Rui-Jie Zhu

According to our database, Rui-Jie Zhu authored at least 38 papers between 2022 and 2025.

Collaborative distances:

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

2025

MagicTime: Time-Lapse Video Generation Models as Metamorphic Simulators.

Shenghai Yuan, Jinfa Huang, Yujun Shi, Yongqi Xu, Ruijie Zhu, Bin Lin, Xinhua Cheng, Li Yuan, Jiebo Luo

IEEE Trans. Pattern Anal. Mach. Intell., September, 2025

Scaling Linear Attention with Sparse State Expansion.

Yuqi Pan, Yongqi An, Zheng Li, Yuhong Chou, Rui-Jie Zhu, Xiaohui Wang, Mingxuan Wang, Jinqiao Wang, Guoqi Li

CoRR, July, 2025

A Systematic Analysis of Hybrid Linear Attention.

Dustin Wang, Rui-Jie Zhu, Steven Abreu, Yong Shan, Taylor Kergan, Yuqi Pan, Yuhong Chou, Zheng Li, Ge Zhang, Wenhao Huang, Jason Eshraghian

CoRR, July, 2025

A Survey on Latent Reasoning.

Ruijie Zhu, Tianhao Peng, Tianhao Cheng, Xingwei Qu, Jinfa Huang, Dawei Zhu, Hao Wang, Kaiwen Xue, Xuanliang Zhang, Yong Shan, Tianle Cai, Taylor Kergan, Assel Kembay, Andrew Smith, Chenghua Lin, Binh Nguyen, Yuqi Pan, Yuhong Chou, Zefan Cai, Zhenhe Wu, Yongchi Zhao, Tianyu Liu, Jian Yang, Wangchunshu Zhou, Chujie Zheng, Chongxuan Li, Yuyin Zhou, Zhoujun Li, Zhaoxiang Zhang, Jiaheng Liu, Ge Zhang, Wenhao Huang, Jason Eshraghian

CoRR, July, 2025

ZeCO: Zero Communication Overhead Sequence Parallelism for Linear Attention.

Yuhong Chou, Zehao Liu, Rui-Jie Zhu, Xinyi Wan, Tianjian Li, Congying Chu, Qian Liu, Jibin Wu, Zejun Ma

CoRR, July, 2025

TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks.

Rui-Jie Zhu, Malu Zhang, Qihang Zhao, Haoyu Deng, Yule Duan, Liang-Jian Deng

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

Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2.

Steven Abreu, Sumit Bam Shrestha, Rui-Jie Zhu, Jason Eshraghian

CoRR, March, 2025

A Comprehensive Survey on Long Context Language Modeling.

Jiaheng Liu, Dawei Zhu, Zhiqi Bai, Yancheng He, Huanxuan Liao, Haoran Que, Zekun Wang, Chenchen Zhang, Ge Zhang, Jiebin Zhang, Yuanxing Zhang, Zhuo Chen, Hangyu Guo, Shilong Li, Ziqiang Liu, Yong Shan, Yifan Song, Jiayi Tian, Wenhao Wu, Zhejian Zhou, Ruijie Zhu, Junlan Feng, Yang Gao, Shizhu He, Zhoujun Li, Tianyu Liu, Fanyu Meng, Wenbo Su, Yingshui Tan, Zili Wang, Jian Yang, Wei Ye, Bo Zheng, Wangchunshu Zhou, Wenhao Huang, Sujian Li, Zhaoxiang Zhang

CoRR, March, 2025

SDTrack: A Baseline for Event-based Tracking via Spiking Neural Networks.

Yimeng Shan, Zhenbang Ren, Haodi Wu, Wenjie Wei, Rui-Jie Zhu, Shuai Wang, Dehao Zhang, Yichen Xiao, Jieyuan Zhang, Kexin Shi, Jingzhinan Wang, Jason K. Eshraghian, Haicheng Qu, Jiqing Zhang, Malu Zhang, Yang Yang

CoRR, March, 2025

ARFlow: Autogressive Flow with Hybrid Linear Attention.

