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Integrating adaptive human behavior into epidemic models with large language models

Paper recorded by Signals 4 on 2026-08-30 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.AI · 人工智能 · first seen 2026-09-01

Abstract

Infectious disease transmission is shaped by patterns of human interaction, which adapt as epidemic conditions change. Capturing these context-dependent behaviors remains a fundamental challenge for epidemic models. Here, we recast this challenge by using large language models (LLMs) to represent adaptive human behavior within mechanistic epidemic models. We operationalize this idea through Genera

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#279 most recent of 300 cs.AI papers we have recorded · ↑ newer: AGM: Achievement-Grounded Memory for Closed-Loop Agents with Frozen VL · ↓ older: The Emergent Symbolic Structure of Artificial Neural Networks
Cite this page: Integrating adaptive human behavior into epidemic models with large language models: the #279 most recent of 300 cs.AI papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/integrating-adaptive-human-behavior-into-epidemic-models-with-large-language-mod.html
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