Supervised fine-tuning (SFT) is the standard training paradigm for large language models (LLMs) and graphic user interface (GUI) agents. However, SFT demands high-quality labeled datasets, resulting ...

The rapid advancements in search engine technologies integrated with large language models (LLMs) have predominantly favored proprietary solutions such as Google’s GPT-4o Search Preview and Perplexity ...

Monocular depth estimation involves predicting scene depth from a single RGB image—a fundamental task in computer vision with wide-ranging applications, including augmented reality, robotics, and 3D ...

Autoregressive visual generation models have emerged as a groundbreaking approach to image synthesis, drawing inspiration from language model token prediction mechanisms. These innovative models ...

Innovative frameworks that simplify complex interactions with large language models have fundamentally transformed the landscape of generative AI development in Python. PydanticAI emerges as a robust ...

Large Vision-Language Models (LVLMs) have made significant strides in recent years, yet several key limitations persist. One major challenge is aligning these models effectively with human ...

Despite the growing interest in Multi-Agent Systems (MAS), where multiple LLM-based agents collaborate on complex tasks, their performance gains remain limited compared to single-agent frameworks.

Artificial intelligence (AI) has made significant strides in recent years, yet challenges persist in achieving efficient, cost-effective, and high-performance models. Developing large language models ...

Visual generation frameworks follow a two-stage approach: first compressing visual signals into latent representations and then modeling the low-dimensional distributions. However, conventional ...

In this guide, you will learn how to deploy a machine learning model as an API using FastAPI. We will create an API that predicts the species of a penguin based on ...

Artificial intelligence systems designed for physical settings require more than just perceptual abilities—they must also reason about objects, actions, and consequences in dynamic, real-world ...

Autoregressive Transformers have become the leading approach for sequence modeling due to their strong in-context learning and parallelizable training enabled by softmax attention. However, softmax ...