PRL速递：尖峰神经网络中的光滑精确梯度下降
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Goals don't necesserily start to crystallize the moment AI is capable enough to fake alignment
9种神经网络优化算法详解
Why mesa-optimization is less likely under gradient descent than natural selection
This AI Paper Introduces Semantic Backpropagation and Gradient Descent: Advanced Methods for Optimizing Language-Based Agentic Systems
Eliminating Fixed Learning Rate Schedules in Machine Learning: How Schedule-Free AdamW Optimizer Achieves Superior Accuracy and Efficiency Across Diverse Applications
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on Science Beakers and DDT
Generalization of Gradient Descent in Over-Parameterized ReLU Networks: Insights from Minima Stability and Large Learning Rates
