| 1 |
VL-Mamba: Exploring State Space Models for Multimodal Learning |
提出VL-Mamba以解决多模态学习中的计算复杂性问题 |
Mamba state space model large language model |
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| 2 |
DepthFM: Fast Monocular Depth Estimation with Flow Matching |
提出DepthFM以解决单目深度估计中的模糊和采样效率问题 |
flow matching depth estimation monocular depth |
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| 3 |
HyperFusion: A Hypernetwork Approach to Multimodal Integration of Tabular and Medical Imaging Data for Predictive Modeling |
提出HyperFusion以解决多模态医疗数据融合问题 |
predictive model multimodal |
✅ |
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| 4 |
RAR: Retrieving And Ranking Augmented MLLMs for Visual Recognition |
提出RAR方法以提升多模态大语言模型的视觉识别能力 |
contrastive learning large language model multimodal |
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| 5 |
ZigMa: A DiT-style Zigzag Mamba Diffusion Model |
提出Zigzag Mamba以解决扩展性和复杂性问题 |
Mamba multimodal |
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| 6 |
Progressive trajectory matching for medical dataset distillation |
提出渐进轨迹匹配方法以解决医疗数据集蒸馏问题 |
distillation foundation model |
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| 7 |
H-vmunet: High-order Vision Mamba UNet for Medical Image Segmentation |
提出H-vmunet以解决医学图像分割中的信息冗余问题 |
Mamba SSM |
✅ |
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| 8 |
Scale Decoupled Distillation |
提出规模解耦蒸馏方法以提升知识蒸馏性能 |
teacher-student distillation |
✅ |
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| 9 |
DD-RobustBench: An Adversarial Robustness Benchmark for Dataset Distillation |
提出DD-RobustBench以评估数据集蒸馏的对抗鲁棒性 |
distillation |
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| 10 |
Multi-Modal Hallucination Control by Visual Information Grounding |
提出多模态互信息解码方法以降低生成模型的幻觉现象 |
DPO direct preference optimization |
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