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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 • 60 -
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
Collections
Discover the best community collections!
Collections including paper arxiv:2402.04248
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Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 139 -
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 60 -
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
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Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 31 -
Scavenging Hyena: Distilling Transformers into Long Convolution Models
Paper • 2401.17574 • Published • 15 -
Scalable Autoregressive Image Generation with Mamba
Paper • 2408.12245 • Published • 26 -
Jamba-1.5: Hybrid Transformer-Mamba Models at Scale
Paper • 2408.12570 • Published • 31
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Graph Mamba: Towards Learning on Graphs with State Space Models
Paper • 2402.08678 • Published • 15 -
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 31 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 53 -
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 60
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Chain-of-Thought Reasoning Without Prompting
Paper • 2402.10200 • Published • 105 -
How to Train Data-Efficient LLMs
Paper • 2402.09668 • Published • 41 -
BitDelta: Your Fine-Tune May Only Be Worth One Bit
Paper • 2402.10193 • Published • 20 -
A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts
Paper • 2402.09727 • Published • 37
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Simple linear attention language models balance the recall-throughput tradeoff
Paper • 2402.18668 • Published • 19 -
Linear Transformers with Learnable Kernel Functions are Better In-Context Models
Paper • 2402.10644 • Published • 80 -
Repeat After Me: Transformers are Better than State Space Models at Copying
Paper • 2402.01032 • Published • 23 -
Zoology: Measuring and Improving Recall in Efficient Language Models
Paper • 2312.04927 • Published • 2
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BiLLM: Pushing the Limit of Post-Training Quantization for LLMs
Paper • 2402.04291 • Published • 49 -
Self-Discover: Large Language Models Self-Compose Reasoning Structures
Paper • 2402.03620 • Published • 115 -
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 31 -
Scaling Laws for Downstream Task Performance of Large Language Models
Paper • 2402.04177 • Published • 18
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Grandmaster-Level Chess Without Search
Paper • 2402.04494 • Published • 68 -
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 31 -
Self-Play Preference Optimization for Language Model Alignment
Paper • 2405.00675 • Published • 27 -
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
Paper • 2404.03715 • Published • 61