Meta’s Llama 3.2 has been developed to redefined how large language models (LLMs) interact with visual data. By introducing a groundbreaking architecture that seamlessly integrates image ...

From super-resolution smartphone cameras to vehicles that can anticipate human movement, computer vision is undergoin ...

Researchers found that vision-language models, widely used to analyze medical images, do not understand negation words like 'no' and 'not.' This could cause them to fail unexpectedly when asked to ...

Thirdly, an introduction on how researchers pre-train VLP models by using different pre-training objectives is given, which are crucial for learning the universal representation of vision-language.

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This not only streamlines the model’s architecture, making it more lightweight than its counterparts, but also helps boost performance on vision-language tasks.

It employs a vision transformer encoder alongside a large language model (LLM). The vision encoder converts images into tokens, which an attention-based extractor then aligns with the LLM.

Deepseek VL-2 is a scalable vision-language model using a mixture of experts (MoE) architecture to optimize performance and resource usage by activating only relevant sub-networks for specific tasks.

Hugging Face Inc. today open-sourced SmolVLM-256M, a new vision language model with the lowest parameter count in its category. The algorithm’s small footprint allows it to run on devices such ...