9 papers
Copying explains the collective behavior of AI agents in the wild
Giordano De Marzo, Nicola Alboré, David Garcia
In June 2026, thousands of AI agents found that a small public wiki would accept edits from inside their sandboxes, and started using it to help one another pass a timed test. Each…
Network Information Enhances Unreliable News Domain Detection
Raphaela Keßler, Roman David Ventzke, Viola Priesemann +1
Content-based detection of unreliable news is increasingly difficult, as low-reliability sources mimic credible journalism and generative AI makes fabricated content harder to flag…
Conformity Generates Collective Misalignment in AI Agents Societies
Giordano De Marzo, Alessandro Bellina, Claudio Castellano +2
Artificial intelligence safety research focuses on aligning individual language models with human values, yet deployed AI systems increasingly operate as interacting populations wh…
Anticipating Innovation Using Large Language Models
Enrico Maria Fenoaltea, Filippo Santoro, Giordano De Marzo +2
Forecasting innovation, intended as the emergence of new technological combinations, is a fundamental challenge for science and policy. We show that forthcoming combinations leave…
AI agents can coordinate beyond human scale
Giordano De Marzo, Claudio Castellano, David Garcia
Large language models (LLMs) are increasingly deployed in collaborative tasks involving multiple agents, forming an "AI agent society: where agents interact and influence one anoth…
Time-Dependent Urn Models reproduce the full spectrum of novelties discovery
Alessandro Bellina, Giordano De Marzo, Vittorio Loreto
Systems driven by innovation, a pivotal force in human society, present various intriguing statistical regularities, from the Heaps' law to logarithmic scaling or somewhat differen…