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Driven by the progress of large-scale pre-training, parameter-efficient transfer learning has gained immense popularity across different subfields of Artificial Intelligence.
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Frozen in time: A joint video and image encoder for end-to-end retrieval
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Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation
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Clip4clip: An empirical study of clip for end to end video clip retrieval and captioning
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Rethinking the role of demonstrations: What makes in-context learning work?
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High-resolution image synthesis with latent diffusion models
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Masked contrastive pre-training for efficient video-text retrieval
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Image as a foreign language: Beit pretraining for all vision and vision-language tasks
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Diffusion-based scene graph to image generation with masked contrastive pre-training
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Diffusion models: A comprehensive survey of methods and applications
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Glipv2: Unifying localization and vision-language understanding
Haotian Zhang, Pengchuan Zhang, Xiaowei Hu, Yen-Chun Chen, Liunian Li, Xiyang Dai, Lijuan Wang, Lu Yuan, Jenq-Neng Hwang, and Jianfeng Gao · 2022
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Learning to prompt for vision-language models
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Valor: Vision-audio-language omni-perception pretraining model and dataset
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Parameter-efficient fine-tuning of large-scale pre-trained language models
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