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cs.LG2024
Sample-Efficient Alignment for LLMs
Zichen Liu, Changyu Chen, Chao Du +2
We study methods for efficiently aligning large language models (LLMs) with human preferences given budgeted online feedback. We first formulate the LLM alignment problem in the fr…
cs.LG2024
Locality Sensitive Sparse Encoding for Learning World Models Online
Zichen Liu, Chao Du, Wee Sun Lee +1
Acquiring an accurate world model online for model-based reinforcement learning (MBRL) is challenging due to data nonstationarity, which typically causes catastrophic forgetting fo…