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<a class="navbar-brand" href="#" style="font-size: 120%; font-weight: bold; color: white;">Tao Huang</a>
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<a class="nav-item nav-link" href="#nav_publications">Publications</a>
<a class="nav-item nav-link" href="#talks">Talks</a>
<a class="nav-item nav-link" href="#teaching">Teaching</a>
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<!-- <a class="nav-item nav-link" href="#awards">Awards</a> -->
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<div class="container" style="align-items: start; align-self: start; align-content: start;">
<div class="left-section">
<h2 style="margin-top: 0em;">Biography</h2>
<div style="text-align:justify" class="paper">
My name is Tao Huang (黄涛). I received my Ph.D. degree in Computer Science at <a href="https://www.sydney.edu.au/">The University of Sydney</a>, advised by <a href="http://changxu.xyz">Prof. Chang Xu</a>.
Before that, I was a Researcher at <a href="https://www.sensetime.com">SenseTime</a>, supervised by <a href="https://shanyou92.github.io/">Dr. Shan You</a>.
In 2020, I received my Bachelor's degree in Computer Science at <a href="http://english.hust.edu.cn/">Huazhong University of Science and Technology</a>, China.
</div>
</p>
<br>
<p>My major research interests lie within <b>efficient machine learning</b> algorithms and their applications in <b>computer vision</b> tasks:
<ul>
<li style="margin-top: 0.2em"><b>Efficient architectures</b>: NAS, handcrafts, pruning, Rep ...</li>
<li style="margin-top: 0.2em"><b>Efficient training</b>: training acceleration, KD, PEFT ...</li>
<li style="margin-top: 0.2em"><b>Efficient data</b>: SSL, zero/low-shot learning, generated training contents ...</li>
<li style="margin-top: 0.2em"><b>Efficient inference</b>: cache optimization, quantization, dynamic networks ...</li>
<li style="margin-top: 0.2em"><b>Efficient large models</b>: LLMs, VLMs, Generative Models ...</li>
</ul>
</p>
</div>
<div class="right-section">
<!-- <h2>Tao Huang</h2> -->
<img src="assets/taohuang_3.png" class="profile-pic">
<p style="font-size: small;">
<strong style="font-size: medium;">Tao Huang</strong><br>
Ph.D.<br>
The University of Sydney<br>
Email: <a href="mailto:[email protected]">huntocn[at]gmail.com</a><br>
<br>
<a href="https://github.com/hunto"><img src="assets/github.png" class="icon"></a>
<a href="https://scholar.google.com/citations?user=jkcRdBgAAAAJ&hl=en"><img src="assets/google_scholar.svg" class="icon"></a>
<!-- <a href="https://www.linkedin.com/in/tao-huang-a93910292"><img src="assets/linkedin.svg" class="icon"></a> -->
</p>
</div>
</div>
<p>
<b style="color: #D13644;">🚩 I am recruiting RA, Master, and PhD students, drop me an email if interested.</b>
</p>
<!-- <p><font color="red">Pinned: </font></p> -->
<div id="news" style="margin-bottom: 2em; margin-top: -2em;"></div>
<h2>News</h2>
<ul>
<li style="margin-top: 0.2em">[2025/01] One paper was accepted to ICLR 2025.</li>
<li style="margin-top: 0.2em">[2025/01] We released MiniMax-01 [<a href="https://arxiv.org/abs/2501.08313">tech report</a>] [<a href="https://github.com/MiniMax-AI/MiniMax-01">Github</a>] [<a href="https://huggingface.co/MiniMaxAI">Hugging Face</a>].</li>
<li style="margin-top: 0.2em">[2024/12] One paper was accepted to AAAI 2025.</li>
<li style="margin-top: 0.2em">[2024/09] One paper was accepted to NeurIPS 2024.</li>
<li style="margin-top: 0.2em">[2024/07] I gave a talk about "Efficient Large Models" at Peking University. Many thanks to Prof. Shanghang Zhang for the invitation.</li>
<li style="margin-top: 0.2em">[2024/07] Two papers were accepted to ECCV 2024.</li>
<li style="margin-top: 0.2em">[2024/06] I co-organized TNNLS 2024 Tutorial "Efficient and Secure Foundation Models" and gave a talk.</li>
<li style="margin-top: 0.2em">[2024/06] One paper was accepted to journal Knowledge-Based Systems.</li>
