6 papers
In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents
Zhen Tan, Jun Yan, I-Hung Hsu +12
Large Language Models (LLMs) have made significant progress in open-ended dialogue, yet their inability to retain and retrieve relevant information from long-term interactions limi…
Knowledge-Driven Feature Selection and Engineering for Genotype Data with Large Language Models
Joseph Lee, Shu Yang, Jae Young Baik +8
Predicting phenotypes with complex genetic bases based on a small, interpretable set of variant features remains a challenging task. Conventionally, data-driven approaches are util…
Symbiotic Cooperation for Web Agents: Harnessing Complementary Strengths of Large and Small LLMs
Ruichen Zhang, Mufan Qiu, Zhen Tan +7
Web browsing agents powered by large language models (LLMs) have shown tremendous potential in automating complex web-based tasks. Existing approaches typically rely on large LLMs…
Path-RAG: Knowledge-Guided Key Region Retrieval for Open-ended Pathology Visual Question Answering
Awais Naeem, Tianhao Li, Huang-Ru Liao +9
Accurate diagnosis and prognosis assisted by pathology images are essential for cancer treatment selection and planning. Despite the recent trend of adopting deep-learning approach…
FairSkin: Fair Diffusion for Skin Disease Image Generation
Ruichen Zhang, Yuguang Yao, Zhen Tan +6
Image generation is a prevailing technique for clinical data augmentation for advancing diagnostic accuracy and reducing healthcare disparities. Diffusion Model (DM) has become a l…
DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature
Dawei Li, Shu Yang, Zhen Tan +10
Recent advancements in large language models (LLMs) have achieved promising performances across various applications. Nonetheless, the ongoing challenge of integrating long-tail kn…