacy impacts of deploying AI in real-world applications, with a special focus on LLMs and recommender systems.
Open Positions
We are looking for self-motivated interns/postdoc to do research with us. Feel free to contact us if you are interested. For more information, please visit the Join us page.
Latest News
Aug 21, 2025 | Three papers are accepted by EMNLP 2025 about Hallucination/Uncertainty Estimation, Backdoor, and Jailbreaking. |
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Aug 01, 2025 | Congratulations to Wanli on receiving the Best Paper Award at the KnowFM @ ACL25 Workshop—a well-deserved recognition of his excellent research! |
May 15, 2025 | Two papers are accepted by ACL2025 about model editing and watermarking. Congrats to Wanli and Beining! |
Dec 22, 2024 | We will hold The 1st Workshop on Human-Centered Recommender Systems on WWW 25. Contributions are welcome ! |
Sep 15, 2024 | Our paper The Fall of ROME is accepted by EMNLP2024 finding. Congrats to Wanli! |
May 16, 2024 | Three papers are accepted by ACL2024 about model editing, bias in knowledge conflict, and confidence alignment. Congrats to Hexiang, Wanli, and Shuchang! |
Mar 22, 2024 | Our paper Unlink to Unlearn: Simplifying Edge Unlearning in GNNs is accepted by WebConf2024. Congrats to Jiajun! |