4 papers
OpenCarbon: A Contrastive Learning-based Cross-Modality Neural Approach for High-Resolution Carbon Emission Prediction Using Open Data
Jinwei Zeng, Yu Liu, Guozhen Zhang +4
Accurately estimating high-resolution carbon emissions is crucial for effective emission governance and mitigation planning. While conventional methods for precise carbon accountin…
Multiple Weaks Win Single Strong: Large Language Models Ensemble Weak Reinforcement Learning Agents into a Supreme One
Yiwen Song, Qianyue Hao, Qingmin Liao +2
Model ensemble is a useful approach in reinforcement learning (RL) for training effective agents. Despite wide success of RL, training effective agents remains difficult due to the…
LLM-Explorer: A Plug-in Reinforcement Learning Policy Exploration Enhancement Driven by Large Language Models
Qianyue Hao, Yiwen Song, Qingmin Liao +2
Policy exploration is critical in reinforcement learning (RL), where existing approaches include greedy, Gaussian process, etc. However, these approaches utilize preset stochastic…
RL of Thoughts: Navigating LLM Reasoning with Inference-time Reinforcement Learning
Qianyue Hao, Sibo Li, Jian Yuan +1
Despite rapid advancements in large language models (LLMs), the token-level autoregressive nature constrains their complex reasoning capabilities. To enhance LLM reasoning, inferen…