AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Multimodal language models (MLLMs) exhibit promising spatial reasoning capabilities, yet the internal mechanisms supporting them remain poorly understood. We uncover S-Space, a linear representation subspace in which object-token representations encode continuous coordinates along horizontal, vertical, and distance axe...
This work introduces HarnessEval-W, an agentified evaluation pipeline that brings the harness paradigm from the LLM ecosystem to world model benchmarking, and applies HarnessEval-W to 18 representative world models over 330 evaluation cases.
Experimental results show that Diffusion-SDF is capable of generating both high-quality and highly diversified 3D shapes that conform well to the given text descriptions, and Diffusion-SDF++ further outperforms Diffusion-SDF with more precise shape details due to the adaptive voxelization strategy.
Experiments show that Code-as-World-VL achieves state-of-the-art performance on QuantiPhy and surpasses leading proprietary models, highlighting the potential of executable world representations as a scalable foundation for physical intelligence.
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