AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Results show no reliable advantage from training-time geometric alignment under this recipe and illustrate the gap between coordinate invariance and physical-layout generalization.
GeoAnchor decomposes 3D spatial information into three complementary components: position latents for object grounding, direction latents for relational orientation, and geometry latents for scene structure, and is introduced a collaborative training strategy that guides the model from local spatial perception to compr...
This work introduces Spatially-Grounded Thought Tokenization to explicitly align special tokens with spatial locations for clear spatial correspondence and visual interpretability, and proposes Mixture-of-Thought-Tokens, a new free-form multimodal grounding method that bridges the perception-reasoning gap.
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