AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces Dyn-3D, a benchmark using counterfactual 3D rendering to rigorously decouple visual changes from true kinematic properties and proposes the TempoVista framework, featuring the Kinematic-GSPO algorithm.
SIEVE, a structure-aware data selection method for VLA imitation learning that can surpass full-data training while using only 50% of demonstrations and 50% of training steps, suggests that reusable structure, captured through primitives and transitions, is an important signal for efficient VLA imitation learning.
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