Author

Carolina Fortuna

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#artificial intelligence Preprint Sep 2026

Multi-agent Scaling Across Disjunctive and Compensatory Tasks

Multi-agent LLM systems are often expected to improve as team size increases, yet the scaling behavior may depend on task structure. Our central contribution is to introduce Steiner's taxonomy of group tasks as a framework for analyzing multi-agent LLM scaling and focusing the analysis on disjunctive and compensatory t...

Carolina Fortuna, Blaž Bertalanič · 0 citations

#artificial intelligence Preprint Sep 2026

Where Should Agents Live? Energy-Memory Characterization of Agentic AI for the Edge-Cloud Continuum

This work introduces agentic-eCAL, generalizing the Energy Cost of AI Lifecycle (eCAL) metric to directed multi-agent workflows by coupling a closed-form two-rate single-call energy model (compute-bound prefill and memory-bound decode) with 7-layer OSI data transport.

Carolina Fortuna, Vid Hanžel, Tim Strnad et al. · 0 citations