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Paper: https://t.co/FlrWYN4O4m Project: https://t.co/SKQEjXumsa Code: https://t.co/rS4piJoNtz: Fusing 2D Material World Knowledge on 3D Geometry
Founder and CEO of https://t.co/5MjtfpwEU3 | Your guide to radiance fields | Host of the podcast @ViewDependent | FTP: 279 | discord: https://t.co/lrl64WGvlD
WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion Contributions: - WorldWarp: A novel framework for long-range novel view extrapolation that generates video chunk-by-chunk using an autoregressive inference pipeline. - Spatio-Temporal Diffusion (ST-Diff): A non-causal diffusion model that leverages bidirectional attention conditioned on forward-warped images as a dense geometric prior. - An online 3D geometric cache mechanism: Uses test-time optimized 3DGS [25] to provide high-fidelity warped priors while preventing the irreversible error propagation of static 3D representations. - State-of-the-art performance on challenging view extrapolation benchmarks, demonstrating significantly improved geometric consistency and image quality over existing methods.
Paper: https://t.co/FlrWYN4O4m Project: https://t.co/SKQEjXumsa Code: https://t.co/rS4piJoNtz: Fusing 2D Material World Knowledge on 3D Geometry
苹果根据欧盟要求在 iOS 26.3 测试版中为其他品牌的耳机带来类似 #AirPods 的贴靠配对体验，只需要贴靠即可检测到并发起一键配对流程。这是欧盟数字市场法案要求的内容，欧盟发文对苹果引入的互操作性变化表示赞赏，同时称赞数字市场法案将为用户和开发者带来新机遇：https://t.co/tej1Q2FEKc
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Was pretty cool visiting an AI chip startup today to learn more about the hardware that the LLM models we build with everyday runs on. :) Thanks for the invite 👋🏻
Photographer & software engineer, prev @Ghost. Loves building w/ Nodejs, React, Rails, Django! DM for collabs. ❤️ @jiwon_baddie
RT @SabatinoMasala: 💡 Laravel dev tip: ->orderBy()->first() is not always cheap! LIMIT 1 changes the MySQL execution plan. Without a match…
~20 yrs in web-dev, now mostly Laravel. My Laravel courses: https://t.co/HRUAJdMRZL My Youtube channel: https://t.co/qPQAkaov2F
Interesting change of strategy by GLM4.7 compared to Kimi K2 Thinking, DeepSeek V3.2 and MiniMax M2.1 Interleaved thinking between tool calls: All these models supported interleaved thinking for tool calls, but they clear thinking from the previous turns as can be seen in the first screenshot below. Preserved thinking in GLM 4.7: Compare to that GLM 4.7 (for coding endpoints alone) preserves reasoning from previous turns, as can be seen in screenshot below (note red blocks) For the other api endpoint, the behaviour is same as before(discard reasoning from previous turns). This is sure to boost some performance, as the model will have past context. As @peakji, advises models need their past thought process to make good decision later. This is anti-context compression, but I guess for coding scenarios may be well worth it. I wish they made it configurable, so we could see impact ourselves.
Artificial Intelligence @amazon, @awscloud Reinforcement Learning, OSS AI, General Purpose Agents, Autonomy All views personal!