<li style="margin-top: 0.2em">[2024/03] Our <a href="">PU-MLC</a> was accepted to ICME 2024 as <b>oral</b>.</li>
<li style="margin-top: 0.2em">[2024/03] We released <a href="https://arxiv.org/abs/2403.06517">ActGen</a> & <a href="https://arxiv.org/abs/2403.09338">LocalMamba</a> & <a href="https://arxiv.org/abs/2403.09977">EfficientVMamba</a> at arXiv.</li>
<li style="margin-top: 0.2em">[2024/02] One paper (<a href="https://arxiv.org/abs/2311.12079">FreeKD</a>) was accepted to CVPR 2024.</li>
<li style="margin-top: 0.2em">[2024/02] We released <a href="assets/dist+/DIST+.pdf">DIST+</a>.</li>
</ul>
<button type="button" class="collapsible">More</button>
<div class="content">
<ul>
<li style="margin-top: 0.2em">[2023/09] One paper (<a href="https://arxiv.org/abs/2305.15712">DiffKD</a>) was accepted to NeurIPS 2023.</li>
<li style="margin-top: 0.2em">[2023/07] One paper (<a href="https://arxiv.org/abs/2305.02722">AKD</a>) was accepted to ACM MM 2023.</li>
<li style="margin-top: 0.2em">[2023/05] We released <a href="https://arxiv.org/abs/2305.15712">DiffKD</a> and <a href="https://arxiv.org/abs/2305.02722">AKD</a> at arXiv.</li>
<li style="margin-top: 0.2em">[2023/01] One paper (<a href="https://arxiv.org/abs/2205.14589">MasKD</a>) was accepted to ICLR 2023.</li>
<li style="margin-top: 0.2em">[2022/09] One paper (<a href="https://arxiv.org/abs/2205.10536">DIST</a>) was accepted to NeurIPS 2022.</li>
<li style="margin-top: 0.2em">[2022/07] We released <a href="https://arxiv.org/abs/2207.05557">LightViT</a> <a href="https://github.com/hunto/LightViT">[code]</a> at arXiv.</li>
<li style="margin-top: 0.2em">[2022/05] We released <a href="https://arxiv.org/abs/2205.10536">DIST</a> <a href="https://github.com/hunto/DIST_KD">[code]</a> and <a href="https://arxiv.org/abs/2205.14589">MasKD</a> <a href="https://github.com/hunto/MasKD">[code]</a> at arXiv.</li>
<li style="margin-top: 0.2em">[2022/04] One paper (<a href="https://arxiv.org/abs/2010.10217">QAS</a>) was accepted to <i>Nature Partner Journals</i> Quantum Information (NPJ QI).</li>
<li style="margin-top: 0.2em">[2022/03] Two papers (<a href="https://arxiv.org/abs/2111.12609">GreedyNASv2</a> & <a href="https://arxiv.org/abs/2203.12868">DyRep</a>) were accepted to CVPR 2022.</li>
<li style="margin-top: 0.2em">[2022/01] One paper (<a href="https://arxiv.org/abs/2202.13197">ReLoss</a>) was accepted to ICLR 2022.</li>
<li style="margin-top: 0.2em">
[2021/12] We released <ax href="https://github.com/open-mmlab/mmrazor">MMRazor</ax> - a model compression toolkit for model slimming and AutoML, which includes 3 mainstream technologies NAS, pruning, and KD. MMRazor can be easily applied to various projects (e.g., MMDet and MMCls) in OpenMMLab.
</li>
<li style="margin-top: 0.2em">
[2021/11] We released GreedyNASv2 at <ax href="https://arxiv.org/abs/2111.12609">arXiv</a>.
</li>
<li style="margin-top: 0.2em">
[2021/03] One paper about NAS was accepted to CVPR 2021. The NAS benchmark in our paper was released at <ax href="https://github.com/xiusu/NAS-Bench-Macro">github</a>.
</li>
<li style="margin-top: 0.2em">
[2021/01] One paper about channel number search (pruning) was accepted to ICLR 2021 as spotlight.
</li>
<li style="margin-top: 0.2em">
[2020/11] One paper about NAS was released at <ax href="https://arxiv.org/abs/2011.09300">arXiv</a>. Our TopoNAS explicitly learns the topology for differentiable NAS (DARTS), and enjoys significant efficiency improvement on obtained architectures.
</li>
<li style="margin-top: 0.2em">
[2020/10] One paper about quantum architecture search (QAS) was released at <ax href="https://arxiv.org/abs/2010.10217">arXiv</a>. Our QAS implicitly learns a rule that can well suppress the influence of quantum noise and the barren plateau.
</li>
<li style="margin-top: 0.2em">
[2020/02] One paper about NAS was accepted to CVPR 2020.
