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Collections including paper arxiv:2403.00818

StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization

Paper • 2311.14495 • Published Nov 24, 2023 • 1
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Paper • 2401.09417 • Published Jan 17 • 59
SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

Paper • 2401.13560 • Published Jan 24 • 1
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces

Paper • 2402.00789 • Published Feb 1 • 2

StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization

Paper • 2311.14495 • Published Nov 24, 2023 • 1
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Paper • 2401.09417 • Published Jan 17 • 59
SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

Paper • 2401.13560 • Published Jan 24 • 1
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces

Paper • 2402.00789 • Published Feb 1 • 2

OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

Paper • 2402.14658 • Published Feb 22 • 82
DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

Paper • 2403.00818 • Published Feb 26 • 15

State Space Models

Repeat After Me: Transformers are Better than State Space Models at Copying

Paper • 2402.01032 • Published Feb 1 • 22
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks

Paper • 2402.04248 • Published Feb 6 • 30
Linear Transformers with Learnable Kernel Functions are Better In-Context Models

Paper • 2402.10644 • Published Feb 16 • 79
In Search of Needles in a 10M Haystack: Recurrent Memory Finds What LLMs Miss

Paper • 2402.10790 • Published Feb 16 • 41

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Paper • 2401.10774 • Published Jan 19 • 54
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Paper • 2401.06761 • Published Jan 12 • 1
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache

Paper • 2401.02669 • Published Jan 5 • 14
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 51

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 144
Orion-14B: Open-source Multilingual Large Language Models

Paper • 2401.12246 • Published Jan 20 • 12
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 51
MM-LLMs: Recent Advances in MultiModal Large Language Models

Paper • 2401.13601 • Published Jan 24 • 45

Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model

Paper • 2401.09417 • Published Jan 17 • 59
VMamba: Visual State Space Model

Paper • 2401.10166 • Published Jan 18 • 38
SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

Paper • 2401.13560 • Published Jan 24 • 1
Graph-Mamba: Towards Long-Range Graph Sequence Modeling with Selective State Spaces

Paper • 2402.00789 • Published Feb 1 • 2

YAYI 2: Multilingual Open-Source Large Language Models

Paper • 2312.14862 • Published Dec 22, 2023 • 13
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling

Paper • 2312.15166 • Published Dec 23, 2023 • 56
TrustLLM: Trustworthiness in Large Language Models

Paper • 2401.05561 • Published Jan 10 • 65
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 43

Trellis Networks for Sequence Modeling

Paper • 1810.06682 • Published Oct 15, 2018 • 1
Pruning Very Deep Neural Network Channels for Efficient Inference

Paper • 2211.08339 • Published Nov 14, 2022 • 1
LAPP: Layer Adaptive Progressive Pruning for Compressing CNNs from Scratch

Paper • 2309.14157 • Published Sep 25, 2023 • 1
Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Paper • 2312.00752 • Published Dec 1, 2023 • 138

LLM architecture

The Impact of Depth and Width on Transformer Language Model Generalization

Paper • 2310.19956 • Published Oct 30, 2023 • 9
Retentive Network: A Successor to Transformer for Large Language Models

Paper • 2307.08621 • Published Jul 17, 2023 • 170
RWKV: Reinventing RNNs for the Transformer Era

Paper • 2305.13048 • Published May 22, 2023 • 14
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 44

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