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  <div align="center">
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  <h1>
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- <img src="forge_icon.png" alt="FORGE Logo" height="50" style="vertical-align:middle; margin-right:10px;" />
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  FORGE: A Benchmark for Manufacturing Anomaly Detection with VLMs
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  </h1>
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  </div>
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  <img src="pipeline.png" width="100%" alt="FORGE Pipeline Overview">
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  </div>
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- ## Overview
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-
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- **FORGE** evaluates Vision-Language Models on industrial manufacturing anomaly detection. It covers three core tasks across photo and three-view rendered modalities, plus spatial grounding ablations. All images are embedded -- no external files needed.
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  ## Quick Start
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  ## Citation
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  ```bibtex
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- @article{jianforge2026,
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- title={FORGE: A Benchmark for Manufacturing Anomaly Detection with VLMs},
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  author={Jian, Xiangru and Xu, Hao and Pang, Wei and Zhao, Xinjian and Tao, Chengyu and Zhang, Qixin and Zhang, Xikun and Zhang, Chao and Deng, Guanzhi and Xue, Alex and Du, Juan and Yu, Tianshu and Tarr, Garth and Sun, Qiuzhuang and Tao, Dacheng},
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  year={2026}
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  }
 
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  <div align="center">
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  <h1>
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+ <img src="forge_icon.png" alt="FORGE Logo" height="20" style="vertical-align:middle; margin-right:10px;" />
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  FORGE: A Benchmark for Manufacturing Anomaly Detection with VLMs
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  </h1>
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  </div>
 
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  <img src="pipeline.png" width="100%" alt="FORGE Pipeline Overview">
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  </div>
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  ## Quick Start
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  ## Citation
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  ```bibtex
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+ @article{jian2026forge,
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+ title={FORGE: Fine-grained Multimodal Evaluation for Manufacturing Scenarios},
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  author={Jian, Xiangru and Xu, Hao and Pang, Wei and Zhao, Xinjian and Tao, Chengyu and Zhang, Qixin and Zhang, Xikun and Zhang, Chao and Deng, Guanzhi and Xue, Alex and Du, Juan and Yu, Tianshu and Tarr, Garth and Sun, Qiuzhuang and Tao, Dacheng},
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  year={2026}
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  }