3 papers
cs.CV2025
Diagnosing Vision Language Models' Perception by Leveraging Human Methods for Color Vision Deficiencies
Kazuki Hayashi, Shintaro Ozaki, Yusuke Sakai +2
Large-scale Vision-Language Models (LVLMs) are being deployed in real-world settings that require visual inference. As capabilities improve, applications in navigation, education,…
cs.CL2025
IterKey: Iterative Keyword Generation with LLMs for Enhanced Retrieval Augmented Generation
Kazuki Hayashi, Hidetaka Kamigaito, Shinya Kouda +1
Retrieval-Augmented Generation (RAG) has emerged as a way to complement the in-context knowledge of Large Language Models (LLMs) by integrating external documents. However, real-wo…
cs.CL2024
Understanding the Impact of Confidence in Retrieval Augmented Generation: A Case Study in the Medical Domain
Shintaro Ozaki, Yuta Kato, Siyuan Feng +8
Retrieval Augmented Generation (RAG) complements the knowledge of Large Language Models (LLMs) by leveraging external information to enhance response accuracy for queries. This app…