arXiv Machine Learning
Adaptive Mean Estimation by In-Context Learning: A Gradient-Flow Analysis
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Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms
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arXiv Machine Learning
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Training-Free Universal Approximation by Prompting Random Transformers
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Gradient Descent as Implicit EM in Distance-Based Neural Models
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Relative Positions Generalize, Absolute Positions Memorize: An Implicit-Bias Account of Length Generalization in Attention
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Transformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression
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arXiv Machine Learning
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Softmax as Linear Attention in the Large-Prompt Regime: a Measure-based Perspective
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