3 papers
cs.AI2026
Semantic Uncertainty-Guided Orchestration in Hierarchical Multi-Agent Systems
John Knowlton, Aritra Guha, Risto Miikkulainen
As large language model (LLM)-based multi-agent systems become increasingly capable, coordinating agents under uncertainty becomes a fundamental challenge. Existing orchestration s…
cs.CY2026
The Open Source Economic Index of AI Adoption and Capability
Seamus Somerstep, Aritra Guha, Divesh Srivastava +1
We work towards measuring both AI adoption and the capability of AI to perform discrete labor tasks across various occupations. To measure adoption, we develop an open-source econo…
cs.AI2026
Consistency as a Testable Property: Statistical Methods to Evaluate AI Agent Reliability
Harsh Raj, Niranjan Orkat, Suvrorup Mukherjee +3
This paper establishes a rigorous measurement science for AI agent reliability, providing a foundational framework for quantifying consistency under semantically preserving perturb…