18 citations · 20 across the 6 of their papers we have counts for
7 papers
Where Did It Go Wrong? Capability-Oriented Failure Attribution for Vision-and-Language Navigation Agents
Jianming Chen, Yawen Wang, Junjie Wang +4
Embodied agents in safety-critical applications such as Vision-Language Navigation (VLN) rely on multiple interdependent capabilities (e.g., perception, memory, planning, decision)…
EXPEREPAIR: Dual-Memory Enhanced LLM-based Repository-Level Program Repair
Fangwen Mu, Junjie Wang, Lin Shi +3
Automatically repairing software issues remains a fundamental challenge at the intersection of software engineering and AI. Although recent advances in Large Language Models (LLMs)…
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…
The Metamorphosis: Automatic Detection of Scaling Issues for Mobile Apps
Yuhui Su, Chunyang Chen, Junjie Wang +4
As the bridge between users and software, Graphical User Interface (GUI) is critical to the app accessibility. Scaling up the font or display size of GUI can help improve the visua…
Putting Them under Microscope: A Fine-Grained Approach for Detecting Redundant Test Cases in Natural Language
Zhiyuan Chang, Mingyang Li, Junjie Wang +2
Natural language (NL) documentation is the bridge between software managers and testers, and NL test cases are prevalent in system-level testing and other quality assurance activit…
VTLayout: Fusion of Visual and Text Features for Document Layout Analysis
Shoubin Li, Xuyan Ma, Shuaiqun Pan +3
Documents often contain complex physical structures, which make the Document Layout Analysis (DLA) task challenging. As a pre-processing step for content extraction, DLA has the po…
PEL-BERT: A Joint Model for Protocol Entity Linking
Shoubin Li, Wenzao Cui, Yujiang Liu +4
Pre-trained models such as BERT are widely used in NLP tasks and are fine-tuned to improve the performance of various NLP tasks consistently. Nevertheless, the fine-tuned BERT mode…