3 papers
cs.LG2025
Understanding Transformer from the Perspective of Associative Memory
Shu Zhong, Mingyu Xu, Tenglong Ao +1
In this paper, we share our reflections and insights on understanding Transformer architectures through the lens of associative memory--a classic psychological concept inspired by…
cs.CV2025
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…
cs.CV2025
Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens
Kaihang Pan, Wang Lin, Zhongqi Yue +6
Recent endeavors in Multimodal Large Language Models (MLLMs) aim to unify visual comprehension and generation by combining LLM and diffusion models, the state-of-the-art in each ta…