AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Category
3,560 papers
This work introduces Generative Translation Priors--a Bayesian framework that transforms diffusion-based image-to-image translation models into cross-modality image priors for ill-posed imaging inverse problems, and derives two discretized GTP algorithms based on gradient and proximal likelihood guidance.
Adversarial Calibration Attack (ACA), the first physical attack against camera-LiDAR online calibration, is presented and demonstrated that online calibration is a practical and safety-critical attack surface for AVs.
Match controls on training recipe as well as capacity, and buy compression robustness with codec diversity before architecture, and buy compression robustness with codec diversity with codec diversity before architecture.
The effectiveness of the proposed source codecs are demonstrated by achieving state-of-the-art performance in distributed semantic segmentation at below 0.2 bits per pixel, measured using the mean intersection-over-union metric on ADE20K (Cityscapes).
Reach audiences
Advertise in front of researchers, engineers, and readers.
This work uses the abundant compute resources of the cloud to run a highly-accurate oracle model that will guide the retraining process of the on-vehicle model, leading to improved inference accuracy over time.
Autonomous vehicles operate in dynamic, ever-changing environments where new scenarios and edge cases constantly emerge. As a result, static learning models are inadequate for ensuring safe and reliable operation. Continuous learning is essential for adapting to these evolving conditions and maintaining robust performa...
TSPFN is introduced, a foundation model that redesigns TabPFN's architecture for time series data and yields a unified, generalizable framework capable of learning the specificities of medical time series.
This work investigates attribution in flow-matching models through a hybrid analytical--learned approach, and uses it to derive trajectory-based attribution scores at the cluster level, which show that semantic similarity constitutes a strong baseline, while the closed-form trajectory-based attribution is competitive i...
It is proved that geometric misalignment forcefully converts spatial textures into high-frequency angular signals via parallax, which establishes a strict identifiability window: if angular capacity is bounded, surface-consistent solutions are mathematically preferred; if unrestricted, the same images can be perfectly...
Geometry finally makes a commanded 3D target a natural goal interface: it is constructed the goal latent from the target and the current latent, at no cost in success rate, without a goal observation.
This paper introduces a sample-wise inverse-temperature update for TTM by locally minimizing the Kullback-Leibler divergence between the temperature-scaled teacher distribution and the student's prediction and derives closed-form first and second derivatives with respect to the inverse temperature.
Extensive experimental evaluation demonstrates that the proposed Context-Aware representations not only provide intrinsic interpretability and dimensionality reduction but also maintain or enhance effectiveness in downstream tasks, specifically in image retrieval and semi-supervised classification using Graph Convoluti...
GPT-Lab
· gpt-lab.eu
Oct 8, 2026
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
A Blog post by H company on Hugging Face
A Blog post by Liquid AI on Hugging Face
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
Human-Computer Interaction and Visualization
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
