SIT: A Bionic and Non-Linear Neuron for Spiking Neural Network. - Cheng Jin 003; Rui-Jie Zhu 003; Xiao Wu; Liang-Jian Deng (CoRR, 2022)

TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks. - Rui-Jie Zhu 003; Qihang Zhao; Tianjing Zhang; Haoyu Deng; Yule Duan; Malu Zhang; Liang-Jian Deng (CoRR, 2022)

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; et al. (EMNLP (Findings), 2023)

When Spiking Neural Networks Meet Temporal Attention Image Decoding and Adaptive Spiking Neuron. - Xuerui Qiu; Zheng Luan; Zhaorui Wang 005; Rui-Jie Zhu 003 (Tiny Papers @ ICLR, 2023)

Uni-Match: A Semantic Unified Model for Query-Product Retrieval. - Zhenyang Zhu; Rui-Jie Zhu 003; Yunrui Ge; Qihang Zhao (Tiny Papers @ ICLR, 2023)

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks. - Rui-Jie Zhu 003; Qihang Zhao; Jason K. Eshraghian (CoRR, 2023)

Both Efficiency and Effectiveness! A Large Scale Pre-ranking Framework in Search System. - Qihang Zhao; Rui-Jie Zhu 003; Liu Yang; Yongming He; Bo Zhou; Luo Cheng (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; et al. (CoRR, 2023)

OR Residual Connection Achieving Comparable Accuracy to ADD Residual Connection in Deep Residual Spiking Neural Networks. - Yimeng Shan; Xuerui Qiu; Rui-Jie Zhu 003; Ruike Li; Meng Wang; Haicheng Qu (CoRR, 2023)

Towards popularity prediction of information cascades via degree distribution and deep neural networks. - Xiaodong Feng 001; Qihang Zhao; Rui-Jie Zhu 003 (J. Informetrics, 2023)

Gated Attention Coding for Training High-Performance and Efficient Spiking Neural Networks. - Xuerui Qiu; Rui-Jie Zhu 003; Yuhong Chou; Zhaorui Wang 005; Liang-Jian Deng; Guoqi Li (AAAI, 2024)

What do Transformers have to learn from Biological Spiking Neural Networks? - Jason K. Eshraghian; Rui-Jie Zhu 003 (CASES, 2024)

Recent Advances in Scalable Energy-Efficient and Trustworthy Spiking Neural Networks: from Algorithms to Technology. - Souvik Kundu 002; Rui-Jie Zhu 003; Akhilesh Jaiswal 001; Peter A. Beerel (ICASSP, 2024)

Reducing Data Bottlenecks in Distributed, Heterogeneous Neural Networks. - Ruhai Lin; Rui-Jie Zhu 003; Jason K. Eshraghian (MCSoC, 2024)

Autonomous Driving with Spiking Neural Networks. - Ruijie Zhu 003; Ziqing Wang; Leilani Gilpin; Jason Eshraghian (NeurIPS, 2024)

Gated Slot Attention for Efficient Linear-Time Sequence Modeling. - Yu Zhang 092; Songlin Yang; Rui-Jie Zhu 003; Yue Zhang 004; Leyang Cui; Yiqiao Wang 005; Bolun Wang; Freda Shi; Bailin Wang; Wei Bi; Peng Zhou 017; Guohong Fu (NeurIPS, 2024)

MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map. - Yuhong Chou; Man Yao; Kexin Wang; Yuqi Pan; Rui-Jie Zhu 003; Jibin Wu; Yiran Zhong; Yu Qiao; Bo Xu 002; Guoqi Li (NeurIPS, 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 003; Xinhua Cheng; Jiebo Luo 001; Li Yuan 007 (NeurIPS, 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; et al. (CoRR, 2024)

Scalable MatMul-free Language Modeling. - Rui-Jie Zhu 003; Yu Zhang 092; Ethan Sifferman; Tyler Sheaves; Yiqiao Wang 005; Dustin Richmond; Peng Zhou 017; Jason K. Eshraghian (CoRR, 2024)

CopyLens: Dynamically Flagging Copyrighted Sub-Dataset Contributions to LLM Outputs. - Qichao Ma; Rui-Jie Zhu 003; Peiye Liu; Renye Yan; Fahong Zhang 004; Ling Liang; Meng Li; Zhaofei Yu; Zongwei Wang 001; Yimao Cai; Tiejun Huang 003 (CoRR, 2024)

