Video understanding has long presented unique challenges for AI researchers. Unlike static images, videos involve intricate temporal dynamics and spatial-temporal reasoning, making it difficult for ...

The growth of data in the digital age presents both opportunities and challenges. An immense volume of text, images, audio, and video is generated daily across platforms. Traditional machine learning ...

The rapid advancements in artificial intelligence have opened new possibilities, but the associated costs often limit who can benefit from these technologies. Large-scale models ...

The rapid advancements in artificial intelligence have opened new possibilities, but the associated costs often limit who can benefit from these technologies. Large-scale models ...

Developing effective multi-modal AI systems for real-world applications requires handling diverse tasks such as fine-grained recognition, visual grounding, reasoning, and multi-step problem-solving.

In today’s fast-paced world of software development, artificial intelligence plays a crucial role in simplifying workflows, speeding up coding tasks, and ensuring quality. But despite its promise, ...

Developing Graphical User Interface (GUI) Agents faces two key challenges that hinder their effectiveness. First, existing agents lack robust reasoning capabilities, relying primarily on single-step ...

Large language models (LLMs) have become crucial tools for applications in natural language processing, computational mathematics, and programming. Such models often require large-scale computational ...

Artificial Intelligence (AI) has made significant strides in various fields, including healthcare, finance, and education. However, its adoption is not without challenges. Concerns about ...

The rapid growth of digital platforms has brought image safety into sharp focus. Harmful imagery—ranging from explicit content to depictions of violence—poses significant challenges for content ...

Large language models (LLMs) like GPT-4, PaLM, Bard, and Copilot have made a huge impact in natural language processing (NLP). They can generate text, solve problems, and carry out conversations with ...

GANs are often criticized for being difficult to train, with their architectures relying heavily on empirical tricks. Despite their ability to generate high-quality images in a single forward pass, ...