1 citations · 3 across the 15 of their papers we have counts for
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Efficient Task Adaptation in Large Language Models: A Survey of Weight-Based, Prompt-Based, and Embedding-Based Adaptations
Jungwon Park, Changin Choi, Jimyeong Kim +2
As large language models are increasingly deployed across diverse downstream tasks, efficient task adaptation has emerged as a central challenge. In response, a wide range of task…
Beyond On-Policy Exploration: Integrating External Policy Rollouts for Reinforcement Learning in Diffusion Language Models
Wonseok Lee, Jimyeong Kim, Jungmin Ko +1
Recent reinforcement learning methods for diffusion large language models (dLLMs) commonly rely on on-policy rollouts generated by the target dLLM itself. When successful on-policy…
Personalized Deep Learning for Short-Term Forecasting of Impending Atrial Fibrillation from Continuous Wearable ECG Signals
Jangwon Suh, Soonil Kwon, Jungmin Ko +4
Background and Objective: Continuous wearable electrocardiogram (ECG) monitoring is increasingly used for ambulatory arrhythmia surveillance, yet forecasting impending atrial fibri…
Orthogonal Negative Guidance in Attention Feature Space for Text-to-Image Generation
Jungmin Ko, Jungwon Park, Jimyeong Kim +3
Text-to-image (T2I) models have become increasingly capable of generating high-quality images. Yet, enforcing the explicit absence of a specified object or attribute remains a fund…
When Confidence Misleads: Suffix Anchoring and Anchor-Proximity Confidence Modulation for Diffusion Language Models
Jungwon Park, Jimyeong Kim, Jungmin Ko +2
Diffusion language models generate text by iteratively selecting and denoising masked positions, making position selection a central inference-time decision. Most training-free met…
Selective Aggregation of Attention Maps Improves Diffusion-Based Visual Interpretation
Jungwon Park, Jungmin Ko, Dongnam Byun +1
Numerous studies on text-to-image (T2I) generative models have utilized cross-attention maps to boost application performance and interpret model behavior. However, the distinct ch…