1 citations · 1 across the 6 of their papers we have counts for
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Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective
Siwei Wang, Yifei Shen, Haoran Sun +5
Recent reinforcement learning (RL) methods have substantially enhanced the planning capabilities of Large Language Models (LLMs), yet the theoretical basis for their effectiveness…
Semantic Caching for Low-Cost LLM Serving: From Offline Learning to Online Adaptation
Xutong Liu, Baran Atalar, Xiangxiang Dai +5
Large Language Models (LLMs) are revolutionizing how users interact with information systems, yet their high inference cost poses serious scalability and sustainability challenges.…
On the Sublinear Regret of Continuous K-Max Bandits
Yu Chen, Siwei Wang, Longbo Huang +1
The -Max combinatorial multi-armed bandit problem arises in applications such as recommendation and distributed decision making, where the reward is determined by the maximum ou…
Offline Learning for Combinatorial Multi-armed Bandits
Xutong Liu, Xiangxiang Dai, Jinhang Zuo +4
The combinatorial multi-armed bandit (CMAB) is a fundamental sequential decision-making framework, extensively studied over the past decade. However, existing work primarily focuse…