AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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LAW, a closed-loop VLM--WAM framework that unifies language reasoning, action generation, and world modeling through semantic subtask progress, is presented, establishing a new open-source state of the art on RoboTwin.
Flow-based policies provide an expressive framework for continuous robot control, but their iterative ODE integration incurs substantial inference cost. Naively reducing the integration budget can severely degrade control, since policies optimized under full-step execution are not explicitly constrained to remain relia...
Reinforcement learning (RL) for dexterous manipulation must discover finger-object contacts and then control the object precisely; the action noise that serves the first goal can interfere with the second. In trajectory-guided settings such as ViViDex, where RL refine hand-object trajectories from human video, our base...
WorldEcho is introduced, which probes action following over a broader action distribution using visual integrity and SE(3) trajectory alignment, and WorldSync is proposed, which strengthens action following along three complementary axes: distributional coverage, representational grounding, and intervention-effect alig...
This work proposes HDR (Hierarchical Denoising for Visual Reasoning), a unified framework that integrates hierarchical latents into causal video generation for multi-step reasoning and introduces a level-stratified multi-step video reasoning benchmark with out-of-distribution cases.
A unified generative framework that leverages pre-trained Diffusion Transformer priors to achieve high perceptual quality at extremely low bitrates, achieving state-of-the-art perceptual fidelity with rich spatial details and robust temporal consistency.
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