AI Research
TRACE: Deployable Tree-Relational Structure Enhancement for Oncology LLMs
Improving clinical oncology LLMs by integrating hierarchical medical grounding into model architecture.
Large language models are increasingly used in oncology applications, but their predictions are often weakly grounded in explicit medical structure. We present TRACE, a deployable tree-relational enhancement framework for oncology LLMs. TRACE separates expensive offline structure...
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ArXiv CS.CL
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ArXiv CS.CL
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TRACE bridges the critical gap between raw language generation and the rigorous hierarchical requirements of clinical oncology data. By decoupling structure from computation, this framework enables safer, more grounded medical decision support without sacrificing the efficiency of current LLMs.
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