Expired50% confidenceFactExact time
Hyper-Connections expands the single skip connection of a residual network into multiple learnable connection pathways and enables information interaction between connections through a parameterized fusion mechanism.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
7/2/2026
First Seen
This claim has expired. It is kept for the record and no longer describes the current state.
Valid until: 9/30/2026(expired)
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Related Claims
UnverifiedUnlike the original residual connections, Hyper-Connections introduces learnable parameters, allowing the model to autonomously determine the weight allocation for each connection.79% similarUnverifiedResidual Connections add the input of each layer directly to its output, solving the vanishing gradient problem in deep networks72% similarUnverified跳跃连接通过提供梯度直通路径解决了深度网络训练中的梯度消失问题，使极深网络训练成为可能70% similarUnverified残差连接与层归一化解决了深层网络训练不稳定的问题，使模型可堆叠到数十层67% similarUnverifiedResNet（残差网络）通过跳跃连接解决了深层网络的梯度消失问题，能提取层次化视觉特征66% similar
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