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ResearcharXiv1d ago

TRACE: Tree-Relational Structure Enhancement Improves Oncology LLMs

TRACE introduces a tree-relational structure approach for grounding oncology LLM predictions in explicit medical knowledge, separating offline structure learning from online inference and improving accuracy and interpretability over standard RAG techniques.

RAGoncologyLLM

ResearcharXiv1d ago

Entropy-Driven Adaptive Router (EDAR): Hybrid Routing for RAG and Long-Context LLMs

EDAR is a framework that adaptively routes queries between retrieval-augmented generation (RAG) and full long-context (LC) processing in large language models. It leverages predictive entropy to balance accuracy and computational cost, providing a practical path to efficient LLM deployment for long-context tasks.

RAGRAGlong-context