Agent Sociodrama: Social-Dynamics-Guided Persona Recasting for LLM Agent Teams

Key points

• Large language model (LLM) agents are increasingly deployed as teams, yet they fail in characteristically social ways: information holders stay silent, dominant speakers anchor groups on wrong answers, and norm violations go unsanctioned.1
• We then introduce Trajectory-Guided Persona Recasting (TPR), which diagnoses group-dynamic failures from interaction transcripts and social trajectories and recasts agent personas before rerunning the task.1
• On representative distributed-information cooperation and mixed-motive bargaining tasks, we outperform SOTOPIA and AgentVerse in three of four comparisons, by up to 37.5%p in Pareto rate.1
• These results show that validated social trajectories provide actionable signals for repairing LLM agent teams.1

Sources (2)

• [1]Agent Sociodrama: Social-Dynamics-Guided Persona Recasting for LLM Agent Teams
  Hugging Face Daily Papers · Oct 11, 12:00 AM

  We present Agent Sociodrama, a framework for modeling and validating evolving social dynamics in LLM agent teams.

  Large language model (LLM) agents are increasingly deployed as teams, yet they fail in characteristically social ways: information holders stay silent, dominant speakers anchor groups on wrong answers, and norm violations go unsanctioned.

• [2]Agent Sociodrama: Social-Dynamics-Guided Persona Recasting for LLM Agent Teams
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 11, 05:23 PM · same content

Extractive summary: sentences quoted from the sources.