Optical Character Recognition (OCR) is a powerful technology that converts images of text into machine-readable content. With the growing need for automation in data extraction, OCR tools have become ...

VLMs have shown notable progress in perception-driven tasks such as visual question answering (VQA) and document-based visual reasoning. However, their effectiveness in reasoning-intensive tasks ...

LLMs are widely used for conversational AI, content generation, and enterprise automation. However, balancing performance with computational efficiency is a key challenge in this field. Many ...

Stereo depth estimation plays a crucial role in computer vision by allowing machines to infer depth from two images. This capability is vital for autonomous driving, robotics, and augmented reality ...

Normalization layers have become fundamental components of modern neural networks, significantly improving optimization by stabilizing gradient flow, reducing sensitivity to weight initialization, and ...

Modern VLMs struggle with tasks requiring complex visual reasoning, where understanding an image alone is insufficient, and deeper interpretation is needed. While recent advancements in LLMs have ...

Like humans, large language models (LLMs) often have differing skills and strengths derived from differences in their architectures and training regimens. However, they struggle to combine specialized ...

In this tutorial, we demonstrate how to build an AI-powered PDF interaction system in Google Colab using Gemini Flash 1.5, PyMuPDF, and the Google Generative AI API. By leveraging these tools, we can ...

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities across various domains, propelling their evolution into multi-modal agents for human assistance. GUI automation ...

Enhancing the reasoning abilities of LLMs by optimizing test-time compute is a critical research challenge. Current approaches primarily rely on fine-tuning models with search traces or RL using ...

Traditional language models rely on autoregressive approaches, which generate text sequentially, ensuring high-quality outputs at the expense of slow inference speeds. In contrast, diffusion models, ...

The rapid evolution of artificial intelligence (AI) has ushered in a new era of large language models (LLMs) capable of understanding and generating human-like text. However, the proprietary nature of ...