6 papers
Rotated, but How Far? Diagnosing and Improving Object-Rotation Reasoning in VLMs
Zhaochen Wang, Yujun Cai, Huangbo Zou +4
Vision-language models (VLMs) can detect that an object has rotated across views, but cannot reliably tell by how much. We introduce OR-Bench, a fine-grained benchmark for object-r…
Embedded Graph Flows for Categorical Graph Generation
Ethan Ma, Zihan Wang, Chris Siu Yeung Chow +5
Generating categorical graphs requires choosing node and edge types that form a coherent structure without depending on node order. Many graph generators encode categories as fixed…
Testing Deep Learning Library APIs via Cross-Framework Differential Fuzzing
Bin Duan, Ruican Dong, Naipeng Dong +2
Deep learning libraries underpin many safety- and reliability-critical applications, yet existing API-level testing techniques often rely on intra-library properties or CPU--GPU di…
Harnessing LLMs for Document-Guided Fuzzing of Python Libraries
Bin Duan, Tarek Mahmud, Meiru Che +4
Python libraries underpin deep learning, scientific computing, data analysis, and computer vision, making their reliability critical to downstream applications. Testing their APIs…
XAMT: Cross-Framework API Matching for Testing Deep Learning Libraries
Bin Duan, Ruican Dong, Naipeng Dong +2
Deep learning powers critical applications such as autonomous driving, healthcare, and finance, where the correctness of underlying libraries is essential. Bugs in widely used deep…
Harnessing LLMs for Document-Guided Fuzzing of OpenCV Library
Bin Duan, Tarek Mahmud, Meiru Che +4
The combination of computer vision and artificial intelligence is fundamentally transforming a broad spectrum of industries by enabling machines to interpret and act upon visual da…