5 papers
Cautious Context Steering for Language Model Personalization
Gihoon Kim, Jeyoung Lee, Suhan Woo +4
Personalizing language models (LMs) to individual user preferences is essential for aligning responses with diverse goals and backgrounds. Existing methods typically train a separa…
Swap-guided Preference Learning for Personalized Reinforcement Learning from Human Feedback
Gihoon Kim, Euntai Kim
Reinforcement Learning from Human Feedback (RLHF) is a widely used approach to align large-scale AI systems with human values. However, RLHF typically assumes a single, universal r…
BridgeTA: Bridging the Representation Gap in Knowledge Distillation via Teacher Assistant for Bird's Eye View Map Segmentation
Beomjun Kim, Suhan Woo, Sejong Heo +1
Bird's-Eye-View (BEV) map segmentation is one of the most important and challenging tasks in autonomous driving. Camera-only approaches have drawn attention as cost-effective alter…
Environmental Change Detection for Real-World Change Analysis
Kyusik Cho, Suhan Woo, Hongje Seong +1
Scene Change Detection (SCD) evaluates changes using predefined query-reference (i.e., present-past) image pairs. However, this formulation overlooks a critical dependency: the cor…
ALC: Active and Automated Label Correction for Semantic Segmentation
Youjin Jeon, Kyusik Cho, Suhan Woo +1
Active Label Correction (ALC) has emerged as a promising solution to the high cost and error-prone nature of manual pixel-wise annotation in semantic segmentation, by actively iden…