Browsing: AI News
Graph Neural Network (GNN)–based motion planning has emerged as a promising approach in robotic systems for its efficiency in pathfinding and navigation tasks. This approach leverages…
The rapid evolution in AI demands models that can handle large-scale data and deliver accurate, actionable insights. Researchers in this field aim to create systems capable…
Charts have become indispensable tools for visualizing data in information dissemination, business decision-making, and academic research. As the volume of multimodal data grows, a critical need…
Multimodal large language models (MLLMs) integrate text and visual data processing to enhance how artificial intelligence understands and interacts with the world. This area of research…
Evaluating Multimodal Large Language Models (MLLMs) in text-rich scenarios is crucial, given their increasing versatility. However, current benchmarks mainly assess general visual comprehension, overlooking the nuanced…
In recent times, contrastive learning has become a potent strategy for training models to learn efficient visual representations by aligning image and text embeddings. However, one…
The interdisciplinary domain of vision-language representation seeks innovative methods to develop systems to understand the nuanced interactions between text and images. This area is pivotal as…
In artificial intelligence, a significant focus has been on developing models that simultaneously process and interpret multiple forms of data. These multimodal models are designed to…
Online text recognition models have advanced significantly in recent years due to enhanced model structures and larger datasets. However, mathematical expression (ME) recognition, a more intricate…
Earlier, with the adoption of computer vision, its studies weren’t content to only scan 2D arrays of flat “patterns.” Rather, they sought to understand images as…