Long-Context Multimodal Understanding No Longer Requires Massive Models: NVIDIA AI Introduces Eagle 2.5, a Generalist Vision-Language Model that Matches GPT-4o on Video Tasks Using Just 8B Parameters

In recent years, vision-language models (VLMs) have advanced significantly in bridging image, video, and textual modalities. Yet, a persistent limitation […]

Google DeepMind Research Releases SigLIP2: A Family of New Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features

Modern vision-language models have transformed how we process visual data, yet they often fall short when it comes to fine-grained […]

NVIDIA AI Releases Eagle2 Series Vision-Language Model: Achieving SOTA Results Across Various Multimodal Benchmarks

Vision-Language Models (VLMs) have significantly expanded AI’s ability to process multimodal information, yet they face persistent challenges. Proprietary models such […]