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+ ---
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+ license: apache-2.0
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+ language:
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+ - en
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+ tags:
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+ - multimodal
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+ - image-restoration
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+ - unified-model
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+ - BAGEL
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+ - VLM
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+ pipeline_tag: image-text-to-text
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+ ---
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+
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+ # CLEAR: Unlocking Generative Potential for Degraded Image Understanding
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+
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+ CLEAR is a unified multimodal model that leverages generative capabilities (image restoration) to improve visual understanding of degraded images. It introduces an **interleaved reasoning** paradigm where the model adaptively decides whether to invoke image restoration before answering.
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+
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+ > [[Paper]](https://arxiv.org/abs/2604.04780) | [[Code]](https://github.com/haoxiangzhao12138/CLEAR) | [[Project Page]](https://haoxiangzhao12138.github.io/CLEAR/) | [[MMD-Bench]](https://huggingface.co/datasets/CUDAOUTOFMEMORY/MMD-Bench)
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+
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+ ## Citation
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+
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+ ```bibtex
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+ @misc{hao2026clearunlockinggenerativepotential,
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+ title={CLEAR: Unlocking Generative Potential for Degraded Image Understanding in Unified Multimodal Models},
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+ author={Xiangzhao Hao and Zefeng Zhang and Zhenyu Zhang and Linhao Yu and Yao Chen and Yiqian Zhang and Haiyun Guo and Shuohuan Wang and Yu Sun},
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+ year={2026},
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+ eprint={2604.04780},
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+ archivePrefix={arXiv},
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+ primaryClass={cs.CV},
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+ url={https://arxiv.org/abs/2604.04780},
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+ }
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+ ```