Sneheel Sarangi

arxiv.org

The $\textit{Silicon Society}$ Cookbook: Design Space of LLM-based Social Simulations

Aurélien Bück-Kaeffer

Studies attempting to simulate human behavior with …

2026-04-29

arXiv (prépublication)

arxiv.org

Position: Time to Close The Validation Gap in LLM Social Simulations

Aurélien Bück-Kaeffer

LLM-based social simulations—in which many language model agents interact over multiple turns—are rapidly proliferating across policy an… (voir plus)alysis, epidemiology, and computational social science. Yet the field lacks consensus on how to validate these simulations, with evaluation methods that are sparse, inconsistent, and rarely shared across disciplinary silos. We argue this creates a serious risk: premature deployment of unvalidated simulators in high-stakes domains. Our position is that the field must pivot from expansion to consolidation, prioritizing methodological standardization—shared benchmarks, open data, and reproducible evaluation protocols grounded in social science and complex systems research. We outline a concrete research program organized around specific learning problems/benchmarks, providing a path toward answering the fundamental question: when are LLM social simulations useful modelling objects?

2025-12-31

International Conference on Machine Learning (Accept (regular))

openreview.net

SandboxSocial: A Sandbox for Social Media Using Multimodal AI Agents

Gayatri Krishnakumar

Busra Tugce Gurbuz

Austin Welch

Andreea Musulan

Hao Yu

Ethan Kosak-Hine

Tom Gibbs

Camille Thibault

Dan Zhao

Kellin Pelrine

The online information ecosystem enables influence campaigns of unprecedented scale and impact. We urgently need empirically grounded approa… (voir plus)ches to counter the growing threat of malicious campaigns, now amplified by generative AI. But, developing defenses in real-world settings is impractical. Social system simulations with agents modelled using Large Language Models (LLMs) are a promising alternative approach and a growing area of research. However, existing simulators lack features needed to capture the complex information-sharing dynamics of platform-based social networks. To bridge this gap, we present SandboxSocial, a new simulator that includes several key innovations, mainly: (1) a virtual social media platform (modelled as Mastodon and mirrored in an actual Mastodon server) that enables a realistic setting in which agents interact; (2) an adapter that uses real-world user data to create more grounded agents and social media content; and (3) multi-modal capabilities that enable our agents to interact using both text and images---just as humans do on social media. We make the simulator more useful to researchers by providing measurement and analysis tools that track simulation dynamics and compute evaluation metrics to compare experimental results.

2025-08-15

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (publié)

A Simulation System Towards Solving Societal-Scale Manipulation

Austin Welch

Gayatri K

Dan Zhao

Hao Yu

Ethan Kosak-Hine

Tom Gibbs

Andreea Musulan

Camille Thibault

Busra Tugce Gurbuz

Kellin Pelrine

The rise of AI-driven manipulation poses significant risks to societal trust and democratic processes. Yet, studying these effects in real-w… (voir plus)orld settings at scale is ethically and logistically impractical, highlighting a need for simulation tools that can model these dynamics in controlled settings to enable experimentation with possible defenses. We present a simulation environment designed to address this. We elaborate upon the Concordia framework that simulates offline, `real life' activity by adding online interactions to the simulation through social media with the integration of a Mastodon server. We improve simulation efficiency and information flow, and add a set of measurement tools, particularly longitudinal surveys. We demonstrate the simulator with a tailored example in which we track agents' political positions and show how partisan manipulation of agents can affect election results.

2024-10-16

ArXiv (prépublication)

arxiv.org

Simulation System Towards Solving Societal-Scale Manipulation

Austin Welch

Gayatri K

Dan Zhao

Hao Yu

Tom Gibbs

Ethan Kosak-Hine

Andreea Musulan

Camille Thibault

Busra Tugce Gurbuz