AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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4,009 papers
Fixed-budget robustness evaluation can select the wrong frozen vision encoder. An encoder that survives a shallow attack may lose most of that robustness when the same evaluation is strengthened. We ask whether the shallow evaluation contains enough information to identify this budget fragility. For each clean-correct...
Results demonstrate that MVM provides a direct single-field parameterization of stochastic reverse dynamics while maintaining competitive generation quality.
MT-ProtBERT consistently outperforms PARROT, an RNN-based IDP-specific model, across all tasks, and demonstrates that combining self-supervised and biochemistry-informed tasks, and multi-scale learning enables robust modeling of unstructured proteins under data scarcity.
Breast core needle biopsy (CNB) is central to breast cancer diagnosis yet remains challenging because limited tissue sampling, lesion heterogeneity, and subtle morphologic overlap can obscure subtype distinctions. We developed CorePath, a breast-specialized multimodal pathology foundation model fine-tuned from PRISM us...
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eX2L demonstrates that functional domain invariance can be enforced by explicitly decoupling label and nuisance attributes at the group level by penalizing the similarity between Grad-CAM activation maps generated by a primary label classifier and those from a concurrently trained confounder classifier.
SSMProbe is introduced, an explicitly inspectable probe that replaces invariant pooling with a Sinkhorn-learned evidence route followed by a diagonal S4 decoder and uses the mathematical transparency of state-space models to turn a frozen ViT readout into an auditable evidence-routing analysis.
Under the evaluated four-image setting, these results indicate that separator-based long-sequence pretraining improves recognition robustness and dense visual prediction relative to ARM.
Experiments demonstrate that the proposed novel framework leveraging Remote Sensing imagery and Multimodal Large Language Models for global context-aware landing site assessment significantly outperforms geometric baselines in risk identification accuracy and qualitative results confirm its ability to generate human-li...
OV-MAP is introduced, a novel approach to open-world 3D mapping for mobile robots by integrating open-features into 3D maps to enhance object recognition capabilities by employing a class-agnostic segmentation model to project 2D masks into 3D space.
Experiments on video temporal grounding and highlight detection benchmarks show that TEMPURA substantially improves strong base VLMs across model families and scales, confirming that combining event-level reasoning with fine-grained temporal segmentation is an effective recipe for video temporal understanding.
EndoCogniAgent is proposed, a closed-loop agentic framework that formulates endoscopic diagnosis as a controlled state update process for integrating complementary visual and textual evidence and introduces EndoAgentBench, a workflow-oriented benchmark to evaluate diagnostic agents across a comprehensive diagnostic cha...
This work presents FleXray, a generalist model for anatomical segmentation across the entire body in clinical X-rays, and builds a scalable, physics-based generative X-ray data engine that makes X-rays directly amenable to quantitative analysis.
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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