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Mamba

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/flj19951219/mamba_dose

공식 코드

MD-Dose: A diffusion model based on the Mamba for radiation dose prediction

https://github.com/frank-oy/hrefnet

공식 코드

A Novel Hybrid Approach for Retinal Vessel Segmentation with Dynamic Long-Range Dependency and Multi-Scale Retinal Edge Fusion Enhancement

https://github.com/freedomintelligence/longllava

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LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture

https://github.com/freedompuppy77/charon

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Mamba-VA: A Mamba-based Approach for Continuous Emotion Recognition in Valence-Arousal Space

https://github.com/fudan-zvg/demo

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DeMo: Decoupling Motion Forecasting into Directional Intentions and Dynamic States

https://github.com/furiocolombo/mamba-foley

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MambaFoley: Foley Sound Generation using Selective State-Space Models

https://github.com/furiosa-ai/ssm-peft

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Parameter-Efficient Fine-Tuning of State Space Models

https://github.com/gatech-eic/longmamba

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LongMamba: Enhancing Mamba's Long Context Capabilities via Training-Free Receptive Field Enlargement

https://github.com/ge-xing/segmamba

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SegMamba: Long-range Sequential Modeling Mamba For 3D Medical Image Segmentation

https://github.com/gengzichen/ARDHOI

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Auto-Regressive Diffusion for Generating 3D Human-Object Interactions

https://github.com/gimpong/AAAI25-S5VH

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Efficient Self-Supervised Video Hashing with Selective State Spaces

https://github.com/gndlwch2w/msvm-unet

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MSVM-UNet: Multi-Scale Vision Mamba UNet for Medical Image Segmentation

https://github.com/goombalab/hydra

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Hydra: Bidirectional State Space Models Through Generalized Matrix Mixers

https://github.com/gpantaz/vl_mamba

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Shaking Up VLMs: Comparing Transformers and Structured State Space Models for Vision & Language Modeling

https://github.com/graphmamba/gmn

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Graph Mamba: Towards Learning on Graphs with State Space Models

https://github.com/gregorbachmann/next-token-failures

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The pitfalls of next-token prediction

https://github.com/guanguanboy/Semi-LLIE

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Semi-LLIE: Semi-supervised Contrastive Learning with Mamba-based Low-light Image Enhancement

https://github.com/guanxiongsun/vfe.pytorch

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MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection

https://github.com/guo-stone/mambamorph

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MambaMorph: a Mamba-based Framework for Medical MR-CT Deformable Registration

https://github.com/guoruilu/slimseiz

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SlimSeiz: Efficient Channel-Adaptive Seizure Prediction Using a Mamba-Enhanced Network

https://github.com/gwenzhang/voxel-mamba

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Voxel Mamba: Group-Free State Space Models for Point Cloud based 3D Object Detection

https://github.com/gxnu-zhonglab/mambalct

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MambaLCT: Boosting Tracking via Long-term Context State Space Model

https://github.com/gxnu-zhonglab/temtrack

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Robust Tracking via Mamba-based Context-aware Token Learning

https://github.com/h-zhao1997/cobra

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Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference

https://github.com/hackerhyper/tmcn

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Trusted Mamba Contrastive Network for Multi-View Clustering

https://github.com/hao1635/langmamba

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LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models

https://github.com/haoxuanli-thu/hcma-unet

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HCMA-UNet: A Hybrid CNN-Mamba UNet with Axial Self-Attention for Efficient Breast Cancer Segmentation

https://github.com/happinesslz/LION

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LION: Linear Group RNN for 3D Object Detection in Point Clouds

https://github.com/harboryuan/ovsam

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Mamba or RWKV: Exploring High-Quality and High-Efficiency Segment Anything Model

https://github.com/harlanhong/actalker

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Audio-visual Controlled Video Diffusion with Masked Selective State Spaces Modeling for Natural Talking Head Generation

https://github.com/hashmatshadab/robustness-of-volumetric-medical-segmentation-models

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On Evaluating Adversarial Robustness of Volumetric Medical Segmentation Models

https://github.com/hazyresearch/based

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Simple linear attention language models balance the recall-throughput tradeoff

https://github.com/hazyresearch/zoology

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Simple linear attention language models balance the recall-throughput tradeoff

https://github.com/hcplab-sysu/dart

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DART: Differentiable Dynamic Adaptive Region Tokenizer for Vision Transformer and Mamba

https://github.com/hdy6438/spec2volcamu-net

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Spec2VolCAMU-Net: A Spectrogram-to-Volume Model for EEG-to-fMRI Reconstruction based on Multi-directional Time-Frequency Convolutional Attention Encoder and Vision-Mamba U-Net

https://github.com/hornhehhf/llm-ell

공식 코드

A Law of Next-Token Prediction in Large Language Models

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