Zicheng Liu

According to our database, Zicheng Liu authored at least 34 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

GenURL: A General Framework for Unsupervised Representation Learning.

Siyuan Li, Zicheng Liu, Zelin Zang, Di Wu, Zhiyuan Chen, Stan Z. Li

IEEE Trans. Neural Networks Learn. Syst., January, 2025

2024

Homophily-Enhanced Self-Supervision for Graph Structure Learning: Insights and Directions.

Lirong Wu, Haitao Lin, Zihan Liu, Zicheng Liu, Yufei Huang, Stan Z. Li

IEEE Trans. Neural Networks Learn. Syst., September, 2024

Beyond Homophily and Homogeneity Assumption: Relation-Based Frequency Adaptive Graph Neural Networks.

Lirong Wu, Haitao Lin, Bozhen Hu, Cheng Tan, Zhangyang Gao, Zicheng Liu, Stan Z. Li

IEEE Trans. Neural Networks Learn. Syst., June, 2024

Unveiling the Backbone-Optimizer Coupling Bias in Visual Representation Learning.

Siyuan Li, Juanxi Tian, Zedong Wang, Luyuan Zhang, Zicheng Liu, Weiyang Jin, Yang Liu, Baigui Sun, Stan Z. Li

CoRR, 2024

A Survey on Mixup Augmentations and Beyond.

Xin Jin, Hongyu Zhu, Siyuan Li, Zedong Wang, Zicheng Liu, Chang Yu, Huafeng Qin, Stan Z. Li

CoRR, 2024

CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph.

Haitao Lin, Guojiang Zhao, Odin Zhang, Yufei Huang, Lirong Wu, Zicheng Liu, Siyuan Li, Cheng Tan, Zhifeng Gao, Stan Z. Li

CoRR, 2024

Peer Review as A Multi-Turn and Long-Context Dialogue with Role-Based Interactions.

Cheng Tan, Dongxin Lyu, Siyuan Li, Zhangyang Gao, Jingxuan Wei, Siqi Ma, Zicheng Liu, Stan Z. Li

CoRR, 2024

GenBench: A Benchmarking Suite for Systematic Evaluation of Genomic Foundation Models.

Zicheng Liu, Jiahui Li, Siyuan Li, Zelin Zang, Cheng Tan, Yufei Huang, Yajing Bai, Stan Z. Li

CoRR, 2024

Switch EMA: A Free Lunch for Better Flatness and Sharpness.

Siyuan Li, Zicheng Liu, Juanxi Tian, Ge Wang, Zedong Wang, Weiyang Jin, Di Wu, Cheng Tan, Tao Lin, Yang Liu, Baigui Sun, Stan Z. Li

CoRR, 2024

Masked Modeling for Self-supervised Representation Learning on Vision and Beyond.

Siyuan Li, Luyuan Zhang, Zedong Wang, Di Wu, Lirong Wu, Zicheng Liu, Jun Xia, Cheng Tan, Yang Liu, Baigui Sun, Stan Z. Li

CoRR, 2024

LongVQ: Long Sequence Modeling with Vector Quantization on Structured Memory.

Zicheng Liu, Li Wang, Siyuan Li, Zedong Wang, Haitao Lin, Stan Z. Li

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

PPFLOW: Target-Aware Peptide Design with Torsional Flow Matching.

Haitao Lin, Odin Zhang, Huifeng Zhao, Dejun Jiang, Lirong Wu, Zicheng Liu, Yufei Huang, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling.

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Cheng Tan, Jiangbin Zheng, Yufei Huang, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Short-Long Convolutions Help Hardware-Efficient Linear Attention to Focus on Long Sequences.

Zicheng Liu, Siyuan Li, Li Wang, Zedong Wang, Yunfan Liu, Stan Z. Li

Proceedings of the Forty-first International Conference on Machine Learning, 2024

MogaNet: Multi-order Gated Aggregation Network.

Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

SemiReward: A General Reward Model for Semi-supervised Learning.

Siyuan Li, Weiyang Jin, Zedong Wang, Fang Wu, Zicheng Liu, Cheng Tan, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design.

