AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Recent advancements in large language models have significantly enhanced the capabilities of agents in modeling long-term conversations. Despite these successes, existing approaches typically adopt a static heuristic paradigm, where information is passively archived without adaptive memory valuation. Consequently, thes...
Lifelong conversational agents rely on memory systems to maintain deep, context-aware interactions with users. However, existing explicit textual memory pipelines suffer from a severe information bottleneck, often losing subtle behavioral patterns and emotional shifts. Furthermore, being typically static post-deploymen...
GRAIN models reasoning as a semantic parsing and tool-execution pipeline, guided by a Structure Invariance Reward, which forces the LLM to learn robust text-to-structure mappings rather than memorizing linguistic artifacts.
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