4 papers
CeProAgents: A Hierarchical Agents System for Automated Chemical Process Development
Yuhang Yang, Ruikang Li, Jifei Ma +8
The development of chemical processes, a cornerstone of chemical engineering, presents formidable challenges due to its multi-faceted nature, integrating specialized knowledge, con…
AgentCAT: An LLM Agent for Extracting and Analyzing Catalytic Reaction Data from Chemical Engineering Literature
Wei Yang, Zihao Liu, Tao Tan +6
This paper presents a large language model (LLM) agent named AgentCAT, which extracts and analyzes catalytic reaction data from chemical engineering papers, %and supports natural l…
Demystifying Design Choices of Reinforcement Fine-tuning: A Batched Contextual Bandit Learning Perspective
Hong Xie, Xiao Hu, Tao Tan +5
The reinforcement fine-tuning area is undergoing an explosion papers largely on optimizing design choices. Though performance gains are often claimed, inconsistent conclusions also…
Rethinking Reinforcement fine-tuning of LLMs: A Multi-armed Bandit Learning Perspective
Xiao Hu, Hong Xie, Tao Tan +2
A large number of heuristics have been proposed to optimize the reinforcement fine-tuning of LLMs. However, inconsistent claims are made from time to time, making this area elusive…