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Nai-Peng Dong

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#artificial intelligence Preprint Oct 2026

Rotated, but How Far? Diagnosing and Improving Object-Rotation Reasoning in VLMs

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-rotation reasoning with eight tasks covering rotation detection, rotation magnitude estimation, and multi-view rotation reasoning. Across 12...

Zhao-Chen Wang, Yu-Jun Cai, Huang-Bo Zou et al. · 0 citations
#machine learning Preprint Sep 2026

Embedded Graph Flows for Categorical Graph Generation

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 one-hot vectors, which can impose an artificial geometry in which categories are equidistant. We propose Embedded Graph Flows (EGF), a gene...

Ethan Ma, Zi-Han Wang, C. Chow et al. · 0 citations
Preprint Aug 2026

Testing Deep Learning Library APIs via Cross-Framework Differential Fuzzing

Xamt, a cross-framework differential fuzzing approach for deep learning library APIs, constructs and tests execution-validated groups of APIs intended to implement equivalent operations across seven libraries.

Bin Duan, Rui Dong, Nai-Peng Dong et al. · 0 citations
Preprint Aug 2026

Harnessing LLMs for Document-Guided Fuzzing of Python Libraries

VistaFuzz is introduced, a document-guided fuzzing technique that uses a locally served open-sourced LLM to extract parameter specifications from API documents and generate inputs that satisfy both parameter constraints and inter-parameter dependencies.

Bin Duan, Tarek Mahmud, Meiru Che et al. · 0 citations

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