9 papers
FT-MDT: Extracting Decision Trees from Medical Texts via a Novel Low-rank Adaptation Method
Yuheng Li, Jiechao Gao, Wei Han +3
Knowledge of the medical decision process, which can be modeled as medical decision trees (MDTs), is critical to building clinical decision support systems. However, current MDT co…
AMAS: Adaptively Determining Communication Topology for LLM-based Multi-Agent System
Hui Yi Leong, Yuheng Li, Yuqing Wu +4
Although large language models (LLMs) have revolutionized natural language processing capabilities, their practical implementation as autonomous multi-agent systems (MAS) for indus…
Coarse-to-Fine Personalized LLM Impressions for Streamlined Radiology Reports
Chengbo Sun, Hui Yi Leong, Lei Li
The manual creation of the "Impression" section in radiology reports is a primary driver of radiologist burnout. To address this challenge, we propose a coarse-to-fine framework th…
Sensitivity-LoRA: Low-Load Sensitivity-Based Fine-Tuning for Large Language Models
Hao Zhang, Bo Huang, Zhenjia Li +6
Large Language Models (LLMs) have transformed both everyday life and scientific research. However, adapting LLMs from general-purpose models to specialized tasks remains challengin…
Beyond Magic Words: Sharpness-Aware Prompt Evolving for Robust Large Language Models with TARE
Guancheng Wan, Lucheng Fu, Haoxin Liu +10
The performance of Large Language Models (LLMs) hinges on carefully engineered prompts. However, prevailing prompt optimization methods, ranging from heuristic edits and reinforcem…
DynaSwarm: Dynamically Graph Structure Selection for LLM-based Multi-agent System
Hui Yi Leong, Yuqing Wu
Current multi-agent systems (MAS) frameworks often rely on manually designed and static collaboration graph structures, limiting adaptability and performance. To address these limi…