AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Generative reward models (GRMs) are important for LLM optimization. Unlike scalar reward models, GRMs generate natural-language critiques alongside preference judgments, providing finer-grained evaluation signals. Their effectiveness depends heavily on critique reliability. However, existing GRM training typically uses...
Graph Engineering is introduced, an emerging paradigm for next-generation agent systems that provides a unified foundation for organizing complex objectives, orchestrating heterogeneous agents, modeling system dynamics, and enabling scalable agent evolution.
This work proposes LifeMem, a longitudinal memory framework that combines structured life-event retrieval with agent-specific parametric memory for experience integration, and shows that LifeMem improves alignment with human data in terms of response distributions, overall and within-group diversity, and patterns of wi...
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