5 papers
EDU-CIRCUIT-HW: Evaluating Multimodal Large Language Models on Real-World University-Level STEM Student Handwritten Solutions
Weiyu Sun, Liangliang Chen, Yongnuo Cai +3
Multimodal Large Language Models (MLLMs) hold significant promise for revolutionizing traditional education and reducing teachers' workload. However, accurately interpreting uncons…
Enhancing Large Language Model-Based Systems for End-to-End Circuit Analysis Problem Solving
Liangliang Chen, Weiyu Sun, Huiru Xie +2
LLMs have demonstrated strong performance in data-rich domains such as programming, yet their reliability in engineering tasks remains limited. Circuit analysis--requiring multimod…
Enhancing Large Language Models for Automated Homework Assessment in Undergraduate Circuit Analysis
Liangliang Chen, Huiru Xie, Zhihao Qin +3
This research full paper presents an enhancement pipeline for large language models (LLMs) in assessing homework for an undergraduate circuit analysis course, aiming to improve LLM…
WIP: Large Language Model-Enhanced Smart Tutor for Undergraduate Circuit Analysis
Liangliang Chen, Huiru Xie, Jacqueline Rohde +1
This research-to-practice work-in-progress (WIP) paper presents an AI-enabled smart tutor designed to provide homework assessment and feedback for students in an undergraduate circ…
Benchmarking Large Language Models on Homework Assessment in Circuit Analysis
Liangliang Chen, Zhihao Qin, Yiming Guo +2
Large language models (LLMs) have the potential to revolutionize various fields, including code development, robotics, finance, and education, due to their extensive prior knowledg…