activity
20242026
collaborators

8 papers

cs.MA2026

PolicyMediator: Multi-Regional Policy Learning through Mediation Agents with Evolving Skills in OPC Ecosystems

Jie Li, Bin Guo, Georgina Curto +3

One-person companies (OPCs) are emerging enterprises operated by individual entrepreneurs through digital platforms and LLM-based AI agents. These highly skilled entrepreneurs are…

cs.AI2026

Proactive Dialogue Policy Optimization via Cognitive-State Transition

Minghui Ma, Mengqi Chen, Bin Guo +1

Proactive dialogue requires agents to continually adapt their policies to user feedback while progressing toward task objectives over multiple turns. To move beyond imitation learn…

cs.AI2026

Cognitive World Model for Progressive BDI/E Trajectory Evaluation of Conversational Agents

Minghui Ma, Bin Guo, Hao Wang +4

As LLM-based conversational agents advance toward increasingly open-ended and interaction-intensive scenarios, task completion alone provides an incomplete assessment of their effe…

cs.AI2026

Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents

Minghui Ma, Bin Guo, Runze Yang +7

Persuasive dialogue requires reasoning about others' latent mental states, a capability known as Theory of Mind (ToM). However, due to reliance on simple prompting strategies and i…

cs.AI2026

Truth or Tribe: How In-group Favoritism Prioritize Facts in Persona Agents

Shijun Lei, Hongyu Wang, Yunji Liang +3

In-group favoritism refers to the phenomena of favoring members of one's in-group over out-group members and is widely observed in numerous social cooperative behaviors. Recently,…

cs.AI2025

MemoCue: Empowering LLM-Based Agents for Human Memory Recall via Strategy-Guided Querying

Qian Zhao, Zhuo Sun, Bin Guo +1

Agent-assisted memory recall is one critical research problem in the field of human-computer interaction. In conventional methods, the agent can retrieve information from its equip…

cs.IR2024

Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference

Jing Du, Zesheng Ye, Bin Guo +5

Recent cross-domain recommendation (CDR) studies assume that disentangled domain-shared and domain-specific user representations can mitigate domain gaps and facilitate effective k…

cs.IR2024

Joint Identifiability of Cross-Domain Recommendation via Hierarchical Subspace Disentanglement

Jing Du, Zesheng Ye, Bin Guo +2

Cross-Domain Recommendation (CDR) seeks to enable effective knowledge transfer across domains. Existing works rely on either representation alignment or transformation bridges, but…