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Arxiv
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Scaling Test-Time Inference with Policy-Optimized, Dynamic Retrieval-Augmented Generation via KV Caching and Decoding
- A comprehensive framework that enhances Retrieval-Augmented Generation (RAG) systems is presented.
- The framework integrates Policy-Optimized Retrieval-Augmented Generation (PORAG) and Adaptive Token-Layer Attention Scoring (ATLAS).
- The techniques improve the utilization and relevance of retrieved content, enhancing factual accuracy and response quality.
- The framework demonstrates efficiency, scalability, and reduced hallucinations in RAG systems.
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