65 citations · 129 across the 15 of their papers we have counts for
5 papers · 1 filter
Network topology shapes consensus and vulnerability in LLM populations
Roberto Passaro, Ariel Flint, Romualdo Pastor-Satorras +2
As large language models (LLMs) are deployed in interacting populations, their collective behaviour depends not only on the models but also on who interacts with whom. Studies of c…
Peer Influence across Heterogeneous AI Models
Frida Nøhr Laustsen, Marie Haahr Petersen, Victoria Popa +4
When two AI agents disagree, who persuades whom? As multi-agent systems increasingly combine language models of different families and sizes, the answer can determine which judgmen…
Indirect tipping: a social attack surface in AI agent populations
Ariel Flint, Luca Maria Aiello, Sara M. Constantino +2
As generative AI agents are deployed at scale, safety will depend not only on technical safeguards and individual model design, but also on collective equilibria that determine how…
Billions of Sketches Reveal Hidden Cultural Variation in Human Concepts
Arianna Pera, Mauro Martino, Nima Dehmamy +3
Claims about the universality of human concepts have been predominantly assessed through linguistic similarity across languages and cultures. However, words are effective as commun…
Failure of contextual invariance in large language models
Sagar Kumar, Ariel Flint, Luca Maria Aiello +1
Standard evaluation practices assume that large language model (LLM) outputs are stable when prompts are embedded in contextually equivalent discourses. Here, we test this assumpti…