activity
20232026
most citedTackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination

3 citations · 6 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AI2026

CoNav-UAV: Cooperative Dual-Altitude Aerial Navigation via Stackelberg Learning

Junru Song, Wenhao Zhang, Yang Yang +7

Target-oriented vision-and-language navigation (VLN) on aerial platforms is attracting growing attention for missions such as disaster rescue, infrastructure inspection, and securi…

cs.AI2026

HiMAC: Hierarchical Macro-Micro Learning for Long-Horizon LLM Agents

Hongbo Jin, Rongpeng Zhu, Jiayu Ding +2

Large language model (LLM) agents have recently demonstrated strong capabilities in interactive decision-making, yet they remain fundamentally limited in long-horizon tasks that re…

cs.LG2025

Context Value Informed In-Context Reinforcement Learning

Wenhao Zhang, Shao Zhang, Xihuai Wang +2

In-context reinforcement learning (ICRL) has emerged as an effective paradigm for test time adaptation to unseen tasks without parameter updates. However, existing ICRL methods can…

cs.AI2025

Leveraging Dual Process Theory in Language Agent Framework for Real-time Simultaneous Human-AI Collaboration

Shao Zhang, Xihuai Wang, Wenhao Zhang +10

Agents built on large language models (LLMs) have excelled in turn-by-turn human-AI collaboration but struggle with simultaneous tasks requiring real-time interaction. Latency issu…

cs.HC2024★ 2 cited

Mutual Theory of Mind in Human-AI Collaboration: An Empirical Study with LLM-driven AI Agents in a Real-time Shared Workspace Task

Shao Zhang, Xihuai Wang, Wenhao Zhang +6

Theory of Mind (ToM) significantly impacts human collaboration and communication as a crucial capability to understand others. When AI agents with ToM capability collaborate with h…

cs.MA2024

Aligning Individual and Collective Objectives in Multi-Agent Cooperation

Yang Li, Wenhao Zhang, Jianhong Wang +4

Among the research topics in multi-agent learning, mixed-motive cooperation is one of the most prominent challenges, primarily due to the mismatch between individual and collective…

cs.AI2023★ 1 cited

ZSC-Eval: An Evaluation Toolkit and Benchmark for Multi-agent Zero-shot Coordination

Xihuai Wang, Shao Zhang, Wenhao Zhang +4

Zero-shot coordination (ZSC) is a new cooperative multi-agent reinforcement learning (MARL) challenge that aims to train an ego agent to work with diverse, unseen partners during d…

cs.AI2023★ 3 cited

Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination

Yang Li, Shao Zhang, Jichen Sun +5

Securing coordination between AI agent and teammates (human players or AI agents) in contexts involving unfamiliar humans continues to pose a significant challenge in Zero-Shot Coo…