4 papers
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…
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…
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…
A Model-based Multi-Agent Personalized Short-Video Recommender System
Peilun Zhou, Xiaoxiao Xu, Lantao Hu +2
Recommender selects and presents top-K items to the user at each online request, and a recommendation session consists of several sequential requests. Formulating a recommendation…