1 citations · 1 across the 5 of their papers we have counts for
5 papers
SAIL: Structure-Aware Interpretable Learning for Anatomy-Aligned Post-hoc Explanations in OCT
Tienyu Chang, Tianhao Li, Ruogu Fang +2
Optical coherence tomography (OCT), a commonly used retinal imaging modality, plays a central role in retinal disease diagnosis by providing high-resolution visualization of retina…
Mapping from Meaning: Addressing the Miscalibration of Prompt-Sensitive Language Models
Kyle Cox, Jiawei Xu, Yikun Han +6
An interesting behavior in large language models (LLMs) is prompt sensitivity. When provided with different but semantically equivalent versions of the same prompt, models may prod…
GuideLLM: Exploring LLM-Guided Conversation with Applications in Autobiography Interviewing
Jinhao Duan, Xinyu Zhao, Zhuoxuan Zhang +12
Although Large Language Models (LLMs) succeed in human-guided conversations such as instruction following and question answering, the potential of LLM-guided conversations-where LL…
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…
Improving Fairness of Automated Chest X-ray Diagnosis by Contrastive Learning
Mingquan Lin, Tianhao Li, Zhaoyi Sun +5
Purpose: Limited studies exploring concrete methods or approaches to tackle and enhance model fairness in the radiology domain. Our proposed AI model utilizes supervised contrastiv…