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3,462 papers
LUCAID is an agentic AI system for precision lung cancer pathology that combines diagnostic reasoning with nine modules that cover the full routine workflow, from quality control, tumor detection and segmentation, histological subtyping, tumor microenvironment profiling, tumor cellularity quantification, and predictive...
The core design principle of DELE-w0.5 is to model how the physical world changes under robot actions, rather than how its visual appearance evolves frame by frame, which enables cheaper training and low-latency inference.
A scheme to train a better transformation for a given image dataset is developed, using isometric tensor networks, inspired by quantum many-body theory, to parameterize the basis, and train it with Riemannian optimization.
The results show that RegionFM maintains performance comparable to less interpretable fine-tuning approaches while providing anatomically grounded explanations, and better aligns model explanations with anatomy-based clinical reasoning while maintaining competitive predictive performance.
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A central lesson is to validate uncertainty in the region, and against the error target, for which it will be used, to validate uncertainty in the region, and against the error target, for which it will be used.
FracEvent, an event simulator that models this pixel-level lifecycle with fractional-relaxation voltage dynamics, improves the temporal structure of generated events and achieves stronger downstream-transfer results than competing simulator baselines, showing its practical value for event-camera simulation.
DASH is introduced, which supervises the conditional and unconditional branches independently and an anchor term regularises the conditional prediction toward ground-truth noise, and the teacher's final learned per-timestep curriculum transfers into the student as a frozen prior.
Focusing on the autonomous driving safety-critical case of pedestrian detection in the dark, it is shown how synthetic low-light samples can be used to better characterize the performance of a state-of-the-art object detection model as a function of the scene illumination.
This work proposes a VQA-based fine-tuning strategy that trains models to answer structured questions about visual content rather than relying solely on captions or simple instructions, which encourages deeper visual grounding and reasoning.
NanoVDR exploits query--document asymmetry by decoupling the two encoding paths: a frozen 2B VLM teacher indexes documents offline, while a distilled text-only student as small as 69M parameters encodes queries at inference, and the resulting NanoVDR-S-Multi (DistilBERT, 69M) retains 95.1% of teacher quality.
This work proposes DesignAsCode, a novel framework that reimagines graphic design as a programmatic synthesis task using HTML/CSS, incorporating a Plan-Implement-Reflect pipeline, incorporating a Semantic Planner to construct dynamic, variable-depth element hierarchies and a Visual-Aware Reflection mechanism that optim...
The results suggest that explicitly regulating representation geometry is an effective complement to optimization balancing, and provide evidence that geometry-aware regularization can improve multimodal learning across diverse architectures and domains.
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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