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cs.LG2026
Efficient Multi-objective Prompt Optimization via Pure-exploration Bandits
Donghao Li, Chengshuai Shi, Weijuan Ou +2
Prompt engineering has become central to eliciting the capabilities of large language models (LLMs). At its core lies prompt selection -- efficiently identifying the most effective…
cs.LG2026
Breaking the Computational Barrier: Provably Efficient Actor-Critic for Low-Rank MDPs
Ruiquan Huang, Donghao Li, Yingbin Liang +1
Reinforcement learning (RL) is a fundamental framework for sequential decision-making, in which an agent learns an optimal policy through interactions with an unknown environment.…