DeepSeek Publishes New Paper by Liang Wenfeng: Proposes a New mHC Architecture to Improve the Stability of Large Model Training
DeepSeek has published a new paper proposing a novel architecture called Manifold-Constrained Hyperconnectivity (mHC), designed to address issues such as training instability and limited scalability in hyperconnectivity (HC) networks caused by the violation of the identity mapping property. By mapping the residual connection space of HC to a specific manifold to restore the identity mapping property, while combining it with rigorous infrastructure optimizations to ensure efficiency, the architecture achieves significant performance improvements and superior scalability. DeepSeek anticipates that mHC, as a flexible and practical extension of HC, will contribute to a deeper understanding of topological architecture design and point to a promising direction for the evolution of foundation models. The paper lists Zhenda Xie, Yixuan Wei, and Huanqi Cao as co-first authors, with Wenfeng Liang also included among the authors.
Source:富途快讯 · Source Link
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