collaborators

6 papers

cs.AI2026

GAIA: A Data Flywheel System for Training GUI Test-Time Scaling Critic Models

Shaokang Wang, Pei Fu, Ruoceng Zhang +7

While Large Vision-Language Models (LVLMs) have significantly advanced GUI agents' capabilities in parsing textual instructions, interpreting screen content, and executing tasks, a…

cs.CV2026

Enhancing Trustworthy GUI Grounding via Self-Critiqued Reinforcement Learning

Shaojie Zhang, Pei Fu, Ruoceng Zhang +8

Autonomous graphical user interface (GUI) agents rely on accurate GUI grounding, which maps language instructions to on-screen coordinates, to execute user commands. However, curre…

cs.AI2026

From Experience to Skill: Multi-Agent Generative Engine Optimization via Reusable Strategy Learning

Beining Wu, Fuyou Mao, Jiong Lin +7

Generative engines (GEs) are reshaping information access by replacing ranked links with citation-grounded answers, yet current Generative Engine Optimization (GEO) methods optimiz…

cs.AI2026

Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking

Jinyi Han, Ying Huang, Ying Liao +11

Large Reasoning Models (LRMs) have achieved impressive performance on challenging tasks, yet their deep reasoning often incurs substantial computational costs. To achieve efficient…

cs.CV2025

BTL-UI: Blink-Think-Link Reasoning Model for GUI Agent

Shaojie Zhang, Ruoceng Zhang, Pei Fu +8

In the field of AI-driven human-GUI interaction automation, while rapid advances in multimodal large language models and reinforcement fine-tuning techniques have yielded remarkabl…

cs.AI2025

OS-MAP: How Far Can Computer-Using Agents Go in Breadth and Depth?

Xuetian Chen, Yinghao Chen, Xinfeng Yuan +12

Computer-using agents have shown strong potential to boost human productivity and enable new application forms across platforms. While recent advances have led to usable applicatio…