Mude Hui, Rui-Jie Zhu, Songlin Yang, Yu Zhang, Zirui Wang, Yuyin Zhou, Jason Eshraghian, Cihang Xie

CoRR, January, 2025

Learnable Sparsification of Die-to-Die Communication via Spike-Based Encoding.

Joshua Nardone, Ruijie Zhu, Joseph Callenes, Mohammed E. Elbtity, Ramtin Zand, Jason Eshraghian

CoRR, January, 2025

Quantized Spike-driven Transformer.

Xuerui Qiu, Malu Zhang, Jieyuan Zhang, Wenjie Wei, Honglin Cao, Junsheng Guo, Rui-Jie Zhu, Yimeng Shan, Yang Yang, Haizhou Li

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Advancing Spiking Neural Networks Towards Multiscale Spatiotemporal Interaction Learning.

Yimeng Shan, Malu Zhang, Ruijie Zhu, Xuerui Qiu, Jason K. Eshraghian, Haicheng Qu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Bridging the gap between artificial intelligence and natural intelligence.

Rui-Jie Zhu, Skye Gunasekaran, Jason Eshraghian

Nat. Comput. Sci., August, 2024

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks.

Rui-Jie Zhu, Qihang Zhao, Guoqi Li, Jason Eshraghian

Trans. Mach. Learn. Res., 2024

Tensor decomposition based attention module for spiking neural networks.

Haoyu Deng, Rui-Jie Zhu, Xuerui Qiu, Yule Duan, Malu Zhang, Liang-Jian Deng

Knowl. Based Syst., 2024

Future-Guided Learning: A Predictive Approach To Enhance Time-Series Forecasting.

Skye Gunasekaran, Assel Kembay, Hugo J. Ladret, Rui-Jie Zhu, Laurent Perrinet, Omid Kavehei, Jason Eshraghian

CoRR, 2024

CopyLens: Dynamically Flagging Copyrighted Sub-Dataset Contributions to LLM Outputs.

Qichao Ma, Rui-Jie Zhu, Peiye Liu, Renye Yan, Fahong Zhang, Ling Liang, Meng Li, Zhaofei Yu, Zongwei Wang, Yimao Cai, Tiejun Huang

CoRR, 2024

Scalable MatMul-free Language Modeling.

Rui-Jie Zhu, Yu Zhang, Ethan Sifferman, Tyler Sheaves, Yiqiao Wang, Dustin Richmond, Peng Zhou, Jason K. Eshraghian

CoRR, 2024

Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence.

Bo Peng, Daniel Goldstein, Quentin Anthony, Alon Albalak, Eric Alcaide, Stella Biderman, Eugene Cheah, Xingjian Du, Teddy Ferdinan, Haowen Hou, Przemyslaw Kazienko, Kranthi Kiran GV, Jan Kocon, Bartlomiej Koptyra, Satyapriya Krishna, Ronald McClelland Jr., Niklas Muennighoff, Fares Obeid, Atsushi Saito, Guangyu Song, Haoqin Tu, Stanislaw Wozniak, Ruichong Zhang, Bingchen Zhao, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu

CoRR, 2024

ChronoMagic-Bench: A Benchmark for Metamorphic Evaluation of Text-to-Time-lapse Video Generation.

Shenghai Yuan, Jinfa Huang, Yongqi Xu, Yaoyang Liu, Shaofeng Zhang, Yujun Shi, Ruijie Zhu, Xinhua Cheng, Jiebo Luo, Li Yuan

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

MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map.

Yuhong Chou, Man Yao, Kexin Wang, Yuqi Pan, Rui-Jie Zhu, Jibin Wu, Yiran Zhong, Yu Qiao, Bo Xu, Guoqi Li

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

Gated Slot Attention for Efficient Linear-Time Sequence Modeling.

Yu Zhang, Songlin Yang, Rui-Jie Zhu, Yue Zhang, Leyang Cui, Yiqiao Wang, Bolun Wang, Freda Shi, Bailin Wang, Wei Bi, Peng Zhou, Guohong Fu

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

Autonomous Driving with Spiking Neural Networks.

