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States of LLM-generated Texts and Phase Transitions between them
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It is known for some time that autocorrelations of words in human-written texts decay according to a power law. Recent works have also shown that the autocorrelations decay in texts generated by LLMs is qualitatively different from the literary texts. Solid state physics tie the autocorrelations decay laws to the states of matter. In this work, we empirically demonstrate that, depending on the temperature parameter, LLMs can generate text that can be classified as solid, critical state or gas.
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Temperature-driven inversion and nonlinear dynamics in ChatGPT-like AIs
A projection of LLM internal states, trained on some runs, predicts repetition on held-out runs and can be steered to change repetition; the headline entropy maximum is a reparameterization of an occupancy split.
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