TC–RAG: Turing–Complete RAG's Case study on Medical LLM Systems (2025 · 25 citations)
Retrieval-augmented generation can reduce hallucinations and stale knowledge in medical LLMs. However, existing RAG pipelines lack an explicit state variable that tells the system when to stop retrieving, so they can loop without converging or pile up noisy context. The authors propose TC–RAG, which they prove to be…
DFAMS: Dynamic-flow guided Federated Alignment based Multi-prototype Search (2026)
Federated Retrieval (FR) sends a query to several separate knowledge bases instead of one central index. Current FR systems often pick the wrong source or return weak documents when a query is ambiguous or crosses domains. DFAMS addresses this using the Dynamic Information Flow (DIF), meaning the activation paths…

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Updated 2 November 2026