Fashion remains an unpredictable beast: allergic to certainty, resistant to logic, and most alive precisely when it’s busy proving everyone wrong.

Abstract: Automatic dietary assessment based on food images remains a challenge, requiring precise food detection, segmentation, and classification. Vision-Language Models (VLMs) offer new ...

Speculative decoding is a widely adopted technique for accelerating inference in large language models (LLMs), yet its application to vision-language models (VLMs) remains underexplored, with existing ...

A benchmark for evaluating vision-language models in simulated 3D, outdoor, photorealistic environments. Easy for humans, hard for state-of-the-art VLMs / MLLMs. The real world is messy and ...

Vision language models (VLMs) have made impressive strides over the past year, but can they handle real-world enterprise challenges? All signs point to yes, with one caveat: They still need maturing ...

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 ...

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched. Large language model optimization (LLMO), a set of tactics for ...

Alibaba’s Qwen team has launched Qwen3-VL, its most powerful vision-language model series to date. Released on September 23, the flagship is a massive 235-billion-parameter model made freely available ...

Abstract: Amid growing efforts to leverage advances in large language models (LLMs) and vision-language models (VLMs) for robotics, Vision-Language-Action (VLA) models have recently gained significant ...

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 ...