Rubing Yang

According to our database, Rubing Yang authored at least 10 papers between 2022 and 2026.

Collaborative distances:

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

2026

AngelSlim: A more accessible, comprehensive, and efficient toolkit for large model compression.

Rui Cen, Qiangqiang Hu, Hong Huang, Hong Liu, Song Liu, Xin Luo, Lin Niu, Yifan Tan, Decheng Wu, Linchuan Xie, Rubing Yang, Guanghua Yu, Jianchen Zhu

CoRR, February, 2026

CIMinus: Empowering Sparse DNN Workloads Modeling and Exploration on SRAM-Based CIM Architectures.

Yingjie Qi, Jianlei Yang, Rubing Yang, Cenlin Duan, Xiaolin He, Ziyan He, Weitao Pan, Weisheng Zhao

IEEE Trans. Computers, January, 2026

SlimInfer: Accelerating Long-Context LLM Inference via Dynamic Token Pruning.

Lingkun Long, Rubing Yang, Yushi Huang, Desheng Hui, Ao Zhou, Jianlei Yang

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

SpecExit: Accelerating Large Reasoning Model via Speculative Exit.

Rubing Yang, Huajun Bai, Song Liu, Guanghua Yu, Runzhi Fan, Yanbin Dang, Jiejing Zhang, Kai Liu, Jianchen Zhu, Peng Chen

CoRR, September, 2025

HPIM: Heterogeneous Processing-In-Memory-based Accelerator for Large Language Models Inference.

Cenlin Duan, Jianlei Yang, Rubing Yang, Yikun Wang, Yiou Wang, Lingkun Long, Yingjie Qi, Xiaolin He, Ao Zhou, Xueyan Wang, Weisheng Zhao

CoRR, September, 2025

An Effective Gram Matrix Characterizes Generalization in Deep Networks.

Rubing Yang, Pratik Chaudhari

CoRR, April, 2025

2024

Prospective Learning: Learning for a Dynamic Future.

Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Joshua T. Vogelstein, Pratik Chaudhari

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold.

Jialin Mao, Itay Griniasty, Han Kheng Teoh, Rahul Ramesh, Rubing Yang, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari

CoRR, 2023

A Picture of the Space of Typical Learnable Tasks.

Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari

Proceedings of the International Conference on Machine Learning, 2023

2022

Does the Data Induce Capacity Control in Deep Learning?

Rubing Yang, Jialin Mao, Pratik Chaudhari

Proceedings of the International Conference on Machine Learning, 2022