Feb. 8, 2024, 5:42 a.m. | Yiyou Sun Junjie Hu Wei Cheng Haifeng Chen

cs.LG updates on arXiv.org arxiv.org

This paper introduces the Definite Finite Automaton augmented large language model (DFA-LLM), a novel framework designed to enhance the capabilities of conversational agents using large language models (LLMs). Traditional LLMs face challenges in generating regulated and compliant responses in special scenarios with predetermined response guidelines, like emotional support and customer service. Our framework addresses these challenges by embedding a Definite Finite Automaton (DFA), learned from training dialogues, within the LLM. This structured approach enables the LLM to adhere to a …

agents automaton capabilities challenges chatbot conversational conversational agents cs.cl cs.lg face framework guidelines language language model language models large language large language model large language models llm llms novel paper pipeline responses support

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Field Sample Specialist (Air Sampling) - Eurofins Environment Testing – Pueblo, CO

@ Eurofins | Pueblo, CO, United States

Camera Perception Engineer

@ Meta | Sunnyvale, CA