@inproceedings{kong2025PL,
title={Preserving Label Correlation for Multi-label Text Classification by Prototypical Regularizations},
author={Kong, Fanshuang and Zhang, Richong and Guo, Xiaohui and Chen, Junfan and Wang, Ziqiao},
booktitle={Proceedings of the ACM on Web Conference},
year={2025}
}
@inproceedings{kong2025LH,
title={LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning},
author={Kong, Fanshuang and Zhang, Richong and Wang, Ziqiao},
booktitle={Proceedings of the 31th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
year={2025}
}
@inproceedings{
wang2024generalization,
title={Generalization Bounds via Conditional \$f\$-Information},
author={Ziqiao Wang and Yongyi Mao},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=ocxVXe5XN1}
}
@inproceedings{
wang2024on,
title={On \$f\$-Divergence Principled Domain Adaptation: An Improved Framework},
author={Ziqiao Wang and Yongyi Mao},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024},
url={https://openreview.net/forum?id=xSU27DgWEr}
}
@inproceedings{kong2024unsupervised,
title={On Unsupervised Domain Adaptation: Pseudo Label Guided Mixup for Adversarial Prompt Tuning},
author={Kong, Fanshuang and Zhang, Richong and Wang, Ziqiao and Mao, Yongyi},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={38},
number={16},
pages={18399--18407},
year={2024}
}
@inproceedings{huang2024cross,
title={Cross-Modal and Uni-Modal Soft-Label Alignment for Image-Text Retrieval},
author={Huang, Hailang and Nie, Zhijie and Wang, Ziqiao and Shang, Ziyu},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
volume={38},
number={16},
pages={18298--18306},
year={2024}
}
@inproceedings{
Wang2023sampleconditioned,
title={Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds},
author={Ziqiao Wang and Yongyi Mao},
booktitle={Thirty-seventh Conference on Neural Information Processing Systems},
year={2023},
url={https://openreview.net/forum?id=oqDSDKLd3S}
}
@inproceedings{
wang2022on,
title={On the Generalization of Models Trained with {SGD}: Information-Theoretic Bounds and Implications},
author={Ziqiao Wang and Yongyi Mao},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=oWZsQ8o5EA}
}
@inproceedings{Wang2022a,
author = {Ziqiao Wang and Yongyi Mao},
title = {Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States},
booktitle = {Proceedings of the Fortieth Conference on Uncertainty in Artificial Intelligence},
year = {2024},
url={https://openreview.net/pdf?id=ZhMkLTWRyh}
}
@inproceedings{
wang2023two,
title={Two Facets of {SDE} Under an Information-Theoretic Lens: Generalization of {SGD} via Training Trajectories and via Terminal States},
author={Ziqiao Wang and Yongyi Mao},
booktitle={NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning},
year={2023},
url={https://openreview.net/forum?id=hWDqKtIwSo}
}
@inproceedings{
liu2023overtraining,
title={Over-Training with Mixup May Hurt Generalization},
author={Zixuan Liu and Ziqiao Wang and Hongyu Guo and Yongyi Mao},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=JmkjrlVE-DG}
}
@article{Wang2020,
author = {Ziqiao Wang and Yongyi Mao and Hongyu Guo and Richong Zhang},
title = {On SkipGram Word Embedding Models with Negative Sampling: Unified Framework and Impact of Noise Distributions},
journal = {CoRR},
year = {2020},
volume = {abs/2009.04413},
url = {https://arxiv.org/abs/2009.04413}
}
@inproceedings{
wang2023informationtheoretic,
title={Information-Theoretic Analysis of Unsupervised Domain Adaptation},
author={Ziqiao Wang and Yongyi Mao},
booktitle={The Eleventh International Conference on Learning Representations },
year={2023},
url={https://openreview.net/forum?id=c5tbxWXU9-y}
}
@inproceedings{wang2023tighter,
title={Tighter Information-Theoretic Generalization Bounds from Supersamples},
author={Wang, Ziqiao and Mao, Yongyi},
booktitle={International Conference on Machine Learning},
year={2023},
organization={PMLR}
}
* denotes equal contribution.
Preprints
Generalization in Federated Learning: A Conditional Mutual Information Framework
Ziqiao Wang, Cheng Long, and Yongyi Mao
Under Review, [Arxiv].
Revisiting Weak-to-Strong Generalization in Theory and Practice: Reverse KL vs. Forward KL
Wei Yao, Wenkai Yang, Ziqiao Wang, Yankai Lin, and Yong Liu
Under Review, [Arxiv].
Understanding the Capabilities and Limitations of Weak-to-Strong Generalization
Wei Yao, Wenkai Yang, Ziqiao Wang, Yankai Lin, and Yong Liu
Under Review, [Arxiv].
Distributional Information Embedding: A Framework for Multi-bit Watermarking
Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, and Yuheng Bu
Under Review, [Arxiv].
