9 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…
HALO: Heterogeneous Admission through Localized Obligations for Safe Agentic Execution
Taewoo Park, Kyeonghyun Yoo, Kiseok Kim +2
Recent agentic AI systems may return a heterogeneous response containing notices, requests, handoffs, and actions. Conditions can change before external use, so components from the…
Arm2Air: Cross-Embodiment Skeleton Transfer for 3D Relay Formation
Dohun Lee, Kyeonghyun Yoo, Seokmin Kim +3
Unmanned aerial vehicle (UAV) relay networks can restore connectivity after communication infrastructure is damaged. Urban relay placement is difficult because line-of-sight blocka…
Cross-IP Request Coalescing: Relocating the Fan-out Point in Virtualized I/O
Kiseok Kim, Hyeontae Joo, Hwangnam Kim
Cloud data centers rely on virtualization technologies to serve AI workloads in multi-tenant environments. With the growing scale of data-intensive AI workloads, the performance of…
LAEI: Layered Autonomous Edge Intelligence Framework for Robust UAV Swarm Operations
Changmin Park, Wooyong Jung, Hwangnam Kim
Autonomous UAV swarms require scalable coordination mechanisms that maintain mission performance under limited communication, environmental uncertainty, and component failures. Cen…
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…
From Numbers to Prompts: A Cognitive Symbolic Transition Mechanism for Lightweight Time-Series Forecasting
Namkyung Yoon, Hwangnam Kim
Large language models have achieved remarkable success in time series prediction tasks, but their substantial computational and memory requirements limit deployment on lightweight…