5 papers
Scale-Dependent Collective Adaptation in Self-Amending LLM Societies: A Cross-Family Study of Emergent Governance
Kazuya Horibe, Masaomi Hatakeyama, Gen Masumoto +2
We study group decision-making in artificial societies where the rules of play are themselves subject to collective amendment. Using the self-amending game Nomic, we compare multip…
From Human-Level AI Tales to AI Leveling Human Scales
Peter Romero, Fernando MartÃnez-Plumed, Zachary R. Tidler +11
Comparing AI models to "human level" is often misleading when benchmark scores are incommensurate or human baselines are drawn from a narrow population. To address this, we propose…
Capabilities Ain't All You Need: Measuring Propensities in AI
Daniel Romero-Alvarado, Fernando MartÃnez-Plumed, Lorenzo Pacchiardi +11
AI evaluation has primarily focused on measuring capabilities, with formal approaches inspired from Item Response Theory (IRT) being increasingly applied. Yet propensities - the te…
Psychometric Personality Shaping Modulates Capabilities and Safety in Language Models
Stephen Fitz, Peter Romero, Steven Basart +2
Large Language Models increasingly mediate high-stakes interactions, intensifying research on their capabilities and safety. While recent work has shown that LLMs exhibit consisten…
Personality Traits in Large Language Models
Greg Serapio-GarcÃa, Mustafa Safdari, Clément Crepy +6
The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant human-like text. As LLMs in…