AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Multi-agent reasoning with large language models (LLMs) raises a central question for collective decision-making: when agents disagree, whose decision should be trusted? Resolving such disagreements is difficult because agents'decisions are susceptible to non-semantic biases such as majority pressure and response-style...
Across diverse tasks and roles, model scales, and MoE architectures, DEP achieves better overall accuracy than static pruning and merging baselines, and generalizes to workflows unseen in training without retraining.
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