3 papers
cs.CV2025
ERGO: Efficient High-Resolution Visual Understanding for Vision-Language Models
Jewon Lee, Wooksu Shin, Seungmin Yang +5
Efficient processing of high-resolution images is crucial for real-world vision-language applications. However, existing Large Vision-Language Models (LVLMs) incur substantial comp…
cs.SD2025
When Good Sounds Go Adversarial: Jailbreaking Audio-Language Models with Benign Inputs
Hiskias Dingeto, Taeyoun Kwon, Dasol Choi +5
As large language models (LLMs) become increasingly integrated into daily life, audio has emerged as a key interface for human-AI interaction. However, this convenience also introd…
cs.CV2025
Efficient LLaMA-3.2-Vision by Trimming Cross-attended Visual Features
Jewon Lee, Ki-Ung Song, Seungmin Yang +6
Visual token reduction lowers inference costs caused by extensive image features in large vision-language models (LVLMs). Unlike relevant studies that prune tokens in self-attentio…