social-simulation

AgoraSim is a hybrid agent-based modeling framework that combines LLM agents with classical ABM for social reaction analysis. It supports multimodal inputs and structured decision outputs for scenario-oriented simulation.

This paper introduces AgentViSS, a benchmark evaluating visual social intelligence in multimodal social simulation, containing 240 scenarios with aligned visual-textual evidence. Evaluating seven recent MLLMs reveals a gap between local role enactment and visually grounded interaction management.

Introduces Think-Before-Speak (TBS), an interval-based multi-agent simulation framework that separates agents' private internal evaluation from public utterance generation, enabling analysis of the pathway from internal states to public expression in social simulations.

This paper decomposes the faithfulness gap in LLM agents into reasoning→conclusion and conclusion→action steps using Texas Hold'em poker as a controlled environment. It finds that the conclusion→action step is reliable, while the reasoning→conclusion step is the primary source of inconsistency.

This paper studies how persona prompting influences language generated by multimodal large language models in urban perception, finding that captions converge while justifications vary systematically with persona attributes.