AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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3,920 papers
A cross-modal teacher-student framework that lifts commercial radar to full-body, per-frame, metric 3D mesh reconstruction with per-joint uncertainty, plus a multi-stage ground-truth quality pipeline plus systematic information-lever ablations.
MoSPR (Morpho-Spatial Program Regression), a linear framework that couples an adjacency-informed histology representation with a low-rank molecular basis, provides an interpretable link between spatially coherent macrostate regions and their associated molecular programs.
These exploratory offline results characterize ranking, probability quality and interface failures; they establish neither a causal typed-interface benefit nor general superiority, calibration or end-to-end acceleration.
This study introduces SpecRegMatch, a novel SSR method aimed at addressing the computational cost associated with training by leveraging a single model, thus eliminating the need for multiple data samplings.
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Interpreting architecture, engineering, and construction (AEC) drawings is hard for general Multimodal Large Language Models (MLLMs) and vision-language models (VLMs). We introduce K-OPSD, a VLM post-training methodology for improving AEC drawing understanding. Building on On-Policy Self-Distillation (OPSD) with verifi...
A YOLOv8 convolutional neural network was trained to classify full-page website screenshots as phishing or legitimate based on layout, logo placement, color scheme, and login-form structure, rather than on text extracted from the page.
Investigation to Act (P2A) is introduced, an active probing framework for the browser-agent loop that addresses an asymmetric bridge between symbolic DOM hypotheses and screenshot layout by rendering on-demand symbolic DOM structure back into pixels.
This work presents WorldAgent, an agentic framework for verification-guided physical world construction from a single natural-language prompt, without iterative user debugging, and introduces AgenticSimBench, on which WorldAgent achieves the best scores among the evaluated agent-based methods on five of seven metrics.
This work introduces PlanGuard, the first pre-execution detector that evaluates the physical safety of a complete multi-step plan in its current environment, and proposes Strong-Teacher Adaptive Compensation for On-Policy Distillation (STAC-OPD), which provides compact models with adaptive strong-teacher supervision al...
Endpoint coordinate triage is therefore a useful circuit prior, but occlusion recovery requires a separate benchmark, using object-mask endpoint replacement for recovery and clean-input flooring for depth localization.
It is shown that split invariance forces the local mass factor to be linear for any fixed positive attention kernel, provided that factor is nondecreasing.
This work proposes LocalProp, a training procedure that locally updates the weights of a model, where the pre-training is based on I-JEPA, and empirically shows that it reaches good performance at a fraction of GPU peak memory.
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
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.
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