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- <div align="center">
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- <a href="https://huggingface.co/spaces/teowu/Q-Instruct-on-mPLUG-Owl-2"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm-dark.svg" alt="Open in Spaces"></a>
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- <a href="https://arxiv.org/abs/2311.06783"><img src="https://img.shields.io/badge/Arxiv-2311:06783-red"></a>
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- <a href="https://huggingface.co/datasets/teowu/Q-Instruct"><img src="https://img.shields.io/badge/%F0%9F%A4%97%20Q%20Instruct-Dataset-green"></a>
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- <h1>Q-Instruct: Improving Low-level Visual Abilities for Multi-modality Foundation Models</h1>
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- <div>
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- <a href="https://teowu.github.io/" target="_blank">Haoning Wu</a><sup>1</sup><sup>*</sup>,
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- <a href="https://github.com/zzc-1998" target="_blank">Zicheng Zhang</a><sup>2</sup><sup>*</sup>,
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- <a href="https://github.com/ZhangErliCarl/" target="_blank">Erli Zhang</a><sup>1</sup><sup>*</sup>,
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- <a href="https://chaofengc.github.io" target="_blank">Chaofeng Chen</a><sup>1</sup>,
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- <a href="https://liaoliang92.github.io" target="_blank">Liang Liao</a><sup>1</sup>,
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- <a href="https://github.com/AnnanWangDaniel" target="_blank">Annan Wang</a><sup>1</sup>,
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- <a href="https://scholar.google.com/citations?user=NBIqaHQAAAAJ&hl=en" target="_blank">Kaixin Xu</a><sup>4</sup>,
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- <a href="https://github.com/lcysyzxdxc" target="_blank">Chunyi Li</a><sup>2</sup>,
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- <a href="https://scholar.google.com.sg/citations?user=NlNOyiQAAAAJ&hl=en" target="_blank">Jingwen Hou</a><sup>1</sup>,
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- <a href="https://ee.sjtu.edu.cn/en/FacultyDetail.aspx?id=24&infoid=153&flag=153" target="_blank">Guangtao Zhai</a><sup>2</sup>,
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- <a href="https://scholar.google.com/citations?user=ZYVZ1bgAAAAJ&hl=en" target="_blank">Geng Xue</a><sup>4</sup>,
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- <a href="https://wenxiusun.com" target="_blank">Wenxiu Sun</a><sup>3</sup>,
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- <a href="https://scholar.google.com/citations?user=uT9CtPYAAAAJ&hl=en" target="_blank">Qiong Yan</a><sup>3</sup>,
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- <a href="https://personal.ntu.edu.sg/wslin/Home.html" target="_blank">Weisi Lin</a><sup>1</sup><sup>#</sup>
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- <sup>1</sup>Nanyang Technological University, <sup>2</sup>Shanghai Jiaotong University, <sup>3</sup>Sensetime Research, <sup>4</sup>I2R@A*STAR
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- <sup>*</sup>Equal contribution. <sup>#</sup>Corresponding author.
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- </div>
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- <a href="https://HuggingFace.co/datasets/teowu/Q-Instruct"><strong>Dataset</strong></a> | <a href="https://github.com/Q-Future/Q-Instruct/tree/main/model_zoo"><strong>Model Zoo</strong></a> | <a href="https://github.com/Q-Future/Q-Instruct/tree/main/fig/Q_Instruct_v0_1_preview.pdf"><strong>Paper (Preview)</strong></a> | <a href="https://huggingface.co/spaces/teowu/Q-Instruct-on-mPLUG-Owl-2"><strong>Demo (Hugging Face)</strong></a>
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- <div style="width: 100%; text-align: center; margin:auto;">
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- <img style="width:100%" src="https://raw.githubusercontent.com/Q-Future/Q-Instruct/main/new_q_instruct.png">
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- <h1>Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels</h1>
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- *One Unified Model for Image Quality Assessment (IQA), Image Aesthetic Assessment (IAA), and Video Quality Assessment (VQA).*
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- <a href="https://teowu.github.io/" target="_blank">Haoning Wu</a><sup>1</sup><sup>*</sup><sup>+</sup>,
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- <a href="https://github.com/zzc-1998" target="_blank">Zicheng Zhang</a><sup>2</sup><sup>*</sup>,
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- <a href="https://sites.google.com/view/r-panda" target="_blank">Weixia Zhang</a><sup>2</sup>,
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- <a href="https://chaofengc.github.io" target="_blank">Chaofeng Chen</a><sup>1</sup>,
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- <a href="https://liaoliang92.github.io" target="_blank">Liang Liao</a><sup>1</sup>,
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- <a href="https://github.com/lcysyzxdxc" target="_blank">Chunyi Li</a><sup>2</sup>,
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- <a href="https://github.com/YixuanGao98" target="_blank">Yixuan Gao</a><sup>2</sup>,
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- <a href="https://github.com/AnnanWangDaniel" target="_blank">Annan Wang</a><sup>1</sup>,
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- <a href="https://github.com/ZhangErliCarl/" target="_blank">Erli Zhang</a><sup>1</sup>,
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- <a href="https://wenxiusun.com" target="_blank">Wenxiu Sun</a><sup>3</sup>,
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- <a href="https://scholar.google.com/citations?user=uT9CtPYAAAAJ&hl=en" target="_blank">Qiong Yan</a><sup>3</sup>,
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- <a href="https://sites.google.com/site/minxiongkuo/" target="_blank">Xiongkuo Min</a><sup>2</sup>,
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- <a href="https://ee.sjtu.edu.cn/en/FacultyDetail.aspx?id=24&infoid=153&flag=153" target="_blank">Guangtao Zhai</a><sup>2</sup><sup>#</sup>,
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- <a href="https://personal.ntu.edu.sg/wslin/Home.html" target="_blank">Weisi Lin</a><sup>1</sup><sup>#</sup>
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- <sup>1</sup>Nanyang Technological University, <sup>2</sup>Shanghai Jiao Tong University, <sup>3</sup>Sensetime Research
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- <sup>*</sup>Equal contribution. <sup>+</sup>Project Lead. <sup>#</sup>Corresponding author(s).
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- <a href="https://HuggingFace.co/q-future/one-align"><strong>One Align</strong></a> | <a href="https://github.com/Q-Future/Q-Align/tree/main/model_zoo"><strong>Model Zoo</strong></a> | <a href="xx"><strong>Technical Report (Coming Soon)</strong></a>
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- <h2>Results</h2>
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- <img style="width: 75%" src="https://raw.githubusercontent.com/Q-Future/Q-Align/main/fig/radar.png">
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- <h2>Syllabus</h2>
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- <h2>Structure</h2>
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+ Our spaces:
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+ HF Spaces that our group maintains (Great thanks to the research GPU grants!):
 
