Cookie Consent by Free Privacy Policy Generator ๐Ÿ“Œ How to Keep Foundation Models Up to Date with the Latest Data? Researchers from Apple and CMU Introduce the First Web-Scale Time-Continual (TiC) Benchmark with 12.7B Timestamped Img-Text Pairs for Continual Training of VLMs

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๐Ÿ“š How to Keep Foundation Models Up to Date with the Latest Data? Researchers from Apple and CMU Introduce the First Web-Scale Time-Continual (TiC) Benchmark with 12.7B Timestamped Img-Text Pairs for Continual Training of VLMs


๐Ÿ’ก Newskategorie: AI Nachrichten
๐Ÿ”— Quelle: marktechpost.com

A paradigm change in multimodal learning has occurred thanks to the contributions of large multimodal foundation models like CLIP, Flamingo, and Stable Diffusion, enabling previously unimaginable improvements in image generation and zero-shot generalization. These baseline models are generally trained on big, web-scale, static datasets. Whether or not legacy models, like OpenAIโ€™s CLIP models, which were [โ€ฆ]

The post How to Keep Foundation Models Up to Date with the Latest Data? Researchers from Apple and CMU Introduce the First Web-Scale Time-Continual (TiC) Benchmark with 12.7B Timestamped Img-Text Pairs for Continual Training of VLMs appeared first on MarkTechPost.

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