A Reproducibility Study of Metacognitive Retrieval-Augmented Generation

This collection of recent arXiv papers focuses on retrieval-augmented generation (RAG), vector search, LLM-enhanced recommenders, and personalized multimodal generation, with several works proposing new architectures, metrics, and evaluation frameworks (MetaRAG reproducibility, HaS speculative retrieval, SmartVector temporal/confidence-aware embeddings, Semantic Recall/Tolerant Recall, SAKE agentic retrieval for GMNER, TF-LLMER for training stability, DPPMG discrete preference tokens, and a policy paper on governable personalization). From a security/privacy viewpoint the set highlights risks: