Quanquan Gu

Feb 13, 2024 | arxiv.org | Yihe Deng |Weitong Zhang |Quanquan Gu

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Oct 2, 2023 | arxiv.org | Yihe Deng |Yuanzhi Li |Quanquan Gu

[Submitted on 2 Oct 2023 ( v1 ), last revised 11 Jul 2024 (this version, v2)] Title:Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP View a PDF of the paper titled Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP, by Zixiang Chen and Yihe Deng and Yuanzhi Li and Quanquan Gu View PDF HTML (experimental) Abstract:Multi-modal learning has become increasingly popular due to its ability to leverage information from different data...

Mar 17, 2023 | arxiv.org | Weitong Zhang |Quanquan Gu

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.