Large Language Models as Autonomous Agents
Project Description
With the advent of Large Language Models (LLMs), LLM-based agents are achieving greater autonomy through advanced agentic workflows and tool utilization. These agents have been deployed across various major domains, including software engineering, healthcare, and advanced research. Exploring the application and enhancement of these agents in diverse scenarios is becoming increasingly significant. This project is highly research-oriented and requires applicants to have a strong academic background, preferably with prior research experience in ML/NLP.
Supervisor
SONG Yangqiu
Quota
5
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
Collaborate with a PhD student on task formulation, experiment design, result analysis, and research paper writing.
Applicant's Learning Objectives
Gain hands-on experience with LLM Agents while learning research methodologies in natural language processing.
Complexity of the project
Challenging