55 citations · 240 across the 40 of their papers we have counts for
4 papers · 1 filter
Uncertainty-Aware Budget Allocation for Efficient LLM Tree Search
Jianguo Huang, Zhiyi Lyu, Fuxiang Zhang +3
Tree search enhances multi-step reasoning in large language models (LLMs), yet prevailing methods expand every step with a fixed budget, irrespective of the marginal utility of exp…
Multi-objective Large Language Model Alignment with Hierarchical Experts
Zhuo Li, Guodong Du, Weiyang Guo +8
Aligning large language models (LLMs) to simultaneously satisfy multiple objectives remains a significant challenge, especially given the diverse and often conflicting nature of hu…
Improving Sample Efficiency of Reinforcement Learning with Background Knowledge from Large Language Models
Fuxiang Zhang, Junyou Li, Yi-Chen Li +3
Low sample efficiency is an enduring challenge of reinforcement learning (RL). With the advent of versatile large language models (LLMs), recent works impart common-sense knowledge…
More Agents Is All You Need
Junyou Li, Qin Zhang, Yangbin Yu +2
We find that, simply via a sampling-and-voting method, the performance of large language models (LLMs) scales with the number of agents instantiated. Also, this method, termed as A…