English

SAUCE: Synchronous and Asynchronous User-Customizable Environment for Multi-Agent LLM Interaction

Computation and Language 2024-11-07 v1 Human-Computer Interaction

Abstract

Many human interactions, such as political debates, are carried out in group settings, where there are arbitrarily many participants, each with different views and agendas. To explore such complex social settings, we present SAUCE: a customizable Python platform, allowing researchers to plug-and-play various LLMs participating in discussions on any topic chosen by the user. Our platform takes care of instantiating the models, scheduling their responses, managing the discussion history, and producing a comprehensive output log, all customizable through configuration files, requiring little to no coding skills. A novel feature of SAUCE is our asynchronous communication feature, where models decide when to speak in addition to what to say, thus modeling an important facet of human communication. We show SAUCE's attractiveness in two initial experiments, and invite the community to use it in simulating various group simulations.

Keywords

Cite

@article{arxiv.2411.03397,
  title  = {SAUCE: Synchronous and Asynchronous User-Customizable Environment for Multi-Agent LLM Interaction},
  author = {Shlomo Neuberger and Niv Eckhaus and Uri Berger and Amir Taubenfeld and Gabriel Stanovsky and Ariel Goldstein},
  journal= {arXiv preprint arXiv:2411.03397},
  year   = {2024}
}

Comments

https://github.com/Deep-Cognition-Lab/SAUCE

R2 v1 2026-06-28T19:49:23.446Z