5 papers
Efficient Quantization-Aware Distillation with Cross-Modal Alignment for Edge Vision-Language Models
Jinwoo Jeon, GyuYeop Do, Yubin Lim +4
Large-scale vision-language models (VLM) such as CLIP enable strong open-vocabulary reasoning, yet deploying these capabilities on resource-constrained edge devices remains challen…
TABX: A High-Throughput Sandbox Battle Simulator for Multi-Agent Reinforcement Learning
Hayeong Lee, JunHyeok Oh, Byung-Jun Lee
The design of environments plays a critical role in shaping the development and evaluation of cooperative multi-agent reinforcement learning (MARL) algorithms. While existing bench…
uCLIP: Parameter-Efficient Multilingual Extension of Vision-Language Models with Unpaired Data
Dahyun Chung, Donghyun Shin, Yujin Sung +3
Contrastive Language-Image Pre-training (CLIP) has demonstrated strong generalization across a wide range of visual tasks by leveraging large-scale English-image pairs. However, it…
Iterative Prompt Refinement for Safer Text-to-Image Generation
Jinwoo Jeon, JunHyeok Oh, Hayeong Lee +1
Text-to-Image (T2I) models have made remarkable progress in generating images from text prompts, but their output quality and safety still depend heavily on how prompts are phrased…
Offline Reinforcement Learning with Penalized Action Noise Injection
JunHyeok Oh, Byung-Jun Lee
Offline reinforcement learning (RL) optimizes a policy using only a fixed dataset, making it a practical approach in scenarios where interaction with the environment is costly. Due…