Phase Transition
Phase transitions, abrupt changes in a system's behavior in response to parameter shifts, are a focus of intense research across diverse scientific fields. Current investigations utilize machine learning techniques, including large language models and neural networks, to detect and characterize these transitions in various contexts, from physical systems and biological processes to the training dynamics of artificial neural networks and even social phenomena like civil unrest. Understanding these transitions offers crucial insights into the underlying mechanisms governing complex systems and has significant implications for improving model performance, prediction accuracy, and the design of more efficient algorithms.
Papers
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