All Publications | Zhongzhan Huang (黄中展)

2024

IEEE TNNLS

Continuous Value Assignment: A Doubly Robust Data Augmentation for Off-Policy Learning

Junfan Lin, Zhongzhan Huang, Keze Wang, Lingbo Liu, and Liang Lin

In IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2024

@inproceedings{linContinuousValue,
  title = {Continuous Value Assignment: A Doubly Robust Data Augmentation for Off-Policy Learning},
  author = {Lin, Junfan and Huang, Zhongzhan and Wang, Keze and Liu, Lingbo and Lin, Liang},
  booktitle = {IEEE Transactions on Neural Networks and Learning Systems (<strong>TNNLS</strong>)},
  year = {2024}
}

ECCV’24

ASR: Stripe Observation Guided Inference Cost-free Attention Mechanism

Zhongzhan Huang, Shanshan Zhong, Wushao Wen, Jinghui Qin, and Liang Lin

In The European Conference on Computer Vision (ECCV), 2024

PDF

@inproceedings{asr,
  title = {ASR: Stripe Observation Guided Inference Cost-free Attention Mechanism},
  author = {Huang, Zhongzhan and Zhong, Shanshan and Wen, Wushao and Qin, Jinghui and Lin, Liang},
  booktitle = {The European Conference on Computer Vision (<strong>ECCV</strong>)},
  year = {2024}
}

IEEE TASLP

MVT: An Introspective Data Augmentation Method for Training Math Word Problem Solvers

Jinghui Qin, Zhongzhan Huang, Ying Zeng, and Liang Lin

In IEEE Transactions on Audio, Speech and Language Processing (TALSP), 2024

PDF

@inproceedings{mvt,
  title = {MVT: An Introspective Data Augmentation Method for Training Math Word Problem Solvers},
  author = {Qin, Jinghui and Huang, Zhongzhan and Zeng, Ying and Lin, Liang},
  booktitle = {IEEE Transactions on Audio, Speech and Language Processing (<strong>TALSP</strong>)},
  year = {2024}
}

ICML’24

AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios

Zhongzhan Huang, Mingfu Liang, Shanshan Zhong, and Liang Lin

In The International Conference on Machine Learning (ICML), 2024

PDF Code

@inproceedings{AttSolver1,
  title = {AttNS: Attention-Inspired Numerical Solving For Limited Data Scenarios},
  author = {Huang, Zhongzhan and Liang, Mingfu and Zhong, Shanshan and Lin, Liang},
  booktitle = {The International Conference on Machine Learning (<strong>ICML</strong>)},
  year = {2024}
}

ICME’24

The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network

Zhongzhan Huang, Senwei Liang, Mingfu Liang, Wei He, Haizhao Yang, and Liang Lin

In IEEE International Conference on Multimedia & Expo (ICME Oral), 2024

PDF Code

@inproceedings{huang2022lottery,
  title = {The Lottery Ticket Hypothesis for Self-attention in Convolutional Neural Network},
  author = {Huang, Zhongzhan and Liang, Senwei and Liang, Mingfu and He, Wei and Yang, Haizhao and Lin, Liang},
  booktitle = {IEEE International Conference on Multimedia & Expo (<strong>ICME</strong> <strong style="color:red;">Oral</strong>)},
  year = {2024},
}

CVPR’24

Let’s Think Outside the Box: Exploring Leap-of-Thought in LLMs with Creative Humor Generation

Shanshan Zhong, (co-first) Zhongzhan Huang, Shanghua Gao, Wushao Wen, Liang Lin, Marinka Zitnik, and Pan Zhou

In The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024

PDF Code

@inproceedings{scale,
  title = {Let’s Think Outside the Box: Exploring Leap-of-Thought in LLMs with Creative Humor Generation},
  author = {Zhong, Shanshan and Huang, (co-first) Zhongzhan and Gao, Shanghua and Wen, Wushao and Lin, Liang and Zitnik, Marinka and Zhou, Pan},
  booktitle = {The IEEE/CVF Conference on Computer Vision and Pattern Recognition (<strong>CVPR</strong>)},
  year = {2024},
}

WWW’24

Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima

Shanshan Zhong, (co-first) Zhongzhan Huang, Daifeng Li, Wushao Wen, Jinghui Qin, and Liang Lin

In International World Wide Web Conference (WWW), 2024

PDF Code

@inproceedings{mg,
  title = {Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima},
  author = {Zhong, Shanshan and Huang, (co-first) Zhongzhan and Li, Daifeng and Wen, Wushao and Qin, Jinghui and Lin, Liang},
  booktitle = {International World Wide Web Conference  (<strong>WWW</strong>)},
  year = {2024}
}

2023

NeurIPS’23

ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection

Zhongzhan Huang, Pan Zhou, Shuicheng Yan, and Liang Lin

In The Conference on Neural Information Processing Systems (NeurIPS), 2023

PDF Code

@inproceedings{scalf,
  title = {ScaleLong: Towards More Stable Training of Diffusion Model via Scaling Network Long Skip Connection},
  author = {Huang, Zhongzhan and Zhou, Pan and Yan, Shuicheng and Lin, Liang},
  booktitle = {The Conference on Neural Information Processing Systems (<strong>NeurIPS</strong>)},
  year = {2023},
}

