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Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 138 -
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 59 -
Vivim: a Video Vision Mamba for Medical Video Object Segmentation
Paper • 2401.14168 • Published • 2 -
HiPPO: Recurrent Memory with Optimal Polynomial Projections
Paper • 2008.07669 • Published • 1
Collections
Discover the best community collections!
Collections including paper arxiv:2402.04248
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StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization
Paper • 2311.14495 • Published • 1 -
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 59 -
SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation
Paper • 2401.13560 • Published • 1 -
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces
Paper • 2402.00789 • Published • 2
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Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 59 -
VMamba: Visual State Space Model
Paper • 2401.10166 • Published • 38 -
SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation
Paper • 2401.13560 • Published • 1 -
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces
Paper • 2402.00789 • Published • 2
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Trellis Networks for Sequence Modeling
Paper • 1810.06682 • Published • 1 -
Pruning Very Deep Neural Network Channels for Efficient Inference
Paper • 2211.08339 • Published • 1 -
LAPP: Layer Adaptive Progressive Pruning for Compressing CNNs from Scratch
Paper • 2309.14157 • Published • 1 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 138
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The Impact of Depth and Width on Transformer Language Model Generalization
Paper • 2310.19956 • Published • 9 -
Retentive Network: A Successor to Transformer for Large Language Models
Paper • 2307.08621 • Published • 170 -
RWKV: Reinventing RNNs for the Transformer Era
Paper • 2305.13048 • Published • 15 -
Attention Is All You Need
Paper • 1706.03762 • Published • 50
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Efficient Memory Management for Large Language Model Serving with PagedAttention
Paper • 2309.06180 • Published • 25 -
LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models
Paper • 2308.16137 • Published • 39 -
Scaling Transformer to 1M tokens and beyond with RMT
Paper • 2304.11062 • Published • 2 -
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models
Paper • 2309.14509 • Published • 17
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Ada-Instruct: Adapting Instruction Generators for Complex Reasoning
Paper • 2310.04484 • Published • 5 -
Diversity of Thought Improves Reasoning Abilities of Large Language Models
Paper • 2310.07088 • Published • 5 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 77 -
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
Paper • 2310.13332 • Published • 14
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Dissecting In-Context Learning of Translations in GPTs
Paper • 2310.15987 • Published • 5 -
In-Context Learning Creates Task Vectors
Paper • 2310.15916 • Published • 42 -
ZeroGen: Efficient Zero-shot Learning via Dataset Generation
Paper • 2202.07922 • Published • 1 -
Promptor: A Conversational and Autonomous Prompt Generation Agent for Intelligent Text Entry Techniques
Paper • 2310.08101 • Published • 2
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StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization
Paper • 2311.14495 • Published • 1 -
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 59 -
SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation
Paper • 2401.13560 • Published • 1 -
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces
Paper • 2402.00789 • Published • 2