</li>
</ul>
</div>
<div id="nav_publications" style="margin-bottom: 2em; margin-top: -2em;"></div>
<h2>Publications <a href="https://scholar.google.com/citations?user=jkcRdBgAAAAJ&hl=en">[Google Scholar]</a></h2>
*: co-first author. <br>
<button class="filter" type="button" onclick="filterPub('All')" style="--color: #000; --border: #000">All</button>
<button class="filter" type="button" onclick="filterPub('First-author')">First-author</button>
<button class="filter" type="button" onclick="filterPub('KD')">KD</button>
<button class="filter" type="button" onclick="filterPub('NAS')">NAS</button>
<button class="filter" type="button" onclick="filterPub('Pruning')">Pruning</button>
<button class="filter" type="button" onclick="filterPub('Efficient Training')">Efficient Training</button>
<button class="filter" type="button" onclick="filterPub('Efficient Data')">Efficient Data</button>
<ul id="publications">
<h3 style="margin-top: 1em;">2025</h3>
<li class="paper" first_authored=true category="Efficient Data">
<venue>ICLR</venue><pt>Learning Mask Invariant Mutual Information for Masked Image Modeling</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>*, Yanxiang Ma*, Shan You, Chang Xu</g><br>
<em>International Conference on Learning Representations</em> (<b>ICLR</b>), 2025.</em>
</div>
<p>
<a class="button-59" href="">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="">
<venue>Report</venue><pt>MiniMax-01: Scaling Foundation Models with Lightning Attention</pt><br>
<div class="author">
<em>Technical Report</em>, 2025
</div>
<p>
<a href="https://arxiv.org/abs/2501.08313" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/MiniMax-AI/MiniMax-01" class="button-59">Code</a>
<a href="https://huggingface.co/MiniMaxAI" class="button-59">Hugging Face</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@misc{minimax2025minimax01scalingfoundationmodels,
title={MiniMax-01: Scaling Foundation Models with Lightning Attention},
author={MiniMax and Aonian Li and Bangwei Gong and Bo Yang and Boji Shan and Chang Liu and Cheng Zhu and Chunhao Zhang and Congchao Guo and Da Chen and Dong Li and Enwei Jiao and Gengxin Li and Guojun Zhang and Haohai Sun and Houze Dong and Jiadai Zhu and Jiaqi Zhuang and Jiayuan Song and Jin Zhu and Jingtao Han and Jingyang Li and Junbin Xie and Junhao Xu and Junjie Yan and Kaishun Zhang and Kecheng Xiao and Kexi Kang and Le Han and Leyang Wang and Lianfei Yu and Liheng Feng and Lin Zheng and Linbo Chai and Long Xing and Meizhi Ju and Mingyuan Chi and Mozhi Zhang and Peikai Huang and Pengcheng Niu and Pengfei Li and Pengyu Zhao and Qi Yang and Qidi Xu and Qiexiang Wang and Qin Wang and Qiuhui Li and Ruitao Leng and Shengmin Shi and Shuqi Yu and Sichen Li and Songquan Zhu and Tao Huang and Tianrun Liang and Weigao Sun and Weixuan Sun and Weiyu Cheng and Wenkai Li and Xiangjun Song and Xiao Su and Xiaodong Han and Xinjie Zhang and Xinzhu Hou and Xu Min and Xun Zou and Xuyang Shen and Yan Gong and Yingjie Zhu and Yipeng Zhou and Yiran Zhong and Yongyi Hu and Yuanxiang Fan and Yue Yu and Yufeng Yang and Yuhao Li and Yunan Huang and Yunji Li and Yunpeng Huang and Yunzhi Xu and Yuxin Mao and Zehan Li and Zekang Li and Zewei Tao and Zewen Ying and Zhaoyang Cong and Zhen Qin and Zhenhua Fan and Zhihang Yu and Zhuo Jiang and Zijia Wu},
year={2025},
eprint={2501.08313},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2501.08313},
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" first_authored=true, category="">
<venue>AAAI</venue><pt>EfficientVMamba: Atrous Selective Scan for Light Weight Visual Mamba</pt><br>
<div class="author">
<g>Xiaohuan Pei*, </g><b><u>Tao Huang</u></b>*<g>, Chang Xu</g><br>
<em>In Proceedings of the AAAI Conference on Artificial Intelligence</em> (<b>AAAI</b>), 2025
</div>
<p>
<a href="https://arxiv.org/abs/2403.09977" class="button-59">ArXiv</a>
<a href="https://github.com/TerryPei/EfficientVMamba" class="button-59">Code</a>
</p>
</li>
<h3 style="margin-top: 1em;">2024</h3>
<li class="paper">
<venue>NeurIPS</venue><pt>Unveiling the Tapestry of Consistency in Large Vision-Language Models</pt><br>
<div class="author">
<g>Yuan Zhang, Fei Xiao, </g><b><u>Tao Huang</u></b><g>, Chun-Kai Fan, Hongyuan Dong, Jiawen Li, Jiacong Wang, Kuan Cheng, Shanghang Zhang, Haoyuan Guo</g><br>
<em>Advances in Neural Information Processing Systems</em> (<b>NeurIPS</b>), 2024.
