activity
20232026
most citedControlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach

3 citations · 3 across the 7 of their papers we have counts for

collaborators

7 papers

cs.RO2026

RoboStriker: Latent-Space Strategic Games for Autonomous Humanoid Boxing

Kangning Yin, Kaige Liu, Zhe Cao +9

Achieving human-level competitive intelligence and physical agility in humanoid robots remains a profound challenge, particularly in contact-rich and highly dynamic tasks such as b…

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.RO2026

Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales

Yang Li, Feng Xue, Fan Mo +6

Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existing approaches often address the…

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.RO2025

AT-Drone: Benchmarking Adaptive Teaming in Multi-Drone Pursuit

Yang Li, Junfan Chen, Feng Xue +5

Adaptive teaming-the capability of agents to effectively collaborate with unfamiliar teammates without prior coordination-is widely explored in virtual video games but overlooked i…

cs.RO2024

HOLA-Drone: Hypergraphic Open-ended Learning for Zero-Shot Multi-Drone Cooperative Pursuit

Yang Li, Dengyu Zhang, Junfan Chen +4

Zero-shot coordination (ZSC) is a significant challenge in multi-agent collaboration, aiming to develop agents that can coordinate with unseen partners they have not encountered be…

cs.AI2023★ 3 cited

Controlling Large Language Model-based Agents for Large-Scale Decision-Making: An Actor-Critic Approach

Bin Zhang, Hangyu Mao, Jingqing Ruan +9

The remarkable progress in Large Language Models (LLMs) opens up new avenues for addressing planning and decision-making problems in Multi-Agent Systems (MAS). However, as the numb…