 
 
 
 
 
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+ - **Q-Align** (*Most Powerful Visual Scorer*): <a href="https://huggingface.co/spaces/teowu/OneScorer"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm-dark.svg" alt="Open in Huggingface Spaces"></a>
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+ - **Q-Instruct** (*Low-level Vision-Language Assistant/Chatbot, support 1-4 images*): <a href="https://huggingface.co/spaces/teowu/Q-Instruct-v1"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm-dark.svg" alt="Open in Huggingface Spaces"></a>
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+ Corresponding models:
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+ - `q-future/one-align`: AutoModel for Visual Scoring. Trained with Mixture of existing datasets: See [Github](https://github.com/Q-Future/Q-Align) for details.
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+ - `q-future/co-instruct-preview`: AutoModel for Low-level Visual Dialog (Description, Comparison, Question Answering). Trained with the scaled 480K new Q-Instruct dataset (*will also release soon!*).
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+ - `q-future/q-instruct-mplug-owl2-1031`: Older version of Q-Instruct, as reported by [**paper**](https://q-future.github.io/Q-Instruct/fig/Q_Instruct_v0_1_preview.pdf). Trained with **released** Q-Instruct-200K dataset.
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+ *Though we have other model variants released for the community to replicate our results, please use the previous ones as they are proved to have more stable performance.*