这项研究跳出了先有传统视觉 backbone，再接语言模型的常规路径，直接从text-only LLM初始化vision encoder。 可一旦任务变成文档阅读、图表理解、细粒度描述、多图关系判断，甚至长视频里的时间定位，模型真正需要保住的，恰恰是那些不该太早被抹平的局部结构、空间关系和时序细节。

Abstract: With the development of face forgery technology, fake faces are rampant, threatening the security and authenticity of many fields. Therefore, it is of great significance to study face ...

CLIP is one of the most important multimodal foundational models today, aligning visual and textual signals into a shared feature space using a simple contrastive learning loss on large-scale ...

An unexpected revisit to my earlier post on mouse encoder hacking sparked a timely opportunity to reexamine quadrature encoders, this time with a clearer lens and a more targeted focus on their signal ...

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. For anyone versed in the technical underpinnings of LLMs, this ...

Contrastive Language-Image Pre-training (CLIP) has become important for modern vision and multimodal models, enabling applications such as zero-shot image classification and serving as vision encoders ...

Researchers have tested a method for rewriting blocked prompts in text-to-video systems so they slip past safety filters without changing their meaning. The approach worked across several platforms, ...

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more The University of California, Santa Cruz ...