24 citations · 27 across the 4 of their papers we have counts for
4 papers
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…
Seed1.5-Thinking: Advancing Superb Reasoning Models with Reinforcement Learning
ByteDance Seed, :, Jiaze Chen +267
We introduce Seed1.5-Thinking, capable of reasoning through thinking before responding, resulting in improved performance on a wide range of benchmarks. Seed1.5-Thinking achieves 8…
MegaScale: Scaling Large Language Model Training to More Than 10,000 GPUs
Ziheng Jiang, Haibin Lin, Yinmin Zhong +29
We present the design, implementation and engineering experience in building and deploying MegaScale, a production system for training large language models (LLMs) at the scale of…
ATTA: Anomaly-aware Test-Time Adaptation for Out-of-Distribution Detection in Segmentation
Zhitong Gao, Shipeng Yan, Xuming He
Recent advancements in dense out-of-distribution (OOD) detection have primarily focused on scenarios where the training and testing datasets share a similar domain, with the assump…