</div>
<p>
<a href="https://arxiv.org/abs/2405.14156" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/foundation-multimodal-models/ConBench" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{zhang2024unveiling,
author = {Zhang, Yuan and Xiao, Fei and Huang, Tao and Fan, Chun-Kai and Dong, Hongyuan and Li, Jiawen and Wang, Jiacong and Cheng, Kuan and Zhang, Shanghang and Guo, Haoyuan},
booktitle = {Advances in Neural Information Processing Systems},
title = {Unveiling the Tapestry of Consistency in Large Vision-Language Models},
year = {2024}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" first_authored=true category="">
<venue>ECCVW</venue><pt>LocalMamba: Visual State Space Model with Windowed Selective Scan</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Xiaohuan Pei, Shan You, Fei Wang, Chen Qian, Chang Xu</g><br>
<em>Efficient Deep Learning for Foundation Models, European Conference on Computer Vision</em> (<b>ECCV</b>) Workshop, 2024.
</div>
<p>
<a href="https://arxiv.org/abs/2403.09338" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/hunto/LocalMamba" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@article{huang2024localmamba,
title={Localmamba: Visual state space model with windowed selective scan},
author={Huang, Tao and Pei, Xiaohuan and You, Shan and Wang, Fei and Qian, Chen and Xu, Chang},
journal={arXiv preprint arXiv:2403.09338},
year={2024}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" first_authored=true category="Efficient Data,Efficient Training">
<venue>ECCV</venue><pt>Active Generation for Image Classification</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>*, Jiaqi Liu*, Shan You, Chang Xu</g><br>
<em>European Conference on Computer Vision</em> (<b>ECCV</b>), 2024.
</div>
<p>
<a href="https://arxiv.org/abs/2403.06517" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/hunto/ActGen" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{huang2024active,
title={Active Generation for Image Classification},
author={Huang, Tao and Liu, Jiaqi and You, Shan and Xu, Chang},
booktitle={European Conference on Computer Vision},
year={2024},
organization={Springer}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="generation,Efficient Training">
<venue>ECCV</venue><pt>Training-free Composite Scene Generation for Layout-to-Image Synthesis</pt><br>
<div class="author">
<g>Jiaqi Liu,</g> <b><u>Tao Huang</u></b><g>, Chang Xu</g><br>
<em>European Conference on Computer Vision</em> (<b>ECCV</b>), 2024.
</div>
<p>
<a href="https://arxiv.org/abs/2407.13609" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/Papple-F/csg" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{liu2024training,
title={Training-free Composite Scene Generation for Layout-to-Image Synthesis},
author={Liu, Jiaqi and Huang, Tao and Xu, Chang},
booktitle={European Conference on Computer Vision},
year={2024},
organization={Springer}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="Efficient Data">
<venue>KBS</venue><pt>Diverse and Tailored Image Generation for Zero-Shot Multi-Label Classification</pt><br>
<div class="author">
<g>Kaixin Zhang, Zhixiang Yuan, </g><b><u>Tao Huang</u></b><br>
<em>Knowledge-Based Systems</em> (<b>KBS</b>), Volume 299, 5 September 2024, 112077.
</div>
<p>
<a href="https://arxiv.org/abs/2404.03144" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://www.sciencedirect.com/science/article/abs/pii/S0950705124007111" class="button-59">KBS</a>
<a href="https://github.com/TAKELAMAG/Diff-ZS-MLC" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@article{ZHANG2024112077,
title = {Diverse and tailored image generation for zero-shot multi-label classification},
journal = {Knowledge-Based Systems},
volume = {299},
pages = {112077},
year = {2024},
issn = {0950-7051},
doi = {https://doi.org/10.1016/j.knosys.2024.112077},
url = {https://www.sciencedirect.com/science/article/pii/S0950705124007111},
author = {Kaixin Zhang and Zhixiang Yuan and Tao Huang},
keywords = {Zero-shot multi-label learning, Deep generative model, Diffusion model, Synthetic data},
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="Efficient Data">
<venue>ICME</venue><pt>Positive Label Is All You Need for Multi-Label Classification</pt><flag>🚩 Oral</flag><br>
<div class="author">
<g>Zhixiang Yuan, Kaixin Zhang, </g><b><u>Tao Huang</u></b><br>
<em>IEEE International Conference on Multimedia and Expo</em> (<b>ICME</b>), 2024.
