[2604.06262] From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning

Quantitative Biology > Quantitative Methods arXiv:2604.06262 (q-bio) [Submitted on 7 Apr 2026] Title:From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning Authors:Chuang Zhao, Hongke Zhao, Xiaofang Zhou, Xiaomeng Li View a PDF of the paper titled From Exposure to Internalization: Dual-Stream Calibration for In-context Clinical Reasoning, by Chuang Zhao and 3 other authors View PDF HTML (experimental) Abstract:Contextual clinical reasoning demands robust inference grounded in complex, heterogeneous clinical records. While state-of-the-art fine-tuning, in-context learning (ICL), and retrieval-augmented generation (RAG) enable knowledge exposure, they often fall short of genuine contextual internalization: dynamically adjusting a model's internal representations to the subtle nuances of individual cases at inference time. To address this, we propose Dual-Stream Calibration (DSC), a test-time training framework that transcends superficial knowledge exposure to achieve deep internalization during inference. DSC facilitates input internalization by synergistically aligning two calibration streams. Unlike passive context exposure, the Semantic Calibration Stream enforces a deliberative reflection on core evidence, internalizing semantic anchors by minimizing entropy to stabilize generative trajectories. Simultaneously, the Structural Calibration Stream assimilates latent inferential dependencies through an iterative meta-learning objective. B...