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A Coding Tutorial on OpenMythos on Recurrent-Depth Transformers with Depth Extrapolation, Adaptive Computation, and Mixture-of-Experts Routing

In this tutorial, we explore the implementation of OpenMythos, a theoretical reconstruction of the Claude Mythos architecture that enables deeper reasoning through iterative computation rather

Editor Editor 10 Min Read

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Efficient Privacy Loss Accounting for Subsampling and Random Allocation

We consider the privacy amplification properties of a sampling scheme in which

Your Synthetic Data Passed Every Test and Still Broke Your Model

looked solid. The KL divergence was well within acceptable ranges. On the

ParaRNN: Large-Scale Nonlinear RNNs, Trainable in Parallel

Recurrent Neural Networks (RNNs) are naturally suited to efficient inference, requiring far

Using a Local LLM as a Zero-Shot Classifier

that “groups are remarkably intelligent, and are often smarter than the smartest

I Simulated an International Supply Chain and Let OpenClaw Monitor It

, I published an article showing how an AI agent could help

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