Author

Kejun Wu

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Preprint Aug 2026

DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection

Few-shot anomaly detection (FSAD) has recently benefited from vision-language models such as CLIP, which enable anomaly de?tection by aligning visual features with text descriptions of normal and abnormal states. However, existing methods typically rely on static text prompts that are applied uniformly across the entir...

Wen-Yang Liu, Tianyi Liu, Dongshuo Zhang et al. · 0 citations

Review Aug 2026

AesCanvas: A Large-Scale Dataset and Benchmark for Aesthetic Critique and Contextual Suitability

Recent advances in Multimodal Large Language Models (MLLMs) have extended Image Aesthetic Assessment (IAA) beyond scalar scores toward interpretable critique and guidance. Yet existing benchmarks mainly assess intrinsic visual quality or fixed domain criteria, leaving open whether an appealing image is appropriate for...

Xuan-Wei Hu, Hao-Yue Dong, Kejun Wu et al. · 0 citations

Preprint Aug 2026

FLM: Frequency-Aware Language Models for Generative Image Compression

FLM is a frequency-aware language model that improves compression efficiency through frequency-domain probabilistic modeling while retaining deterministic reconstruction and is validated to be applicable to the lossless recompression task with competitive performance.

Jia-Run Chen, Ke-Jun Wu, Li Li et al. · 0 citations