</div>
<p>
<a href="https://arxiv.org/abs/2306.16016" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/TAKELAMAG/PU-MLC" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{yuan2024positive,
title={Positive label is all you need for multi-label classification},
author={Yuan, Zhixiang and Zhang, Kaixin and Huang, Tao},
booktitle={2024 IEEE International Conference on Multimedia and Expo (ICME)},
pages={1--6},
year={2024},
organization={IEEE}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="KD">
<venue>CVPR</venue><pt>FreeKD: Knowledge Distillation via Semantic Frequency Prompt</pt><br>
<div class="author">
<g>Yuan Zhang,</g> <b><u>Tao Huang</u></b><g>, Jiaming Liu, Tao Jiang, Kuan Cheng, Shanghang Zhang</g><br>
<em>IEEE Conference on Computer Vision and Pattern Recognition</em> (<b>CVPR</b>), 2024.
</div>
<p>
<a href="https://arxiv.org/abs/2311.12079" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/Gumpest/FreeKD" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{zhang2024freekd,
title={FreeKD: Knowledge Distillation via Semantic Frequency Prompt},
author={Zhang, Yuan and Huang, Tao and Liu, Jiaming and Jiang, Tao and Cheng, Kuan and Zhang, Shanghang},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={15931--15940},
year={2024}
}
</pre>
</blockquote>
</div>
</p>
</li>
<h3>2023</h3>
<li class="paper" first_authored=true category="KD">
<venue>NeurIPS</venue><pt>Knowledge Diffusion for Distillation</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Yuan Zhang, Mingkai Zheng, Shan You, Fei Wang, Chen Qian, Chang Xu</g><br>
<em>Advances in Neural Information Processing Systems</em> (<b>NeurIPS</b>), 2023.
</div>
<p>
<a href="https://arxiv.org/abs/2305.15712" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="assets/diffkd/poster_neurips23_diffkd.pdf" class="button-59">Poster</a>
<a href="https://github.com/hunto/DiffKD" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{huang2023knowledge,
author = {Huang, Tao and Zhang, Yuan and Zheng, Mingkai and You, Shan and Wang, Fei and Qian, Chen and Xu, Chang},
booktitle = {Advances in Neural Information Processing Systems},
editor = {A. Oh and T. Naumann and A. Globerson and K. Saenko and M. Hardt and S. Levine},
pages = {65299--65316},
publisher = {Curran Associates, Inc.},
title = {Knowledge Diffusion for Distillation},
url = {https://proceedings.neurips.cc/paper_files/paper/2023/file/cdddf13f06182063c4dbde8cbd5a5c21-Paper-Conference.pdf},
volume = {36},
year = {2023}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="KD">
<venue>ACM MM</venue><pt>Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with Uncertainty</pt><br>
<div class="author">
<g>Yuan Zhang, Weihua Chen, Yichen Lu,</g> <b><u>Tao Huang</u></b><g>, Xiuyu Sun, Jian Cao</g><br>
<em>Proceedings of the 31th ACM International Conference on Multimedia</em> (<b>ACM MM</b>), 2023.
</div>
<p>
<a href="https://arxiv.org/abs/2305.02722" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/Gumpest/AvatarKD" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{zhang2023avatar,
title={Avatar knowledge distillation: self-ensemble teacher paradigm with uncertainty},
author={Zhang, Yuan and Chen, Weihua and Lu, Yichen and Huang, Tao and Sun, Xiuyu and Cao, Jian},
booktitle={Proceedings of the 31st ACM International Conference on Multimedia},
pages={5272--5280},
year={2023}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" first_authored=true category="KD">
<venue>ICLR</venue><pt>Masked Distillation with Receptive Tokens</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>*, Yuan Zhang*, Shan You, Fei Wang, Chen Qian, Jian Cao, Chang Xu</g><br>
<em>International Conference on Learning Representations</em> (<b>ICLR</b>), 2023.</em>
</div>
<p>
<a class="button-59" href="https://arxiv.org/abs/2205.14589">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://github.com/hunto/MasKD" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{
huang2023masked,
title={Masked Distillation with Receptive Tokens},
author={Tao Huang and Yuan Zhang and Shan You and Fei Wang and Chen Qian and Jian Cao and Chang Xu},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=mWRngkvIki3}
}
</pre>
</blockquote>
</div>
</p>
</li>
<h3>2022</h3>
<li class="paper" first_authored=true category="KD">
<venue>NeurIPS</venue><pt>Knowledge Distillation from A Stronger Teacher</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Shan You, Fei Wang, Chen Qian, Chang Xu</g><br>
<em>Advances in Neural Information Processing Systems</em> (<b>NeurIPS</b>), 2022.
