3 papers
cs.CL2026
ProMediate: A Socio-cognitive framework for evaluating proactive agents in multi-party negotiation
Ziyi Liu, Bahar Sarrafzadeh, Pei Zhou +3
While Large Language Models (LLMs) are increasingly used in agentic frameworks to assist individual users, there is a growing need for agents that can proactively manage complex, m…
cs.CL2026
One Model, All Roles: Multi-Turn, Multi-Agent Self-Play Reinforcement Learning for Conversational Social Intelligence
Bowen Jiang, Taiwei Shi, Ryo Kamoi +5
This paper introduces OMAR: One Model, All Roles, a reinforcement learning framework that enables AI to develop social intelligence through multi-turn, multi-agent conversational s…
cs.AI2024
InterIntent: Investigating Social Intelligence of LLMs via Intention Understanding in an Interactive Game Context
Ziyi Liu, Abhishek Anand, Pei Zhou +2
Large language models (LLMs) have demonstrated the potential to mimic human social intelligence. However, most studies focus on simplistic and static self-report or performance-bas…