arXiv — cs.AI preprintsInternational9 October 2026
IAD-Unify: Task-Specific Interfaces for Industrial Anomaly Understanding, Segmentation, and Generation
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arXiv:2604.12440v2 Announce Type: replace-cross Abstract: Industrial anomaly inspection requires complementary capabilities: explaining an observed defect, localizing its pixels, and synthesizing a controlled edit. We present IAD-Unify, a unified architecture connecting a multimodal language model (MLLM), dense visual expert, and diffusion editor through task-specific token interfaces. A multi-reference DINOv2 pathway forms a dense anomaly field and compresses its 1,369 cells into 81 structured evidence tokens. Qwen3.5 consumes these tokens for grounded answers and, with 32 task tokens, conver
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