Future-Guided Learning: A Predictive Approach To Enhance Time-Series Forecasting. - Skye Gunasekaran; Assel Kembay; Hugo J. Ladret; Rui-Jie Zhu 003; Laurent Perrinet; Omid Kavehei; Jason Eshraghian (CoRR, 2024)

Tensor decomposition based attention module for spiking neural networks. - Haoyu Deng; Rui-Jie Zhu 003; Xuerui Qiu; Yule Duan; Malu Zhang; Liang-Jian Deng (Knowl. Based Syst., 2024)

SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks. - Rui-Jie Zhu 003; Qihang Zhao; Guoqi Li; Jason Eshraghian (Trans. Mach. Learn. Res., 2024)

Bridging the gap between artificial intelligence and natural intelligence. - Rui-Jie Zhu 003; Skye Gunasekaran; Jason Eshraghian (Nat. Comput. Sci., 2024)

Advancing Spiking Neural Networks Towards Multiscale Spatiotemporal Interaction Learning. - Yimeng Shan; Malu Zhang; Ruijie Zhu 003; Xuerui Qiu; Jason K. Eshraghian; Haicheng Qu (AAAI, 2025)

Quantized Spike-driven Transformer. - Xuerui Qiu; Malu Zhang; Jieyuan Zhang; Wenjie Wei; Honglin Cao; Junsheng Guo; Rui-Jie Zhu 003; Yimeng Shan; Yang Yang 002; Haizhou Li 001 (ICLR, 2025)

Learnable Sparsification of Die-to-Die Communication via Spike-Based Encoding. - Joshua Nardone; Ruijie Zhu 003; Joseph Callenes; Mohammed E. Elbtity; Ramtin Zand; Jason Eshraghian (CoRR, 2025)

ARFlow: Autogressive Flow with Hybrid Linear Attention. - Mude Hui; Rui-Jie Zhu 003; Songlin Yang; Yu Zhang 092; Zirui Wang; Yuyin Zhou; Jason Eshraghian; Cihang Xie (CoRR, 2025)

SDTrack: A Baseline for Event-based Tracking via Spiking Neural Networks. - Yimeng Shan; Zhenbang Ren; Haodi Wu; Wenjie Wei; Rui-Jie Zhu 003; Shuai Wang; Dehao Zhang; Yichen Xiao; Jieyuan Zhang; Kexin Shi; Jingzhinan Wang; Jason K. Eshraghian; et al. (CoRR, 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 009; Jiebin Zhang; Yuanxing Zhang; Zhuo Chen; et al. (CoRR, 2025)

Neuromorphic Principles for Efficient Large Language Models on Intel Loihi 2. - Steven Abreu; Sumit Bam Shrestha; Rui-Jie Zhu 003; Jason Eshraghian (CoRR, 2025)

TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks. - Rui-Jie Zhu 003; Malu Zhang; Qihang Zhao; Haoyu Deng; Yule Duan; Liang-Jian Deng (IEEE Trans. Neural Networks Learn. Syst., 2025)

ZeCO: Zero Communication Overhead Sequence Parallelism for Linear Attention. - Yuhong Chou; Zehao Liu; Rui-Jie Zhu 003; Xinyi Wan; Tianjian Li; Congying Chu; Qian Liu; Jibin Wu; Zejun Ma (CoRR, 2025)

A Survey on Latent Reasoning. - Ruijie Zhu 003; Tianhao Peng; Tianhao Cheng; Xingwei Qu; Jinfa Huang; Dawei Zhu; Hao Wang; Kaiwen Xue; Xuanliang Zhang; Yong Shan; Tianle Cai; Taylor Kergan; et al. (CoRR, 2025)

A Systematic Analysis of Hybrid Linear Attention. - Dustin Wang; Rui-Jie Zhu 003; Steven Abreu; Yong Shan; Taylor Kergan; Yuqi Pan; Yuhong Chou; Zheng Li; Ge Zhang 009; Wenhao Huang 001; Jason Eshraghian (CoRR, 2025)

Scaling Linear Attention with Sparse State Expansion. - Yuqi Pan; Yongqi An; Zheng Li; Yuhong Chou; Rui-Jie Zhu 003; Xiaohui Wang; Mingxuan Wang; Jinqiao Wang; Guoqi Li (CoRR, 2025)

MagicTime: Time-Lapse Video Generation Models as Metamorphic Simulators. - Shenghai Yuan; Jinfa Huang; Yujun Shi; Yongqi Xu; Ruijie Zhu 003; Bin Lin 014; Xinhua Cheng; Li Yuan 007; Jiebo Luo 001 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)