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CISPA Helmholtz Center for Information Security, Saarbr眉cken, Germany
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Multi-agent LLM systems beat single agents not just through diverse opinions, but by dynamically weighting agents based on input-specific competence, turning deliberation into a learned routing mechanism.
Adam's edge over SGD in fine-tuning might boil down to its ability to nimbly escape saddle points and enforce better feature balance, a feat standard gradient descent struggles with.
