activity
20242026
collaborators

5 papers

cs.AI2026

Qwen-UI-Agent Technical Report: Toward Next-Generation Real-World Centric Foundation GUI Agents

Hanzhang Zhou, Panrong Tong, Xu Zhang +13

GUI agents have the potential to become a general purpose executor over existing digital devices. To advance them toward real-world use, we envision agents that operate reliably on…

cs.AI2025

ProRe: A Proactive Reward System for GUI Agents via Reasoner-Actor Collaboration

Gaole Dai, Shiqi Jiang, Ting Cao +5

Reward is critical to the evaluation and training of large language models (LLMs). However, existing rule-based or model-based reward methods struggle to generalize to GUI agents,…

cs.AI2025

Advancing Mobile GUI Agents: A Verifier-Driven Approach to Practical Deployment

Gaole Dai, Shiqi Jiang, Ting Cao +5

We propose V-Droid, a mobile GUI task automation agent. Unlike previous mobile agents that utilize Large Language Models (LLMs) as generators to directly generate actions at each s…

cs.AI2024

Expand Heterogeneous Learning Systems with Selective Multi-Source Knowledge Fusion

Gaole Dai, Huatao Xu, Yifan Yang +2

Expanding existing learning systems to provide high-quality customized models for more domains, such as new users, is challenged by the limited labeled data and the data and device…

eess.SP2024

SelfReplay: Adapting Self-Supervised Sensory Models via Adaptive Meta-Task Replay

Hyungjun Yoon, Jaehyun Kwak, Biniyam Aschalew Tolera +5

Self-supervised learning has emerged as a method for utilizing massive unlabeled data for pre-training models, providing an effective feature extractor for various mobile sensing a…