collaborators

5 papers

cs.SE2026

Automating Structural Analysis Across Multiple Software Platforms Using Large Language Models

Ziheng Geng, Jiachen Liu, Ian Franklin +3

Recent advances in large language models (LLMs) have shown the promise to significantly accelerate the workflow by automating structural modeling and analysis. However, existing st…

cs.AI2026

A Novel Multi-Agent Architecture to Reduce Hallucinations of Large Language Models in Multi-Step Structural Modeling

Ziheng Geng, Jiachen Liu, Ran Cao +3

Large language models (LLMs) such as GPT and Gemini have demonstrated remarkable capabilities in contextual understanding and reasoning. The strong performance of LLMs has sparked…

cs.AI2025

InsurAgent: A Large Language Model-Empowered Agent for Simulating Individual Behavior in Purchasing Flood Insurance

Ziheng Geng, Jiachen Liu, Ran Cao +3

Flood insurance is an effective strategy for individuals to mitigate disaster-related losses. However, participation rates among at-risk populations in the United States remain str…

cs.CL2025

A Lightweight Large Language Model-Based Multi-Agent System for 2D Frame Structural Analysis

Ziheng Geng, Jiachen Liu, Ran Cao +3

Large language models (LLMs) have recently been used to empower autonomous agents in engineering, significantly improving automation and efficiency in labor-intensive workflows. Ho…

cs.CL2025

A Large Language Model-Empowered Agent for Reliable and Robust Structural Analysis

Jiachen Liu, Ziheng Geng, Ran Cao +3

Large language models (LLMs) have exhibited remarkable capabilities across diverse open-domain tasks, yet their application in specialized domains such as civil engineering remains…