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Meta-reasoning, an inference-time harness that makes agentic meta-reasoning an explicit and structured reasoning process, keeps improving over the tested budget ranges where direct control plateaus, though its overhead can hurt at small budgets.
This tutorial provides an in-depth treatment of modern RAG based on AI-facilitated systematic analysis of ~2000 recent papers (2020--2026) and traces the RAG pipeline from its modular foundations through graph-enhanced reasoning to the latest RL-driven agentic architectures, covering each stage.
Retrieval-Augmented Generation (RAG) has emerged as the dominant strategy to ground LLM outputs in retrieved evidence to reduce hallucinations and increase factuality, yet RAG itself introduces new challenges: noisy retrieval, knowledge conflicts, and wasted computation from unnecessary retrieval. This tutorial provide...
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