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3,462 papers
Evidence-grounded visual reasoning (EGVOR) is proposed, departing from implicit inference, EGVOR reformulates reasoning as the explicit generation of Evidence Atoms–structured triplets that enforce strict spatial-semantic alignment.
Reasoning enabled Graph-based Personalized Large Language and Vision Assistant ReGraP-LLaVA is proposed, a personalized MLLM that incorporates KGs and CoT QA pairs through soft and/or hard graph prompting to align structured relational knowledge with the model's semantic space.
Experimental results show that CoPath achieves competitive or superior performance compared with general image classifiers, pathology foundation models under linear probing, and pathology specific classification models, while maintaining substantially lower computational complexity.
An adversarially robust zero-shot image classifier that boosts the SOTA robustness by a large margin and is the first purification method in multi-modal latent space and CLIPure-Cos is the first purification method that is not based on generative models, which substantially improves defense efficiency.
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A controlled evaluation framework for interactive visual grounding in large vision-language models (LVLMs) is introduced, varying how much target information is provided upfront and how much must be acquired through dialogue.
This paper provides a self-contained, derivation-oriented account of RGMs, clarifying the theory and separating it from its original implementation context, and makes RGMs more transparent, auditable, and reproducible, providing a foundation for future quantitative evaluation and development on machine-learning benchma...
This paper presents IterCAD, a unified multimodal agent framework for closed-loop, interactive CAD generation and editing, and introduces the IterCAD-Bench evaluation suite, establishing a survivor-bias-free standard that unifies code validity and geometric precision.
A lightweight two-stage framework for real-time video anomaly detection that eliminates the need for optical flow, standalone pose estimators, and density-based scoring modules is proposed.
MR-JEPA is presented, a self-supervised video foundation model for CMR that extends LeJEPA to 3D spatiotemporal inputs through tubelet tokenization, spatiotemporal masking augmentation, and initialization from a 2D CMR foundation model.
Locator-Critic (LOCI) is proposed, a training-free framework that decouples visual search from evidence verification and improves accuracy for both open-weight models like Qwen3-VL and proprietary models like Gemini 2.5 Pro.
A Temporally-Aligned, Missingness-Aware, Interpretable (TAMI) multimodal fusion framework that aligns speech, language, facial, and physiological features within question-answer segments on a shared timeline, encodes modality-level missingness over time, and conditions fusion on question context is proposed.
TRIAGE, Tracer-aware Refinement via Interactive Anatomy-Guided sEgmentation, a 3D STU-Net initialized through masked autoencoding pre-training with an asynchronous masking strategy, aiming to learn transferable anatomical and cross-modal representations before task-specific fine-tuning.
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
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