Zhongzhan Huang (黄中展)

@inproceedings{minilong,
  title = {MiniLongBench: The Low-cost Long Context Understanding Benchmark for Large Language Models},
  author = {Huang, Zhongzhan and Ling, Guoming and Zhong, Shanshan and Wu, Hefeng and Lin, Liang},
  booktitle = {The Annual Meeting of the Association for Computational Linguistics (<strong>ACL</strong>)},
  year = {2025}
}

@inproceedings{router,
  title = {Routereval: A Comprehensive Benchmark for Routing LLMs to Explore Model-level Scaling Up in LLMs},
  author = {Huang, Zhongzhan and Ling, Guoming and Liang, Vincent and Lin, Yupei and Chen, Yandong and Zhong, Shanshan and Wu, Hefeng and Lin, Liang},
  booktitle = {arXiv preprint (in submission)},
  year = {preprint}
}

@inproceedings{pami,
  title = {A Causality-aware Paradigm for Evaluating Creativity of Multimodal Large Language Models},
  author = {Huang, Zhongzhan and Zhong, Shanshan and Zhou, Pan and Gao, Shanghua and Marinka, Zitnik and Lin, Liang},
  booktitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence (<strong>IEEE TPAMI</strong>)},
  year = {2025}
}

@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}
}

@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}
}

@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},
}

@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},
}

@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}
}

@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}
}

@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}
}

@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}
}

@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}
}

@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},
}