31 citations · 113 across the 23 of their papers we have counts for
5 papers · 1 filter
AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
Yuliang Liu, Junjie Lu, Zhaoling Chen +10
Current approaches for training Process Reward Models (PRMs) often involve breaking down responses into multiple reasoning steps using rule-based techniques, such as using predefin…
Empowering Large Language Models on Robotic Manipulation with Affordance Prompting
Guangran Cheng, Chuheng Zhang, Wenzhe Cai +3
While large language models (LLMs) are successful in completing various language processing tasks, they easily fail to interact with the physical world by generating control sequen…
Pre-Trained Large Language Models for Industrial Control
Lei Song, Chuheng Zhang, Li Zhao +1
For industrial control, developing high-performance controllers with few samples and low technical debt is appealing. Foundation models, possessing rich prior knowledge obtained fr…
A Versatile Multi-Agent Reinforcement Learning Benchmark for Inventory Management
Xianliang Yang, Zhihao Liu, Wei Jiang +4
Multi-agent reinforcement learning (MARL) models multiple agents that interact and learn within a shared environment. This paradigm is applicable to various industrial scenarios su…
Multi-Agent Reinforcement Learning with Shared Resources for Inventory Management
Yuandong Ding, Mingxiao Feng, Guozi Liu +7
In this paper, we consider the inventory management (IM) problem where we need to make replenishment decisions for a large number of stock keeping units (SKUs) to balance their sup…