AINeutralarXiv – CS AI · 9h ago6/10
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LLM-Guided Open Hypothesis Learning from Autonomous Scanning Probe Microscopy Experiments
Researchers have developed an open hypothesis-learning framework that combines symbolic regression with large language models to autonomously discover physical laws from scanning probe microscopy experiments. Rather than optimizing within predefined objectives, the system generates and evaluates candidate physical models directly from experimental data, demonstrating success in characterizing ferroelectric domain switching behavior.