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Xueyan Zou

@xyz2maureen • 1,772 subscribers

Assistant Professor @Tsinghua_Uni prev. PostDoc 🤖 @UCSDJacobs; PhD 🎓 @UWMadison; Intern @MSFTResearch @BytedanceTalk

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As an AI researcher, are you interested in tracking trends from CV/NLP/ML to robotics—even Nature/Science. Our paper “Real Deep Research for AI, Robotics & Beyond” automates survey generation and trend/topic discovery across fields 🔥Explore RDR at
1:01
xyz2maureen's profile picture

As an AI researcher, are you interested in tracking trends from CV/NLP/ML to robotics—even Nature/Science. Our paper “Real Deep Research for AI, Robotics & Beyond” automates survey generation and trend/topic discovery across fields 🔥Explore RDR at

Xueyan Zou

43,192 次观看 • 7 个月前

Our Latent Encoder-Decoder code base is fully open sourced, you can train and visualize the latent space: Code⚙️: ArXiv 📚: #CVPR2026
0:25
xyz2maureen's profile picture

Our Latent Encoder-Decoder code base is fully open sourced, you can train and visualize the latent space: Code⚙️: ArXiv 📚: #CVPR2026

Xueyan Zou

18,768 次观看 • 2 个月前

[1/n] We are releasing M3 (#ICLR2025): a Gaussian Splatting method that builds LMM memories for arbitrary scenes. 🔥 [Efficient] 16 degrees in each Gaussian primitive for one LMM. 🔥 [Alignment] The rendered features are directly in the source LMM embedding space.
1:16
xyz2maureen's profile picture

[1/n] We are releasing M3 (#ICLR2025): a Gaussian Splatting method that builds LMM memories for arbitrary scenes. 🔥 [Efficient] 16 degrees in each Gaussian primitive for one LMM. 🔥 [Alignment] The rendered features are directly in the source LMM embedding space.

Xueyan Zou

53,410 次观看 • 1 年前

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