AIBullisharXiv – CS AI · Apr 67/10
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Textual Equilibrium Propagation for Deep Compound AI Systems
Researchers introduce Textual Equilibrium Propagation (TEP), a new method to optimize large language model compound AI systems that addresses performance degradation in deep, multi-module workflows. TEP uses local learning principles to avoid exploding and vanishing gradient problems that plague existing global feedback methods like TextGrad.