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cs.CV2026
AgentIAD: Agentic Industrial Anomaly Detection via Adaptive Memory Augmentation
Junwen Miao, Penghui Du, Yingying Fan +5
Industrial anomaly detection (IAD) is challenging due to the subtle and highly localized nature of many defects, which single-pass vision--language models (VLMs) often fail to capt…
cs.CV2026
PROSPECT: Unified Streaming Vision-Language Navigation via Semantic--Spatial Fusion and Latent Predictive Representation
Zehua Fan, Wenqi Lyu, Wenxuan Song +12
Multimodal large language models (MLLMs) have advanced zero-shot end-to-end Vision-Language Navigation (VLN), yet robust navigation requires not only semantic understanding but als…
cs.CV2025
V-Shuffle: Zero-Shot Style Transfer via Value Shuffle
Haojun Tang, Qiwei Lin, Tongda Xu +2
Attention injection-based style transfer has achieved remarkable progress in recent years. However, existing methods often suffer from content leakage, where the undesired semantic…