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cs.CL2026
Taming Visual Neglect: A Variational Information Bottleneck Framework for Adaptive Attention in Multimodal In-Context Learning
Kaito Tanaka, Yuji Nishimura, Keisuke Matsuda +1
Large vision-language models exhibit strong in-context learning (ICL) capabilities, yet when and why visual context helps multimodal ICL remains poorly understood. Empirical studie…
cs.CL2025
High-Fidelity Pseudo-label Generation by Large Language Models for Training Robust Radiology Report Classifiers
Brian Wong, Kaito Tanaka
Automated labeling of chest X-ray reports is essential for enabling downstream tasks such as training image-based diagnostic models, population health studies, and clinical decisio…
cs.CL2024
Leveraging Language Models for Emotion and Behavior Analysis in Education
Kaito Tanaka, Benjamin Tan, Brian Wong
The analysis of students' emotions and behaviors is crucial for enhancing learning outcomes and personalizing educational experiences. Traditional methods often rely on intrusive v…