5 papers
PARALLEL: A Prefrontal-Aligned Reinforcement inspired Approach for Language-Model Learning under Explicit Limits
Namkyung Yoon, Sanghong Kim, Hwangnam Kim
Recent language models achieve strong performance across a variety of tasks, but conventional adaptation applies updates uniformly across training samples regardless of their local…
KD-EKF: Knowledge-Distilled Adaptive Covariance EKF for Robust UWB/PDR Indoor Localization
Kyeonghyun Yoo, Wooyong Jung, Namkyung Yoon +3
Ultra-wideband (UWB) indoor localization provides centimeter-level accuracy and low latency, but its measurement reliability degrades severely under Non-Line-of-Sight (NLOS) condit…
Beyond Learning: A Training-Free Alternative to Model Adaptation
Namkyung Yoon, Kyeonghyun Yoo, Wooyong Jung +2
Despite the continuous research and evolution of language models, they sometimes underperform previous versions. Existing approaches to overcome these challenges are resource-inten…
Contrastive Domain Generalization for Cross-Instrument Molecular Identification in Mass Spectrometry
Seunghyun Yoo, Sanghong Kim, Namkyung Yoon +1
Identifying molecules from mass spectrometry (MS) data remains a fundamental challenge due to the semantic gap between physical spectral peaks and underlying chemical structures. E…
Conditional Generative Framework with Peak-Aware Attention for Robust Chemical Detection under Interferences
Namkyung Yoon, Sanghong Kim, Hwangnam Kim
Gas chromatography-mass spectrometry (GC-MS) is a widely used analytical method for chemical substance detection, but measurement reliability tends to deteriorate in the presence o…