4 papers · 1 filter
Seed1.5-VL Technical Report
Dong Guo, Faming Wu, Feida Zhu +194
We present Seed1.5-VL, a vision-language foundation model designed to advance general-purpose multimodal understanding and reasoning. Seed1.5-VL is composed with a 532M-parameter v…
SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation
Yuying Ge, Sijie Zhao, Jinguo Zhu +6
The rapid evolution of multimodal foundation model has demonstrated significant progresses in vision-language understanding and generation, e.g., our previous work SEED-LLaMA. Howe…
Vision Search Assistant: Empower Vision-Language Models as Multimodal Search Engines
Zhixin Zhang, Yiyuan Zhang, Xiaohan Ding +1
Search engines enable the retrieval of unknown information with texts. However, traditional methods fall short when it comes to understanding unfamiliar visual content, such as ide…
Scaling Up Your Kernels: Large Kernel Design in ConvNets towards Universal Representations
Yiyuan Zhang, Xiaohan Ding, Xiangyu Yue
This paper proposes the paradigm of large convolutional kernels in designing modern Convolutional Neural Networks (ConvNets). We establish that employing a few large kernels, inste…