Abstract: The exploration of various vision-language tasks, such as visual captioning, visual question answering, and visual commonsense reasoning, is an important area in artificial intelligence and ...

As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that human-like reasoning is around the corner. In reality, they still trail us by a ...

Surveys are a primary source of data across the sciences, from medicine to economics. I demonstrate that the assumption that logically coherent responses are from humans is now untenable. I show that ...

VITRA is a novel approach for pretraining Vision-Language-Action (VLA) models for robotic manipulation using large-scale, unscripted, real-world videos of human hand activities. Treating human hand as ...

Imagine pointing your phone's camera at the world, asking it to identify the dark green plant leaves, and asking if it's poisonous for dogs. Likewise, you're working on a computer, pull up the AI, and ...

The device could help a million people with a severe form of macular degeneration to be able to see enough to read. By Gina Kolata For the first time, researchers restored some vision to people with a ...

Fine-grained few-shot ship classification under cloud occlusion is vital for maritime safety but remains challenging due to corrupted features and limited data utility. While the advent of large ...

Abstract: The interpretation of multitemporal remote sensing imagery is critical for monitoring Earth’s dynamic processes. However, previous change detection (CD) methods, which produce binary or ...

Large language models (LLMs) very often generate “hallucinations”—confident yet incorrect outputs that appear plausible. Despite improvements in training methods and architectures, hallucinations ...

Introduction: Vision language models (VLMs) combine image analysis capabilities with large language models (LLMs). Because of their multimodal capabilities, VLMs offer a clinical advantage over image ...