MIRAGE25: ACM MM25 Multimodal Interleaved Reasoning and Generation Challenge
Chen, Dong Gao, Fei Hu, Zhengqing Chang, Xiaojun
Chen, Dong
Gao, Fei
Hu, Zhengqing
Chang, Xiaojun
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Department
Computer Vision
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Type
Conference proceeding
Date
2025
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Language
English
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Abstract
We introduce the MIRAGE Challenge, a comprehensive benchmark for multimodal interleaved reasoning and generation, to ACM MM 2025. The challenge aims to evaluate models' abilities to both understand and generate content from complex, multimodal contexts consisting of interlinked images and text. The challenge is accompanied by the MIRAGE Dataset, comprising 263.7K high-quality instruction-response pairs across 35 tasks in two tracks: reasoning and generation. These pairs span 20 diverse scenarios, from surveillance to artistic creation, ensuring broad coverage. The challenge includes seven major categories: Multi-Image Reasoning, Document and Knowledge-Based Understanding, Interactive Multi-Modal Communication, Multi-Image Discrimination, Sequential Visual Generation, Material-based Image Coloring, and Visual Reference Customization. Hosting the MIRAGE Challenge at MM 2025 will drive significant progress in unified multimodal learning and inspire broad involvement in developing more versatile AI systems capable of both understanding and generating multimodal content. Challenge details and participation information are available at https://mm25mirage.github.io/mirage/.
Citation
D. Chen, F. Gao, Z. Hu, and X. Chang, “MIRAGE25: ACM MM25 Multimodal Interleaved Reasoning and Generation Challenge,” in Proceedings of the 31st ACM International Conference on Multimedia (ACM MM ’25), Singapore, Oct. 2025, pp., doi: 10.1145/3746027.3762000.
Source
Proceedings of the 33rd ACM International Conference on Multimedia
Conference
The 33rd ACM International Conference on Multimedia
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Subjects
Source
The 33rd ACM International Conference on Multimedia
Publisher
Association for Computing Machinery