AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Assigning credit to intermediate steps remains a central challenge in training Large Language Models (LLMs) on multi-step reasoning tasks with sparse terminal rewards, and actor-critic methods such as PPO address this by learning value functions to construct token-level advantages. Their effectiveness, however, hinges...
This work proposes Select-ANd-Extract (SANE), a simple yet effective plugin for RAG that performs blueprint-guided query-time evidence extraction, which allows the generator LM to use only compact and structured key information so that it can perform better reasoning.
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