Unverified50% confidenceBenchmarkExact time
Activation-swapping on the selected neurons flips model predictions at a rate an order of magnitude higher than an equally sized set of random neurons, and this holds in both directions.
1
Sources
50%
Confidence
Long-term
Relevance
9/28/2026
First Seen
Sources
Related Entities
Related Claims
Unverified神经网络层数越多、神经元越多，模型的表达能力越强，但也越容易出现过拟合74% similarUnverified神经元激活的度量方式包括原始激活值、激活频率和相对激活强度等多种，反映模型内部不同的信息组织逻辑73% similarUnverifiedNeural cellular automata replace the update rules of traditional cellular automata with trainable neural networks, enabling the evolution of cell states to be learned from data.72% similarUnverifiedNeural networks are more like something that is 'grown' rather than 'designed,' fine-tuned from a random state by providing data and learning algorithms.71% similarVerifiedReverse-mode automatic differentiation in neural network training is the mathematical essence of backpropagation, because the number of parameters far exceeds the output dimensionality of the loss value.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/955589API
curl https://kongchang.com/api/v1/knowledge/claims/955589MCP
get_claim(id=955589)