AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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GramLoop is introduced, a training-free framework that replays a short transformer window and controls each replay through final-layer cosine-Gram consistency, which improves object detection and semantic segmentation under corruptions, perturbations, and natural shifts.
A training-free looping framework that repeatedly applies selected transformer layers inside each denoising call is introduced, which improves primary and auxiliary quality metrics with competitive quality--efficiency trade-offs across two Scale-RAE model scales.
This training-free method improves the performance of both U-Net-based and Transformer-based diffusion models, including the Stable Diffusion series and FLUX series and adapts self-cross guidance as an effective reward for RL-based post-training and show improved subject diversity with no computational overhead at infe...
OODA-Tool, a typed closed-loop policy designed to mitigate state preservation from action realization, consistently improves task success across model sizes, with larger gains on smaller models and on tasks whose actions depend strongly on information accumulated across turns and prior tool results.
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