</div>
<p>
<a href="https://arxiv.org/abs/2205.10536" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="assets/dist/KD_sharing_Tao_20220715.pdf" class="button-59">Slides</a>
<a href="assets/dist/NeurIPS2022_DIST_poster.pdf" class="button-59">Poster</a>
<a href="https://mp.weixin.qq.com/s/PwzyaZXCrl_W8NmiQgXm0g" class="button-59">解读</a>
<a href="https://github.com/hunto/DIST_KD" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{huang2022knowledge,
author = {Huang, Tao and You, Shan and Wang, Fei and Qian, Chen and Xu, Chang},
booktitle = {Advances in Neural Information Processing Systems},
editor = {S. Koyejo and S. Mohamed and A. Agarwal and D. Belgrave and K. Cho and A. Oh},
pages = {33716--33727},
publisher = {Curran Associates, Inc.},
title = {Knowledge Distillation from A Stronger Teacher},
url = {https://proceedings.neurips.cc/paper_files/paper/2022/file/da669dfd3c36c93905a17ddba01eef06-Paper-Conference.pdf},
volume = {35},
year = {2022}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="NAS">
<venue>NPJ QI</venue><pt></pt><pt>Quantum circuit architecture search for variational quantum algorithms</pt><br>
<div class="author">
<g>Yuxuan Du,</g> <b><u>Tao Huang</u></b></b><g>, Shan You, Min-Hsiu Hsieh, Dacheng Tao</g><br>
<em>Nature Partner Journals Quantum Information</em> (<b>NPJ QI</b>), 2022.<br>
</div>
<p>
<a href="https://arxiv.org/abs/2010.10217" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://www.nature.com/articles/s41534-022-00570-y" class="button-59">Nature</a>
<a href="https://github.com/yuxuan-du/Quantum_architecture_search" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@article{du2022quantum,
author = {Du, Yuxuan and Huang, Tao and You, Shan and Hsieh, Min-Hsiu and Tao, Dacheng},
date = {2022/05/23},
doi = {10.1038/s41534-022-00570-y},
id = {Du2022},
isbn = {2056-6387},
journal = {npj Quantum Information},
number = {1},
pages = {62},
title = {Quantum circuit architecture search for variational quantum algorithms},
url = {https://doi.org/10.1038/s41534-022-00570-y},
volume = {8},
year = {2022},
bdsk-url-1 = {https://doi.org/10.1038/s41534-022-00570-y}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" first_authored=true category="NAS">
<venue>CVPR</venue><pt></pt><pt>GreedyNASv2: Greedier Search with a Greedy Path Filter</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Xiaogang Wang, Chang Xu</g><br>
<em>IEEE Conference on Computer Vision and Pattern Recognition</em> (<b>CVPR</b>), 2022.<br>
</div>
<p>
<a href="https://arxiv.org/abs/2111.12609" class="button-59">ArXiv</a>
<!-- <a href="https://scholar.google.com/scholar?cluster=8646649449956447640&hl=en&as_sdt=0,5" class="button-59">Bib</a> -->
<button class="button-59 bib-link">Bib</button>
<!-- <button class="button-59" onclick="getBibTex('huang2022greedynasv2')">Bib</button> -->
<a href="assets/greedynasv2/CVPR2022_GreedyNASv2_Poster.pdf" class="button-59">Poster</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{huang2022greedynasv2,
title={Greedynasv2: greedier search with a greedy path filter},
author={Huang, Tao and You, Shan and Wang, Fei and Qian, Chen and Zhang, Changshui and Wang, Xiaogang and Xu, Chang},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={11902--11911},
year={2022}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" first_authored=true category="Efficient Training">
<venue>CVPR</venue><pt>DyRep: Bootstrapping Training with Dynamic Re-parameterization</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Shan You, Bohan Zhang, Yuxuan Du, Fei Wang, Chen Qian, Chang Xu</g><br>
<em>IEEE Conference on Computer Vision and Pattern Recognition</em> (<b>CVPR</b>), 2022.<br>
</div>
<p>
<a href="https://arxiv.org/abs/2203.12868" class="button-59">ArXiv</a>
<!-- <a href="https://scholar.google.com/scholar?oi=bibs&hl=en&cluster=9004725926464672087" class="button-59">Bib</a> -->
<button class="button-59 bib-link">Bib</button>
<a href="assets/dyrep/CVPR2022_DyRep_Poster.pdf" class="button-59">Poster</a>
<a href="https://github.com/hunto/DyRep" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{huang2022dyrep,
