Beyond Hallucination: Adaptive RAG Pipelines with Reinforcement-Guided Retrieval and Knowledge Distillation
Retrieval-Augmented Generation (RAG) has recently emerged as a powerful paradigm for extending large language models (LLMs) with access to external knowledge sources, thereby mitigating issues of hallucination, limited corpus coverage, and outdated information. This paper presents an optimized local knowledge-base RAG...