Sci. Reports

On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical Solver

Zhongzhan Huang, Senwei Liang, Hong Zhang, Haizhao Yang, and Liang Lin

In Scientific Reports (Sci. Reports), 2023

arXiv Code

@inproceedings{huang2022accelerating,
  title = {On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical Solver},
  author = {Huang, Zhongzhan and Liang, Senwei and Zhang, Hong and Yang, Haizhao and Lin, Liang},
  booktitle = {Scientific Reports (<strong>Sci. Reports</strong>)},
  year = {2023}
}

ACM MM’23

SUR-adapter: Enhancing text-to-image pre-trained diffusion models with large language models

Shanshan Zhong, (co-first) Zhongzhan Huang, Wushao Wen, Jinghui Qin, and Liang Lin

In 31th ACM International Conference on Multimedia (ACM MM Oral), 2023

arXiv Code

@inproceedings{zhong2023adapter,
  title = {SUR-adapter: Enhancing text-to-image pre-trained diffusion models with large language models},
  author = {Zhong, Shanshan and Huang, (co-first) Zhongzhan and Wen, Wushao and Qin, Jinghui and Lin, Liang},
  booktitle = {31th ACM International Conference on Multimedia (<strong>ACM MM </strong> <strong style="color:red;">Oral</strong>)},
  year = {2023},
  organization = {ACM Press}
}

ICCV’23

Understanding Self-attention Mechanism via Dynamical System Perspective

Zhongzhan Huang, Mingfu Liang, Jinghui Qin, Shanshan Zhong, and Liang Lin

In The IEEE/CVF International Conference on Computer Vision (ICCV), 2023

arXiv

@inproceedings{huang2023understanding,
  title = {Understanding Self-attention Mechanism via Dynamical System Perspective},
  author = {Huang, Zhongzhan and Liang, Mingfu and Qin, Jinghui and Zhong, Shanshan and Lin, Liang},
  booktitle = {The IEEE/CVF International Conference on Computer Vision (<strong>ICCV</strong>)},
  year = {2023}
}

Neurocomp.

ESA: Excitation-Switchable Attention for convolutional neural networks

Shanshan Zhong, Zhongzhan Huang, Wushao Wen, Zhijing Yang, and Jinghui Qin

In Neurocomputing (Neurocomp.), 2023

arXiv Code

@inproceedings{zhong2023esa,
  title = {ESA: Excitation-Switchable Attention for convolutional neural networks},
  author = {Zhong, Shanshan and Huang, Zhongzhan and Wen, Wushao and Yang, Zhijing and Qin, Jinghui},
  booktitle = {Neurocomputing (<strong>Neurocomp.</strong>)},
  pages = {126706},
  year = {2023},
  publisher = {Elsevier}
}

ICME’23

LSAS: Lightweight Sub-attention Strategy for Alleviating Attention Bias Problem

Shanshan Zhong, Wushao Wen, Jinghui Qin, Qiangpu Chen, and Zhongzhan Huang

In IEEE International Conference on Multimedia & Expo (ICME Oral), 2023

arXiv Code

@inproceedings{zhong2023lsas,
  title = {LSAS: Lightweight Sub-attention Strategy for Alleviating Attention Bias Problem},
  author = {Zhong, Shanshan and Wen, Wushao and Qin, Jinghui and Chen, Qiangpu and Huang, Zhongzhan},
  booktitle = {IEEE International Conference on Multimedia & Expo (<strong>ICME</strong> <strong style="color:red;">Oral</strong>)},
  year = {2023}
}

2022

EMNLP’22

CEM: Machine-Human Chatting Handoff via Causal-Enhance Module

Shanshan Zhong, Jinghui Qin, Zhongzhan Huang, and Daifeng Li

In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022

PDF Code

@inproceedings{zhong2022cem,
  title = {CEM: Machine-Human Chatting Handoff via Causal-Enhance Module},
  author = {Zhong, Shanshan and Qin, Jinghui and Huang, Zhongzhan and Li, Daifeng},
  booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (<strong>EMNLP</strong>)},
  pages = {3242--3253},
  year = {2022}
}

ICLR’22

Stiffness-aware neural network for learning Hamiltonian systems

Senwei Liang, Zhongzhan Huang, and Hong Zhang

In International Conference on Learning Representations (ICLR), 2022

PDF Code

@inproceedings{liang2021stiffness,
  title = {Stiffness-aware neural network for learning Hamiltonian systems},
  author = {Liang, Senwei and Huang, Zhongzhan and Zhang, Hong},
  booktitle = {International Conference on Learning Representations (<strong>ICLR</strong>)},
  year = {2022}
}

2021

NeurIPS’21

Rethinking the Pruning Criteria for Convolutional Neural Network

Zhongzhan Huang, Wenqi Shao, Xinjiang Wang, Liang Lin, and Ping Luo

In The Conference on Neural Information Processing Systems (NeurIPS), 2021

PDF

@inproceedings{huang2021convolution,
  title = {Rethinking the Pruning Criteria for Convolutional Neural Network},
  author = {Huang, Zhongzhan and Shao, Wenqi and Wang, Xinjiang and Lin, Liang and Luo, Ping},
  booktitle = {The Conference on Neural Information Processing Systems (<strong>NeurIPS</strong>)},
  year = {2021},
}