title={Dyrep: bootstrapping training with dynamic re-parameterization},
author={Huang, Tao and You, Shan and Zhang, Bohan and Du, Yuxuan and Wang, Fei and Qian, Chen and Xu, Chang},
booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
pages={588--597},
year={2022}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" first_authored=true, category="Efficient Training">
<venue>ICLR</venue><pt>Relational Surrogate Loss Learning</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Zekang Li, Hua Lu, Yong Shan, Shusheng Yang, Yang Feng, Fei Wang, Shan You, Chang Xu</g><br>
<em>International Conference on Learning Representations</em> (<b>ICLR</b>), 2022.<br>
</div>
<p>
<a href="https://arxiv.org/abs/2202.13197" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="assets/reloss/Poster_ICLR2022_ReLoss.pdf" class="button-59">Poster</a>
<a href="assets/reloss/Slides_ICLR2022_ReLoss.pdf" class="button-59">Slides</a>
<a href="https://github.com/hunto/ReLoss" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{
huang2022relational,
title={Relational Surrogate Loss Learning},
author={Tao Huang and Zekang Li and Hua Lu and Yong Shan and Shusheng Yang and Yang Feng and Fei Wang and Shan You and Chang Xu},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=dZPgfwaTaXv}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="pruning">
<venue>ICASSP</venue><pt>Data Agnostic Filter Gating for Efficient Deep Networks</pt><br>
<div class="author">
<g>Hongyan Xu, Xiu Su, Shan You,</g> <b><u>Tao Huang</u></b><g>, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu, Dadong Wang, Arcot Sowmya</g><br>
<em>IEEE International Conference on Acoustics, Speech and Signal Processing</em> (<b>ICASSP</b>), 2022.
</div>
<p>
<a href="https://arxiv.org/abs/2010.15041" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{xu2022data,
title={Data agnostic filter gating for efficient deep networks},
author={Xu, Hongyan and Su, Xiu and You, Shan and Huang, Tao and Wang, Fei and Qian, Chen and Zhang, Changshui and Xu, Chang and Wang, Dadong and Sowmya, Arcot},
booktitle={ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
pages={3503--3507},
year={2022},
organization={IEEE}
}
</pre>
</blockquote>
</div>
</p>
</li>
<h3>2021</h3>
<li class="paper" first_authored=true category="NAS">
<venue>CVPR</venue><pt>Prioritized Architecture Sampling with Monto-Carlo Tree Search</pt><br>
<div class="author">
<g>Xiu Su*,</g> <b><u>Tao Huang</u></b>*<g>, Yanxi Li, Shan You, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu</g><br>
<em>IEEE Conference on Computer Vision and Pattern Recognition</em> (<b>CVPR</b>), 2021.<br>
</div>
<p>
<a href="https://arxiv.org/abs/2103.11922" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="assets/mctnas/Poster_CVPR2021_MCT-NAS.pdf" class="button-59">Poster</a>
<a href="https://github.com/xiusu/NAS-Bench-Macro" class="button-59">NAS-Bench-Macro</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{su2021prioritized,
title={Prioritized architecture sampling with monto-carlo tree search},
author={Su, Xiu and Huang, Tao and Li, Yanxi and You, Shan and Wang, Fei and Qian, Chen and Zhang, Changshui and Xu, Chang},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={10968--10977},
year={2021}
}
</pre>
</blockquote>
</div>
</p>
</li>
<li class="paper" category="NAS,pruning">
<venue>ICLR</venue><pt>Locally Free Weight Sharing for Network Width Search</pt><flag>🚩 Spotlight</flag><br>
<div class="author">
<g>Xiu Su, Shan You,</g> <b><u>Tao Huang</u></b><g>, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu</g><br>
<em>International Conference on Learning Representations</em> (<b>ICLR</b>), 2021.<br>
</div>
<p>
<a href="https://arxiv.org/abs/2102.05258" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="https://openreview.net/forum?id=S0UdquAnr9k" class="button-59">OpenReview</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{
su2021locally,
title={Locally Free Weight Sharing for Network Width Search},
author={Xiu Su and Shan You and Tao Huang and Fei Wang and Chen Qian and Changshui Zhang and Chang Xu},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=S0UdquAnr9k}
