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Root node of the web of threads: https://t.co/ifH80GcLpo


We're in a race. It's not USA vs China but humans and AGIs vs ape power centralization. @deepseek_ai stan #1, 2023–Deep Time «C’est la guerre.» ®1


同样的三张参考图,让他画了一个网络协议的示意图,太可爱了! 非常适合用来当文章插图的风格。


Built 8 startups in 12 months • Sold 3/8 startups • Building https://t.co/ns7SH9FiWh, https://t.co/1tAr7flVT2, https://t.co/pL2Vv5UTCK, https://t.co/sYr4JzzOtJ, https://t.co/HvvzdvWg5H, & a secret startup 🤫

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Excited to share our NeurIPS 2025 Spotlight paper “Does Object Binding Naturally Emerge in Large Pretrained Vision Transformers?” ✨
To add to the broader discussion of binding in neural networks, we ask whether and how Vision Transformers perform object binding (the ability to bind an object’s many features together as a coherent whole).💡
📄 Paper: 🧵[1/8]
Excited to share our NeurIPS 2025 Spotlight paper “Does Object Binding Naturally Emerge in Large Pretrained Vision Transformers?” ✨
To add to the broader discussion of binding in neural networks, we ask whether and how Vision Transformers perform object binding (the ability to bind an object’s many features together as a coherent whole).💡
📄 Paper:](/_next/image?url=https%3A%2F%2Fpbs.twimg.com%2Fmedia%2FG7DcpP_XAAAJnTL.jpg&w=3840&q=75)
[2/8] The binding problem has challenged researchers for decades. If solved, it would enable models to reason efficiently and compositionally at the level of entities or concepts. But modern models still fail here: e.g., diffusion models mixing up attributes and generating a “blue cat” even when asked to produce only red cats and blue dogs. 🔴🐈+🔵🐕➡️🔵🐈


Built 8 startups in 12 months • Sold 3/8 startups • Building https://t.co/ns7SH9FiWh, https://t.co/1tAr7flVT2, https://t.co/pL2Vv5UTCK, https://t.co/sYr4JzzOtJ, https://t.co/HvvzdvWg5H, & a secret startup 🤫
