AIBullisharXiv – CS AI · Mar 177/10
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In-Context Symbolic Regression for Robustness-Improved Kolmogorov-Arnold Networks
Researchers developed new methods for extracting symbolic formulas from Kolmogorov-Arnold Networks (KANs), addressing a key bottleneck in making AI models more interpretable. The proposed Greedy in-context Symbolic Regression (GSR) and Gated Matching Pursuit (GMP) methods achieved up to 99.8% reduction in test error while improving robustness.