4 papers
Compression Tells Intelligence: Visual Coding, Visual Token Technology, and the Unification
Xin Jin, Jinming Liu, Yuntao Wei +6
"Compression Tells Intelligence", is supported by research in artificial intelligence, particularly concerning (multimodal) large language models (LLMs/MLLMs), where compression ef…
When MLLMs Meet Compression Distortion: A Coding Paradigm Tailored to MLLMs
Jinming Liu, Zhaoyang Jia, Jiahao Li +4
The increasing deployment of powerful Multimodal Large Language Models (MLLMs), typically hosted on cloud platforms, urgently requires effective compression techniques to efficient…
Knowledge Regularized Negative Feature Tuning of Vision-Language Models for Out-of-Distribution Detection
Wenjie Zhu, Yabin Zhang, Xin Jin +2
Out-of-distribution (OOD) detection is crucial for building reliable machine learning models. Although negative prompt tuning has enhanced the OOD detection capabilities of vision-…
Scene Graph Disentanglement and Composition for Generalizable Complex Image Generation
Yunnan Wang, Ziqiang Li, Zequn Zhang +5
There has been exciting progress in generating images from natural language or layout conditions. However, these methods struggle to faithfully reproduce complex scenes due to the…