activity
20232026
most citedUnblind Text Inputs: Predicting Hint-text of Text Input in Mobile Apps via LLM

25 citations · 51 across the 8 of their papers we have counts for

collaborators

8 papers

cs.SE2026

Diagnosis-Driven Automatic Repair for Agentic Workflow via Symbolic Inference

Xuyan Ma, Yawen Wang, Junjie Wang +5

Platform-orchestrated agentic workflows have become a popular paradigm for developing LLM-based applications. However, their reliability remains a major challenge due to the uncert…

cs.AI2025

Demystifying the Lifecycle of Failures in Platform-Orchestrated Agentic Workflows

Xuyan Ma, Xiaofei Xie, Yawen Wang +4

Agentic workflows built on low-code orchestration platforms enable rapid development of multi-agent systems, but they also introduce new and poorly understood failure modes that hi…

cs.MA2025

Robust Multi-agent Communication Based on Decentralization-Oriented Adversarial Training

Xuyan Ma, Yawen Wang, Junjie Wang +5

In typical multi-agent reinforcement learning (MARL) problems, communication is important for agents to share information and make the right decisions. However, due to the complexi…

cs.HC2024★ 25 cited

Unblind Text Inputs: Predicting Hint-text of Text Input in Mobile Apps via LLM

Zhe Liu, Chunyang Chen, Junjie Wang +5

Mobile apps have become indispensable for accessing and participating in various environments, especially for low-vision users. Users with visual impairments can use screen readers…

cs.CV2024★ 1 cited

Adversarial Testing for Visual Grounding via Image-Aware Property Reduction

Zhiyuan Chang, Mingyang Li, Junjie Wang +4

Due to the advantages of fusing information from various modalities, multimodal learning is gaining increasing attention. Being a fundamental task of multimodal learning, Visual Gr…

cs.SE2023★ 4 cited

Make LLM a Testing Expert: Bringing Human-like Interaction to Mobile GUI Testing via Functionality-aware Decisions

Zhe Liu, Chunyang Chen, Junjie Wang +5

Automated Graphical User Interface (GUI) testing plays a crucial role in ensuring app quality, especially as mobile applications have become an integral part of our daily lives. De…

cs.SE2023★ 4 cited

Testing the Limits: Unusual Text Inputs Generation for Mobile App Crash Detection with Large Language Model

Zhe Liu, Chunyang Chen, Junjie Wang +5

Mobile applications have become a ubiquitous part of our daily life, providing users with access to various services and utilities. Text input, as an important interaction channel…

cs.SE2023★ 17 cited

Chatting with GPT-3 for Zero-Shot Human-Like Mobile Automated GUI Testing

Zhe Liu, Chunyang Chen, Junjie Wang +5

Mobile apps are indispensable for people's daily life, and automated GUI (Graphical User Interface) testing is widely used for app quality assurance. There is a growing interest in…