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Stochastic Thermodynamics for Autoregressive Generative Models: A Non-Markovian Perspective
Autoregressive generative models -- including Transformers, recurrent neural networks, classical Kalman filters, state space models, and Mamba -- all generate sequences by sampling each output from a deterministic summary of the past, producing genuinely non-Markovian observed processes. We develop
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