ICANN’21

Blending Pruning Criteria for Convolutional Neural Networks

Wei He, (co-first) Zhongzhan Huang, Mingfu Liang, Senwei Liang, and Haizhao Yang

In International Conference on Artificial Neural Networks (ICANN), 2021

PDF

@inproceedings{he2021blending,
  title = {Blending Pruning Criteria for Convolutional Neural Networks},
  author = {He, Wei and Huang, (co-first) Zhongzhan and Liang, Mingfu and Liang, Senwei and Yang, Haizhao},
  booktitle = {International Conference on Artificial Neural Networks (<strong>ICANN</strong>)},
  year = {2021},
}

ICRA’21

Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp

Junfan Lin, Zhongzhan Huang, Keze Wang, Xiaodan Liang, Weiwei Chen, and Liang Lin

In IEEE International Conference on Robotics and Automation (ICRA), 2021

PDF Code

@inproceedings{lin2020continuous,
  title = {Continuous Transition: Improving Sample Efficiency for Continuous Control Problems via MixUp},
  author = {Lin, Junfan and Huang, Zhongzhan and Wang, Keze and Liang, Xiaodan and Chen, Weiwei and Lin, Liang},
  year = {2021},
  booktitle = {IEEE International Conference on Robotics and Automation (<strong>ICRA</strong>)}
}

2020

AAAI’20

Instance enhancement batch normalization: An adaptive regulator of batch noise

Senwei Liang, (co-first) Zhongzhan Huang, Mingfu Liang, and Haizhao Yang

In The AAAI Conference on Artificial Intelligence (AAAI), 2020

PDF Code

@inproceedings{liang2020instance,
  title = {Instance enhancement batch normalization: An adaptive regulator of batch noise},
  author = {Liang, Senwei and Huang, (co-first) Zhongzhan and Liang, Mingfu and Yang, Haizhao},
  booktitle = {The AAAI Conference on Artificial Intelligence (<strong>AAAI</strong>)},
  year = {2020}
}

AAAI’20

DIANet: Dense-and-implicit attention network

Zhongzhan Huang, Senwei Liang, Mingfu Liang, and Haizhao Yang

In The AAAI Conference on Artificial Intelligence (AAAI), 2020

PDF Code

@inproceedings{huang2020dianet,
  title = {DIANet: Dense-and-implicit attention network},
  author = {Huang, Zhongzhan and Liang, Senwei and Liang, Mingfu and Yang, Haizhao},
  booktitle = {The AAAI Conference on Artificial Intelligence (<strong>AAAI</strong>)},
  year = {2020}
}

preprint

Arxiv

A Generic Shared Attention Mechanism for Various Backbone Neural Networks

Zhongzhan Huang, Senwei Liang, Mingfu Liang, and Liang Lin

In arXiv preprint (in submission), preprint

PDF Code

@inproceedings{huang2022layer,
  title = {A Generic Shared Attention Mechanism for Various Backbone Neural Networks},
  author = {Huang, Zhongzhan and Liang, Senwei and Liang, Mingfu and Lin, Liang},
  booktitle = {arXiv preprint (in submission)},
  year = {preprint}
}

Arxiv

Efficient Attention Network: Accelerate Attention by Searching Where to Plug

Zhongzhan Huang, Senwei Liang, Mingfu Liang, Wei He, and Haizhao Yang

In arXiv preprint (in submission), preprint

PDF Code

@inproceedings{huang2020efficient,
  title = {Efficient Attention Network: Accelerate Attention by Searching Where to Plug},
  author = {Huang, Zhongzhan and Liang, Senwei and Liang, Mingfu and He, Wei and Yang, Haizhao},
  booktitle = {arXiv preprint (in submission)},
  year = {preprint}
}

Arxiv

AlterSGD: Finding Flat Minima for Continual Learning by Alternative Training

Zhongzhan Huang, Mingfu Liang, Senwei Liang, and Wei He

In arXiv preprint (in submission), preprint

PDF

@inproceedings{huang2021altersgd,
  title = {AlterSGD: Finding Flat Minima for Continual Learning by Alternative Training},
  author = {Huang, Zhongzhan and Liang, Mingfu and Liang, Senwei and He, Wei},
  booktitle = {arXiv preprint (in submission)},
  year = {preprint}
}

Arxiv

Deepening Neural Networks Implicitly and Locally via Recurrent Attention Strategy

Shanshan Zhong, Zhongzhan Huang, Wushao Wen, and Liang Lin

In arXiv preprint (in submission), preprint

PDF Code

@inproceedings{ram,
  title = {Deepening Neural Networks Implicitly and Locally via Recurrent Attention Strategy},
  author = {Zhong, Shanshan and Huang, Zhongzhan and Wen, Wushao and Lin, Liang},
  booktitle = {arXiv preprint (in submission)},
  year = {preprint}
}