Fine-tuning Aligned Classifiers for Merging Outputs: Towards a Superior Evaluation Protocol in Model Merging
Fanshuang Kong, Richong Zhang, Zhijie Nie, Ziqiao Wang, and Qiang Sun
Under Review, [Arxiv].
Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, and Yuheng Bu
Under Review, [Arxiv][Poster].
Activated Parameter Locating via Causal Intervention for Model Merging
Fanshuang Kong, Richong Zhang, and Ziqiao Wang
Under Review, [Arxiv].
On SkipGram Word Embedding Models with Negative Sampling: Unified Framework and Impact of Noise Distributions
Ziqiao Wang, Yongyi Mao, Hongyu Guo, and Richong Zhang
arXiv preprint arXiv:2009.04413, 2020, [Arxiv][Poster][BibTeX].
Conference Publications
Preserving Label Correlation for Multi-label Text Classification by Prototypical Regularizations
Fanshuang Kong, Richong Zhang, Xiaohui Guo, Junfan Chen, and Ziqiao Wang
Proceedings of the ACM on Web Conference (WWW) 2025, [BibTeX].
LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning
Fanshuang Kong, Richong Zhang, and Ziqiao Wang
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2025, [Arxiv][Code][BibTeX].
Generalization Bounds via Conditional \(f\)-Information
Ziqiao Wang and Yongyi Mao
Advances in Neural Information Processing Systems (NeurIPS) 2024, [Arxiv][Code][Poster][BibTeX].
On \(f\)-Divergence Principled Domain Adaptation: An Improved Framework
Ziqiao Wang and Yongyi Mao
Advances in Neural Information Processing Systems (NeurIPS) 2024, [Arxiv][Code][Poster][BibTeX].
Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States
Ziqiao Wang and Yongyi Mao
Conference on Uncertainty in Artificial Intelligence (UAI) 2024, [Arxiv][BibTeX].
On Unsupervised Domain Adaptation: Pseudo Label Guided Mixup for Adversarial Prompt Tuning
Fanshuang Kong, Richong Zhang, Ziqiao Wang, and Yongyi Mao
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2024, [Code][Poster][BibTeX].
Cross-modal and Uni-modal Soft-label Alignment for Image-Text Retrieval
Hailang Huang, Zhijie Nie, Ziqiao Wang, and Ziyu Shang
Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) 2024, [Arxiv][Code][Poster][BibTeX].
Sample-Conditioned Hypothesis Stability Sharpens Information-Theoretic Generalization Bounds
Ziqiao Wang and Yongyi Mao
Advances in Neural Information Processing Systems (NeurIPS) 2023, [Arxiv] [Poster] [BibTeX].
Tighter Information-Theoretic Generalization Bounds from Supersamples
Ziqiao Wang and Yongyi Mao
International Conference on Machine Learning (ICML) 2023 (Oral Presentation, top 2.2% of submissions), [Arxiv][Code][Poster][BibTeX].
Information-Theoretic Analysis of Unsupervised Domain Adaptation
Ziqiao Wang and Yongyi Mao
International Conference on Learning Representations (ICLR) 2023, [Arxiv][Poster][BibTeX].
Over-Training with Mixup May Hurt Generalization
Zixuan Liu*, Ziqiao Wang*, Hongyu Guo, and Yongyi Mao
International Conference on Learning Representations (ICLR) 2023, [Arxiv][BibTeX].
On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
Ziqiao Wang and Yongyi Mao
International Conference on Learning Representations (ICLR) 2022, [Arxiv][Poster][BibTeX].
Workshop Papers
Understanding the Capabilities and Limitations of Weak-to-Strong Generalization
Wei Yao, Wenkai Yang, Ziqiao Wang, Yankai Lin, and Yong Liu
ICLR 2025 Workshop on Self-Improving Foundation Models Without Human Supervision (SSI-FM).
Distributional Information Embedding: A Framework for Multi-bit Watermarking
Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, and Yuheng Bu
ICLR 2025 Workshop on GenAI Watermarking (WMark).
Theoretically Grounded Framework for LLM Watermarking: A Distribution-Adaptive Approach
Haiyun He, Yepeng Liu, Ziqiao Wang, Yongyi Mao, and Yuheng Bu
ICLR 2025 Workshop on GenAI Watermarking (WMark).
On \(f\)-Divergence Principled Domain Adaptation: An Improved Framework
Ziqiao Wang and Yongyi Mao
18th Canadian Workshop on Information Theory (CWIT 2024).
Two Facets of SDE Under an Information-Theoretic Lens: Generalization of SGD via Training Trajectories and via Terminal States
Ziqiao Wang and Yongyi Mao
NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning (M3L), [Poster] [BibTeX].
Over-Training with Mixup May Hurt Generalization
Zixuan Liu*, Ziqiao Wang*, Hongyu Guo, and Yongyi Mao
NeurIPS 2022 Workshop on Interpolation Regularizers and Beyond, [Poster].
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