| 1 |
Feast Your Eyes: Mixture-of-Resolution Adaptation for Multimodal Large Language Models |
提出混合分辨率适应方法以提升多模态大语言模型的视觉识别能力 |
large language model multimodal |
✅ |
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| 2 |
Finetuned Multimodal Language Models Are High-Quality Image-Text Data Filters |
提出基于微调多模态语言模型的高质量图文数据过滤方法 |
foundation model multimodal |
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| 3 |
MADTP: Multimodal Alignment-Guided Dynamic Token Pruning for Accelerating Vision-Language Transformer |
提出MADTP以解决视觉语言Transformer的动态令牌修剪问题 |
multimodal |
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| 4 |
Multi-modal Instruction Tuned LLMs with Fine-grained Visual Perception |
提出AnyRef以解决多模态细粒度视觉感知问题 |
large language model multimodal |
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| 5 |
ChatGPT and biometrics: an assessment of face recognition, gender detection, and age estimation capabilities |
评估ChatGPT在生物识别中的面部识别、性别检测和年龄估计能力 |
large language model foundation model |
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| 6 |
Interactive Continual Learning: Fast and Slow Thinking |
提出交互式持续学习框架以解决持续学习中的遗忘问题 |
large language model multimodal |
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| 7 |
Modeling Collaborator: Enabling Subjective Vision Classification With Minimal Human Effort via LLM Tool-Use |
提出新框架以减少主观视觉分类中的人工标注工作量 |
large language model foundation model |
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| 8 |
Learning Zero-Shot Material States Segmentation, by Implanting Natural Image Patterns in Synthetic Data |
通过将自然图像模式植入合成数据解决零样本材料状态分割问题 |
foundation model |
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| 9 |
ImgTrojan: Jailbreaking Vision-Language Models with ONE Image |
提出ImgTrojan以解决视觉语言模型的安全性问题 |
large language model |
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| 10 |
Few-shot Learner Parameterization by Diffusion Time-steps |
提出基于扩散时间步的少样本学习者以解决属性提取问题 |
foundation model |
✅ |
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| 11 |
VEglue: Testing Visual Entailment Systems via Object-Aligned Joint Erasing |
提出VEglue以解决视觉蕴含系统测试中的挑战 |
multimodal |
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