18 papers
Activation Quantization of Vision Encoders Needs Prefixing Registers
Seunghyeon Kim, Taesun Yeom, Jinho Kim +3
Large pretrained vision encoders are central to multimodal intelligence, powering applications from on-device vision processing to vision-language models. Since these applications…
Learned Image Compression for Vision-Language-Action Models
Hyeonjun Kim, Jegwang Ryu, Sangbeom Ha +4
Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottleneck for real-time robotic control in b…
Understanding the Effects of Distractors on Reasoning Vision-Language Models
Jiyun Bae, Hyunjong Ok, Sangwoo Mo +1
How does irrelevant information (i.e., distractors) affect test-time scaling in vision-language models (VLMs)? Prior work on text-only language models has shown that textual distra…
Neural Weight Compression for Language Models
Jegwang Ryu, Minkyu Kim, Seungjun Shin +3
Efficient compression of language model weights is increasingly critical as model scale and deployment grow. Yet, most existing methods rely on handcrafted transforms and heuristic…
Over-Alignment vs Over-Fitting: The Role of Feature Learning Strength in Generalization
Taesun Yeom, Taehyeok Ha, Jaeho Lee
Feature learning strength (FLS), i.e., the inverse of the effective output scaling of a model, plays a critical role in shaping the optimization dynamics of neural nets. While its…
Multi-frame Restoration for 10 Hz Lissajous Confocal Laser Endomicroscopy
Minhee Lee, Sangyoon Lee, Jiwook Lee +4
Lissajous confocal laser endomicroscopy (CLE) is a promising solution for high-speed in vivo optical biopsy for handheld scenarios. However, Lissajous scanning traces a resonant tr…