We believe new architectures are necessary for the next generation of AI.
2025
Llamba: Scaling Distilled Recurrent Models for Efficient Language Processing
Aviv Bick, Tobias Katsch, Nimit Sohoni, Arjun Desai, Albert Gu
2024
Based: Simple Linear Attention Language Models Balance the Recall-Throughput Tradeoff
Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina, Silas Alberti, Dylan Zinsley, James Zou, Atri Rudra, Christopher Ré
Zoology: Measuring and Improving Recall in Efficient Language Models
Simran Arora, Sabri Eyuboglu, Aman Timalsina, Isys Johnson, Michael Poli, James Zou, Atri Rudra, Christopher Ré
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Albert Gu*, Tri Dao*
2023
Mamba-3B-SlimPJ: State-space models rivaling the best Transformer architecture
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
2022
How to Train Your HiPPO: State Space Models with Generalized Orthogonal Basis Projections
Albert Gu, Isys Johnson, Aman Timalsina, Atri Rudra, Christopher Ré
S4ND: Modeling Images and Videos as Multidimensional Signals Using State Spaces
Eric Nguyen, Karan Goel, Albert Gu, Gordon W. Downs, Preey Shah, Tri Dao, Stephen A. Baccus, Christopher Ré
It's Raw! Audio Generation with State-Space Models
Karan Goel, Albert Gu, Chris Donahue, Christopher Ré
Efficiently Modeling Long Sequences with Structured State Spaces
Albert Gu, Karan Goel, Christopher Ré
Domino: Discovering Systematic Errors with Cross-Modal Embeddings
Sabri Eyuboglu, Maya Varma, Khaled Saab, Jean-Benoit Delbrouck, Christopher Lee-Messer, Jared Dunnmon, James Zou, Christopher Ré
2021
Model Patching: Closing the Subgroup Performance Gap with Data Augmentation
Karan Goel, Albert Gu, Yixuan Li, Christopher Ré
2020
HiPPO: Recurrent Memory with Optimal Polynomial Projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, Christopher Ré
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