In recent years, contrastive language-image models such as CLIP have established themselves as a default choice for learning vision representations, […]
Category: Vision Language Model
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 […]
Transformer Meets Diffusion: How the Transfusion Architecture Empowers GPT-4o’s Creativity
OpenAI’s GPT-4o represents a new milestone in multimodal AI: a single model capable of generating fluent text and high-quality images […]
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 […]
Google DeepMind Releases PaliGemma 2 Mix: New Instruction Vision Language Models Fine-Tuned on a Mix of Vision Language Tasks
Vision‐language models (VLMs) have long promised to bridge the gap between image understanding and natural language processing. Yet, practical challenges […]
IBM AI Releases Granite-Vision-3.1-2B: A Small Vision Language Model with Super Impressive Performance on Various Tasks
The integration of visual and textual data in artificial intelligence presents a complex challenge. Traditional models often struggle to interpret […]
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 […]
Qwen AI Releases Qwen2.5-VL: A Powerful Vision-Language Model for Seamless Computer Interaction
In the evolving landscape of artificial intelligence, integrating vision and language capabilities remains a complex challenge. Traditional models often struggle […]
Qwen Team Releases QvQ: An Open-Weight Model for Multimodal Reasoning
Multimodal reasoning—the ability to process and integrate information from diverse data sources such as text, images, and video—remains a demanding […]
Meta AI Releases Apollo: A New Family of Video-LMMs Large Multimodal Models for Video Understanding
While multimodal models (LMMs) have advanced significantly for text and image tasks, video-based models remain underdeveloped. Videos are inherently complex, […]