no code implementations • 22 Dec 2023 • Tiejin Chen, Yuanpu Cao, Yujia Wang, Cho-Jui Hsieh, Jinghui Chen
Specifically, FedPTR allows local clients or the server to optimize an auxiliary (synthetic) dataset that mimics the learning dynamics of the recent model update and utilizes it to project the next-step model trajectory for local training regularization.
no code implementations • 15 Nov 2023 • Yuanpu Cao, Bochuan Cao, Jinghui Chen
In this work, we show that it is possible to conduct stealthy and persistent unalignment on large language models via backdoor injections.
1 code implementation • 18 Sep 2023 • Bochuan Cao, Yuanpu Cao, Lu Lin, Jinghui Chen
In this work, we introduce a Robustly Aligned LLM (RA-LLM) to defend against potential alignment-breaking attacks.
8 code implementations • 10 Oct 2019 • Daochen Zha, Kwei-Herng Lai, Yuanpu Cao, Songyi Huang, Ruzhe Wei, Junyu Guo, Xia Hu
The goal of RLCard is to bridge reinforcement learning and imperfect information games, and push forward the research of reinforcement learning in domains with multiple agents, large state and action space, and sparse reward.