Ruijie Zhu, Ziqing Wang, Leilani Gilpin, Jason Eshraghian

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

Reducing Data Bottlenecks in Distributed, Heterogeneous Neural Networks.

Ruhai Lin, Rui-Jie Zhu, Jason K. Eshraghian

Proceedings of the 17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, 2024

Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural Networks: from Algorithms to Technology.

Souvik Kundu, Rui-Jie Zhu, Akhilesh Jaiswal, Peter A. Beerel

Proceedings of the IEEE International Conference on Acoustics, 2024

What do Transformers have to learn from Biological Spiking Neural Networks?

Jason K. Eshraghian, Rui-Jie Zhu

Proceedings of the International Conference on Compilers, 2024

Gated Attention Coding for Training High-Performance and Efficient Spiking Neural Networks.

Xuerui Qiu, Rui-Jie Zhu, Yuhong Chou, Zhaorui Wang, Liang-Jian Deng, Guoqi Li

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

2023

Towards popularity prediction of information cascades via degree distribution and deep neural networks.

Xiaodong Feng, Qihang Zhao, Rui-Jie Zhu

J. Informetrics, August, 2023

OR Residual Connection Achieving Comparable Accuracy to ADD Residual Connection in Deep Residual Spiking Neural Networks.

Yimeng Shan, Xuerui Qiu, Rui-Jie Zhu, Ruike Li, Meng Wang, Haicheng Qu

CoRR, 2023

RWKV: Reinventing RNNs for the Transformer Era.

Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Huanqi Cao, Xin Cheng, Michael Chung, Matteo Grella, Kranthi Kiran G. V., Xuzheng He, Haowen Hou, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Xiangru Tang, Bolun Wang, Johan S. Wind, Stanislaw Wozniak, Ruichong Zhang, Zhenyuan Zhang, Qihang Zhao, Peng Zhou, Jian Zhu, Rui-Jie Zhu

CoRR, 2023

Both Efficiency and Effectiveness! A Large Scale Pre-ranking Framework in Search System.

Qihang Zhao, Rui-Jie Zhu, Liu Yang, Yongming He, Bo Zhou, Luo Cheng

CoRR, 2023

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks.

Rui-Jie Zhu, Qihang Zhao, Jason K. Eshraghian

CoRR, 2023

Uni-Match: A Semantic Unified Model for Query-Product Retrieval.

Zhenyang Zhu, Rui-Jie Zhu, Yunrui Ge, Qihang Zhao

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

When Spiking Neural Networks Meet Temporal Attention Image Decoding and Adaptive Spiking Neuron.

Xuerui Qiu, Zheng Luan, Zhaorui Wang, Rui-Jie Zhu

Proceedings of the First Tiny Papers Track at ICLR 2023, 2023

RWKV: Reinventing RNNs for the Transformer Era.

Bo Peng, Eric Alcaide, Quentin Anthony, Alon Albalak, Samuel Arcadinho, Stella Biderman, Huanqi Cao, Xin Cheng, Michael Chung, Leon Derczynski, Xingjian Du, Matteo Grella, Kranthi Kiran GV, Xuzheng He, Haowen Hou, Przemyslaw Kazienko, Jan Kocon, Jiaming Kong, Bartlomiej Koptyra, Hayden Lau, Jiaju Lin, Krishna Sri Ipsit Mantri, Ferdinand Mom, Atsushi Saito, Guangyu Song, Xiangru Tang, Johan S. Wind, Stanislaw Wozniak, Zhenyuan Zhang, Qinghua Zhou, Jian Zhu, Rui-Jie Zhu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022

TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks.

Rui-Jie Zhu, Qihang Zhao, Tianjing Zhang, Haoyu Deng, Yule Duan, Malu Zhang, Liang-Jian Deng

CoRR, 2022

SIT: A Bionic and Non-Linear Neuron for Spiking Neural Network.

Cheng Jin, Rui-Jie Zhu, Xiao Wu, Liang-Jian Deng

CoRR, 2022