Cheng Tan, Yijie Zhang, Zhangyang Gao, Bozhen Hu, Siyuan Li, Zicheng Liu, Stan Z. Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

PSC-CPI: Multi-Scale Protein Sequence-Structure Contrasting for Efficient and Generalizable Compound-Protein Interaction Prediction.

Lirong Wu, Yufei Huang, Cheng Tan, Zhangyang Gao, Bozhen Hu, Haitao Lin, Zicheng Liu, Stan Z. Li

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning.

Cheng Tan, Siyuan Li, Zhangyang Gao, Wenfei Guan, Zedong Wang, Zicheng Liu, Lirong Wu, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Harnessing Hard Mixed Samples with Decoupled Regularizer.

Zicheng Liu, Siyuan Li, Ge Wang, Lirong Wu, Cheng Tan, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Federated Learning for Inference at Anytime and Anywhere.

Zicheng Liu, Da Li, Javier Fernández-Marqués, Stefanos Laskaridis, Yan Gao, Lukasz Dudziak, Stan Z. Li, Shell Xu Hu, Timothy M. Hospedales

CoRR, 2022

Efficient Multi-order Gated Aggregation Network.

Siyuan Li, Zedong Wang, Zicheng Liu, Cheng Tan, Haitao Lin, Di Wu, Zhiyuan Chen, Jiangbin Zheng, Stan Z. Li

CoRR, 2022

Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation.

Lirong Wu, Yufei Huang, Haitao Lin, Zicheng Liu, Tianyu Fan, Stan Z. Li

CoRR, 2022

Teaching Yourself: Graph Self-Distillation on Neighborhood for Node Classification.

Lirong Wu, Jun Xia, Haitao Lin, Zhangyang Gao, Zicheng Liu, Guojiang Zhao, Stan Z. Li

CoRR, 2022

OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning.

Siyuan Li, Zedong Wang, Zicheng Liu, Di Wu, Stan Z. Li

CoRR, 2022

Decoupled Mixup for Data-efficient Learning.

Zicheng Liu, Siyuan Li, Ge Wang, Cheng Tan, Lirong Wu, Stan Z. Li

CoRR, 2022

Generalized Clustering and Multi-Manifold Learning with Geometric Structure Preservation.

Lirong Wu, Zicheng Liu, Jun Xia, Zelin Zang, Siyuan Li, Stan Z. Li

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Towards Reasonable Budget Allocation in Untargeted Graph Structure Attacks via Gradient Debias.

Zihan Liu, Yun Luo, Lirong Wu, Zicheng Liu, Stan Z. Li

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

AutoMix: Unveiling the Power of Mixup for Stronger Classifiers.

Zicheng Liu, Siyuan Li, Di Wu, Zihan Liu, Zhiyuan Chen, Lirong Wu, Stan Z. Li

Proceedings of the Computer Vision, 2022

Are Gradients on Graph Structure Reliable in Gray-box Attacks?

Zihan Liu, Yun Luo, Lirong Wu, Siyuan Li, Zicheng Liu, Stan Z. Li

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

2021

Boosting Discriminative Visual Representation Learning with Scenario-Agnostic Mixup.

Siyuan Li, Zicheng Liu, Di Wu, Zihan Liu, Stan Z. Li

CoRR, 2021

An interpretable prediction model for longitudinal dispersion coefficient in natural streams based on evolutionary symbolic regression network.

Yifeng Zhao, Zicheng Liu, Pei Zhang, Stan Z. Li, Sergio Andres Galindo-Torres

CoRR, 2021

AutoMix: Unveiling the Power of Mixup.

Zicheng Liu, Siyuan Li, Di Wu, Zhiyuan Chen, Lirong Wu, Jianzhu Guo, Stan Z. Li

CoRR, 2021

2020

Deep Clustering and Representation Learning that Preserves Geometric Structures.

Lirong Wu, Zicheng Liu, Zelin Zang, Jun Xia, Siyuan Li, Stan Z. Li

CoRR, 2020