Adaptive Contextual Compression and a Hybrid CAG-RAG framework are proposed to compress cached context and selectively retrieve new knowledge, but the evaluation is incomplete and not reproducible.
BART: Denoising Sequence-to-Sequence Pre- Training for Natural Language Generation, Translation, and Compre- hension,
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Enhancing Cache-Augmented Generation (CAG) with Adaptive Contextual Compression for Scalable Knowledge Integration
Adaptive Contextual Compression and a Hybrid CAG-RAG framework are proposed to compress cached context and selectively retrieve new knowledge, but the evaluation is incomplete and not reproducible.