Workshop on Large Language Models for Agents

Xinyun Chen, Xiangru Tang, Di Jin, Devamanyu Hazarika, Daniel Fried, Dawn Song, Shafiq Joty, Meredith Ringel Morris

Workshop Type: Hybrid

Keywords: large language models, natural language processing, autonomous agents

Abstract: This workshop delves into the significance of agents driven by large language models (LLMs), a topic that has recently sparked intense discussions. Building on the current huge progress on LLMs, we'll focus on autonomous agents that perform intricate tasks in both real and simulated environments guided by natural language instructions. What sets these agents apart is their sophisticated use of language prompts, not just as a means of communication but also as a medium for reasoning—a characteristic once thought unique to humans. Our workshop specifically aims to discuss the methods, tasks, theories, and risks associated with LLM-driven agents that are capable of using language as a tool for thought and communication.

Submission Number: 36