Anke Tang

According to our database, Anke Tang authored at least 23 papers between 2023 and 2026.

Collaborative distances:

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

2026

Efficient and Effective Weight-Ensembling Mixture of Experts for Multi-Task Model Merging.

Li Shen, Anke Tang, Enneng Yang, Guibing Guo, Yong Luo, Lefei Zhang, Xiaochun Cao, Bo Du, Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., March, 2026

ACE-Brain-0: Spatial Intelligence as a Shared Scaffold for Universal Embodiments.

Ziyang Gong, Zehang Luo, Anke Tang, Zhe Liu, Shi Fu, Zhi Hou, Ganlin Yang, Weiyun Wang, Xiaofeng Wang, Jianbo Liu, Gen Luo, Haolan Kang, Shuang Luo, Yue Zhou, Yong Luo, Li Shen, Xiaosong Jia, Yao Mu, Xue Yang, Chunxiao Liu, Junchi Yan, Hengshuang Zhao, Dacheng Tao, Xiaogang Wang

CoRR, March, 2026

Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models.

Anke Tang, Li Shen, Yong Luo, Shuai Xie, Han Hu, Lefei Zhang, Bo Du, Dacheng Tao

IEEE Trans. Pattern Anal. Mach. Intell., February, 2026

Understanding Model Merging: A Unified Generalization Framework for Heterogeneous Experts.

Qinglun Li, Anke Tang, Miao Zhang, Mengzhu Wang, Quanjun Yin, Li Shen

CoRR, January, 2026

2025

Data-Adaptive Weight-Ensembling for Multi-task Model Fusion.

Anke Tang, Li Shen, Yong Luo, Shiwei Liu, Han Hu, Bo Du, Dacheng Tao

Int. J. Comput. Vis., August, 2025

Unsupervised deep learning model for fast energy layer pre-selection of delivery-efficient proton arc therapy plan optimization of nasopharyngeal carcinoma.

Bohan Yang, Gang Liu, Rirao Dao, Yujia Qian, Ke Shi, Anke Tang, Yong Luo, Jingnan Liu

CoRR, June, 2025

Mix Data or Merge Models? Balancing the Helpfulness, Honesty, and Harmlessness of Large Language Model via Model Merging.

Jinluan Yang, Dingnan Jin, Anke Tang, Li Shen, Didi Zhu, Zhengyu Chen, Daixin Wang, Qing Cui, Zhiqiang Zhang, Jun Zhou, Fei Wu, Kun Kuang

CoRR, February, 2025

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging.

Anke Tang, Enneng Yang, Li Shen, Yong Luo, Han Hu, Bo Du, Dacheng Tao

CoRR, January, 2025

Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent.

Yongxian Wei, Anke Tang, Li Shen, Chun Yuan, Xiaochun Cao

CoRR, January, 2025

Learning from models beyond fine-tuning.

Hongling Zheng, Li Shen, Anke Tang, Yong Luo, Han Hu, Bo Du, Yonggang Wen, Dacheng Tao

Nat. Mac. Intell., 2025

FusionBench: A Unified Library and Comprehensive Benchmark for Deep Model Fusion.

Anke Tang, Li Shen, Yong Luo, Enneng Yang, Han Hu, Lefei Zhang, Bo Du, Dacheng Tao

J. Mach. Learn. Res., 2025

Successive Mouse Movement: Dual-Phase Adaptation with Pre-balancing and Test-Time Learning.

Jingyi Feng, Yong Luo, Anke Tang, Xuxu Liu

Proceedings of the Neural Information Processing - 32nd International Conference, 2025

Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent.

Yongxian Wei, Anke Tang, Li Shen, Zixuan Hu, Chun Yuan, Xiaochun Cao

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Targeted Low-rank Refinement: Enhancing Sparse Language Models with Precision.

Li Shen, Anke Tang, Yong Luo, Tao Sun, Han Hu, Xiaochun Cao

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace.

Jinluan Yang, Anke Tang, Didi Zhu, Zhengyu Chen, Li Shen, Fei Wu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

SMILE: Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models.

Anke Tang, Li Shen, Yong Luo, Shuai Xie, Han Hu, Lefei Zhang, Bo Du, Dacheng Tao

CoRR, 2024

Towards Efficient Pareto Set Approximation via Mixture of Experts Based Model Fusion.

Anke Tang, Li Shen, Yong Luo, Shiwei Liu, Han Hu, Bo Du

CoRR, 2024

FusionBench: A Comprehensive Benchmark of Deep Model Fusion.

Anke Tang, Li Shen, Yong Luo, Han Hu, Bo Du, Dacheng Tao

CoRR, 2024

Merging Multi-Task Models via Weight-Ensembling Mixture of Experts.

Anke Tang, Li Shen, Yong Luo, Nan Yin, Lefei Zhang, Dacheng Tao

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

Parameter-Efficient Multi-Task Model Fusion with Partial Linearization.

Anke Tang, Li Shen, Yong Luo, Yibing Zhan, Han Hu, Bo Du, Yixin Chen, Dacheng Tao

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Concrete Subspace Learning based Interference Elimination for Multi-task Model Fusion.

Anke Tang, Li Shen, Yong Luo, Liang Ding, Han Hu, Bo Du, Dacheng Tao

CoRR, 2023

Learn From Model Beyond Fine-Tuning: A Survey.

Hongling Zheng, Li Shen, Anke Tang, Yong Luo, Han Hu, Bo Du, Dacheng Tao

CoRR, 2023

Improving Heterogeneous Model Reuse by Density Estimation.

Anke Tang, Yong Luo, Han Hu, Fengxiang He, Kehua Su, Bo Du, Yixin Chen, Dacheng Tao

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023