LLM multi-agent systems augmented with data-driven event triggers and Hawkes processes simulate both micro-level interactions and macroscopic topologies in dynamic email networks for realistic phishing synthesis.
Differentiable agent-based epidemiology
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
The paper introduces Experiment-as-Code Labs as a declarative stack synthesizing AI agents, systems orchestration, and physical lab control for AI-driven discovery.
A SEIRD model with Kalman filtering estimates R0 of 2.76 for a cruise ship hantavirus outbreak and identifies a hidden pool of exposed but undetected cases.
citing papers explorer
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Can LLM Agents Simulate Dynamic Networks? A Case Study on Email Networks with Phishing Synthesis
LLM multi-agent systems augmented with data-driven event triggers and Hawkes processes simulate both micro-level interactions and macroscopic topologies in dynamic email networks for realistic phishing synthesis.
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Experiment-as-Code Labs: A Declarative Stack for AI-Driven Scientific Discovery
The paper introduces Experiment-as-Code Labs as a declarative stack synthesizing AI agents, systems orchestration, and physical lab control for AI-driven discovery.
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Modeling the Impact of Exposed Cases in a Hantavirus Outbreak on a Cruise Ship
A SEIRD model with Kalman filtering estimates R0 of 2.76 for a cruise ship hantavirus outbreak and identifies a hidden pool of exposed but undetected cases.