}
</pre>
</blockquote>
</div>
</p>
</li>
<h3>2020</h3>
<li class="paper" first_authored=true category="NAS">
<venue>CVPR</venue><pt>GreedyNAS: Towards Fast One-Shot NAS with Greedy Supernet</pt><br>
<div class="author">
<g>Shan You*,</g> <b><u>Tao Huang</u></b>*<g>, Mingmin Yang*, Fei Wang, Chen Qian, Changshui Zhang</g><br>
<em>IEEE Conference on Computer Vision and Pattern Recognition</em> (<b>CVPR</b>), 2020.</br>
</div>
<p>
<a href="https://arxiv.org/abs/2003.11236" class="button-59">ArXiv</a>
<button class="button-59 bib-link">Bib</button>
<a href="assets/greedynas/Poster_CVPR2020_GreedyNAS.pdf" class="button-59">Poster</a>
<a href="assets/greedynas/Video_CVPR2020_GreedyNAS.mp4" class="button-59">Video</a>
<a href="assets/greedynas/Slides_GreedyNAS_titan.pdf" class="button-59">Slides</a>
<a href="https://github.com/open-mmlab/mmrazor" class="button-59">Code</a>
<div class="bib-div"></div>
<div class="bib-content" style="display:none">
<blockquote>
<pre>
@inproceedings{you2020greedynas,
title={Greedynas: Towards fast one-shot nas with greedy supernet},
author={You, Shan and Huang, Tao and Yang, Mingmin and Wang, Fei and Qian, Chen and Zhang, Changshui},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
pages={1999--2008},
year={2020}
}
</pre>
</blockquote>
</div>
</p>
</li>
</ul>
<h2>Manuscripts</h2>
<button type="button" class="collapsible">More</button>
<div class="content">
<ul>
<li class="paper">
<venue>arXiv</venue><pt>VLA-Cache: Towards Efficient Vision-Language-Action Model via Adaptive Token Caching in Robotic Manipulation</pt><br>
<div class="author">
<g>Siyu Xu, Yunke Wang, Chenghao Xia, Dihao Zhu, </g><b><u>Tao Huang</u></b><g>, Chang Xu</g><br>
<em>arXiv preprint arXiv:2502.02175 (2025).</em>
</div>
<p>
<a href="https://arxiv.org/abs/2502.02175" class="button-59">ArXiv</a>
</p>
</li>
<li class="paper">
<venue>arXiv</venue><pt>Cross-Self KV Cache Pruning for Efficient Vision-Language Inference</pt><br>
<div class="author">
<g>Xiaohuan Pei, </g><b><u>Tao Huang</u></b><g>, Chang Xu</g><br>
<em>arXiv preprint arXiv:2412.04652 (2024).</em>
</div>
<p>
<a href="https://arxiv.org/abs/2412.04652" class="button-59">ArXiv</a>
<a href="https://github.com/TerryPei/CSP" class="button-59">Code</a>
</p>
</li>
<li class="paper">
<venue>arXiv</venue><pt>SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference</pt><br>
<div class="author">
<g>Yuan Zhang*, ChunKai Fan*, Junpeng Ma*, Wenzhao Zheng, </g><b><u>Tao Huang</u></b><g>, Kuan Cheng, Denis Gudovskiy, Tomoyuki Okuno, Yohei Nakata, Kurt Keutzer, Shanghang Zhang</g><br>
<em>arXiv preprint arXiv:2410.04417 (2024).</em>
</div>
<p>
<a href="https://arxiv.org/pdf/2410.04417" class="button-59">ArXiv</a>
<a href="https://github.com/Gumpest/SparseVLMs" class="button-59">Code</a>
</p>
</li>
<li class="paper">
<venue>arXiv</venue><pt>Not All Steps are Equal: Efficient Generation with Progressive Diffusion Models</pt><br>
<div class="author">
<g>Wenhao Li, Xiu Su, Shan You,</g> <b><u>Tao Huang</u></b><g>, Fei Wang, Chen Qian, Chang Xu</g><br>
<em>arXiv preprint arXiv:2312.13307 (2023).</em>
</div>
<p>
<a href="https://arxiv.org/abs/2312.13307v2" class="button-59">ArXiv</a>
</p>
</li>
<li class="paper" first_authored=true category="KD">
<pt>DIST+: Knowledge Distillation from A Stronger Teacher</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Shan You, Fei Wang, Chen Qian, Chang Xu</g><br>
</div>
<p>
<a href="assets/dist+/DIST+.pdf" class="button-59">PDF</a>
</p>
</li>
<li class="paper">
<venue>arXiv</venue><pt>LightViT: Towards Light-Weight Convolution-Free Vision Transformers</pt><br>
<div class="author">
<b><u>Tao Huang</u></b><g>, Lang Huang, Shan You, Fei Wang, Chen Qian, Chang Xu</g><br>
<em>arXiv preprint arXiv:2207.05557 (2022).</em>
</div>
<p>
<a href="https://arxiv.org/abs/2207.05557" class="button-59">ArXiv</a>
<a href="https://scholar.google.com/scholar?oi=bibs&hl=en&cluster=13876321258274905912" class="button-59">Bib</a>
<a href="https://github.com/hunto/LightViT" class="button-59">Code</a>
</p>
</li>
<li class="paper">