Activation Scaling for Steering and Interpreting Language Models

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Activation Scaling for Steering and Interpreting Language Models

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First and Zeroth-Order Implementations of the Regularized Newton Method with Lazy Approximated Hessians

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Building on Efficient Foundations: Effectively Training LLMs with Structured Feedforward Layers

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Distributed Adaptive Learning Under Communication Constraints

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Dimensionally Tight Bounds for Second-Order Hamiltonian Monte Carlo