Gu, Albert

Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Gu, A., & Dao, T. (2023) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 1,579

Efficiently Modeling Long Sequences with Structured State Spaces

Gu, A., Goel, K., & Ré, C. (2021) · arXiv

Topic ModelingAdvanced Neural Network Applications

Cited by 805

Resurrecting Recurrent Neural Networks for Long Sequences

Orvieto, A., Smith, S. L., Gu, A., Fernando, A., Gulcehre, C., Pascanu, R., & De, S. (2023) · arXiv

Neural Networks and ApplicationsTopic Modeling

Cited by 76

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Dao, T., & Gu, A. (2024) · arXiv

Network Security and Intrusion DetectionNetwork Packet Processing and Optimization

Cited by 76

Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations

Dao, T., Gu, A., Eichhorn, M., Rudra, A., & Ré, C. (2019) · arXiv

Advanced Neural Network ApplicationsNeural Networks and Applications

Cited by 43

Kaleidoscope: An Efficient, Learnable Representation For All Structured Linear Maps

Dao, T., Sohoni, N. S., Gu, A., Eichhorn, M., Blonder, A., Leszczynski, M., Rudra, A., & Ré, C. (2020) · arXiv

Advanced Neural Network ApplicationsNeural Networks and Applications

Cited by 21

An Empirical Study of Mamba-based Language Models

Waleffe, R., Byeon, W., Riach, D., Norick, B., Korthikanti, V., Dao, T., Gu, A., Hatamizadeh, A., Singh, S., Narayanan, D., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

De, S., Smith, S. L., Fernando, A., Botev, A., Cristian-Muraru, G., Gu, A., Haroun, R., Berrada, L., Chen, Y., Srinivasan, S., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 8

Mamba-3: Improved Sequence Modeling using State Space Principles

Lahoti, A., Li, K. Y., Chen, B., Wang, C., Bick, A., Kolter, J. Z., Dao, T., & Gu, A. (2026) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1