most citedEnhancing the Performance of Multi-Vehicle Navigation in Unstructured Environments using Hard Sample Mining

1 citations · 1 across the 3 of their papers we have counts for

collaborators

6 papers

cs.GT2025

Policy-Conditioned Policies for Multi-Agent Task Solving

Yue Lin, Shuhui Zhu, Wenhao Li +5

In multi-agent tasks, the central challenge lies in the dynamic adaptation of strategies. However, directly conditioning on opponents' strategies is intractable in the prevalent de…

cs.AI2025

Scaling Agents for Computer Use

Gonzalo Gonzalez-Pumariega, Vincent Tu, Chih-Lun Lee +3

Computer-use agents (CUAs) hold promise for automating everyday digital tasks, but their performance on long-horizon, complex problems remains unreliable. Single-rollout execution…

cs.AI2025

Agent S2: A Compositional Generalist-Specialist Framework for Computer Use Agents

Saaket Agashe, Kyle Wong, Vincent Tu +3

Computer use agents automate digital tasks by directly interacting with graphical user interfaces (GUIs) on computers and mobile devices, offering significant potential to enhance…

cs.DM2025

Revisiting FastMap: New Applications

Ang Li

FastMap was first introduced in the Data Mining community for generating Euclidean embeddings of complex objects. In this dissertation, we first present FastMap to generate Euclide…

cs.RO2025

HWC-Loco: A Hierarchical Whole-Body Control Approach to Robust Humanoid Locomotion

Sixu Lin, Guanren Qiao, Yunxin Tai +3

Humanoid robots, capable of assuming human roles in various workplaces, have become essential to embodied intelligence. However, as robots with complex physical structures, learnin…

cs.MA20241 cited

Enhancing the Performance of Multi-Vehicle Navigation in Unstructured Environments using Hard Sample Mining

Yining Ma, Ang Li, Qadeer Khan +1

Contemporary research in autonomous driving has demonstrated tremendous potential in emulating the traits of human driving. However, they primarily cater to areas with well built r…