Hugging Face Trending Papers

S1-Omni-Image: A Unified Model for Scientific Image Understanding, Generation, and Editing

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We present S1-Omni-Image, an open-weight unified multimodal model for scientific image understanding, generation, and editing. Unlike general-purpose image generation models, scientific image tasks require not only high-fidelity synthesis, but also robust understanding of scientific semantics, structural relations, domain knowledge, and task intent.

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arXiv Computer Vision
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SciGen-Verifier: A Multimodal Reasoner for Explainable Verification in Scientific Image Generation

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arXiv AI
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S1-Omni: A Unified Multimodal Reasoning Model for Scientific Understanding, Prediction, and Generation

arXiv:2607. 15686v1 Announce Type: new Abstract: We present S1-Omni, a unified multimodal reasoning model for scientific understanding, prediction, and generation.

By Jiahao Zhao, Junyi Liu, Lifeng Xu, Nan Xu, Qingli Wang, Qingxiao Li, Tianle Chen, Xiaoyu Wu, Yawen Zheng, Zikai Wang, Guanming Liu, Hequn Zhou, Jingyi Wang, Jingyuan Shu, Keqi Wang, Li He, Songyang Diao, Wenhui Xu, Xinyu Ren, Yaqin Fan, Yujin Zhou, Zhanao Yao
arXiv AI
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Scientific Image Synthesis: Benchmarking, Methodologies, and Downstream Utility

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By Honglin Lin, Zheng Liu, Chonghan Qin, Qizhi Pei, Yu Li, Zhanping Zhong, Xin Gao, Yanfeng Wang, Conghui He, Lijun Wu
arXiv Computer Vision
Sep 11

SenseNova-U1.5: Towards Native Unified Visual Intelligence

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Hugging Face Trending Papers
Jun 29

SciIR: A Large-scale Training Dataset and Benchmark for Scientific Image Reasoning Generation

While Text-to-Image (T2I) models have shown remarkable success in generating photorealistic visual content, they still struggle with the rigorous semantic alignment and logical reasoning required for scientific imagery. Inspired by Peirce's Semiotic Triad, we introduce Scientific Image Reasoning (SciIR), a comprehensive resource for training and evaluation of scientific image generation.

arXiv Computer Vision
Sep 1

DisciplineGen-1M: A Large-Scale Dataset for Multidisciplinary Visual Generation and Editing

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By Zhaokai Wang, Mingxin Liu, Zirun Zhu, Ziqian Fan, Yiguo He, Mohan Zhang, Leyao Gu, Yan Li, Xiangyu Zhao, Ning Liao, Shaofeng Zhang, Xuanhe Zhou, Zhihang Zhong, Xue Yang