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DiabAgent: Toward Agentic Physiological Control

Paper recorded by Signals 4 on 2026-11-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-11-02 on arXiv · recorded by Signals 4 on 2026-11-03

Category: cs.AI · 人工智能 · first seen 2026-11-03

Abstract

As pretraining scales, medical language models have advanced rapidly in clinical question answering. Their ability to achieve effective physiological control through sustained intervention still lacks systematic quantitative evaluation. Type 1 diabetes provides a concrete setting: impaired insulin secretion creates dependence on exogenous insulin, with dosing continually adjusted using information

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#28 most recent of 920 cs.AI papers we have recorded · ↑ newer: Tracing the Scientific Discovery Capacity of LLMs to Their Training Da · ↓ older: Four Bridges: Measuring Deception Propensity in a Multi-Agent Game
Cite this page: DiabAgent: Toward Agentic Physiological Control: the #28 most recent of 920 cs.AI papers we have recorded (as of 2026-11-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/diabagent-toward-agentic-physiological-control.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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