Training large-scale AI models such as transformers and language models have become an indispensable yet highly demanding process in AI. With billions of parameters, these models offer groundbreaking ...

Graphical User Interfaces (GUIs) are central to how users engage with software. However, building intelligent agents capable of effectively navigating GUIs has been a persistent challenge. The ...

Breaking down videos into smaller, meaningful parts for vision models remains challenging, particularly for long videos. Vision models rely on these smaller parts, called tokens, to process and ...

Reward functions play a crucial role in reinforcement learning (RL) systems, but their design presents significant challenges in balancing task definition simplicity with optimization effectiveness.

Ensuring the correctness of electronic designs is critical, as hardware flaws are permanent post-production and can compromise software reliability or the safety of cyber-physical systems.

One of the most critical challenges in computational fluid dynamics (CFD) and machine learning (ML) is that high-resolution, 3D datasets specifically designed for automotive aerodynamics are very hard ...

Multimodal reasoning—the ability to process and integrate information from diverse data sources such as text, images, and video—remains a demanding area of research in artificial intelligence (AI).

Semantic segmentation of the glottal area from high-speed videoendoscopic (HSV) sequences presents a critical challenge in laryngeal imaging. The field faces a significant shortage of high-quality, ...

Graphical User Interfaces (GUIs) play a fundamental role in human-computer interaction, providing the medium through which users accomplish tasks across web, desktop, and mobile platforms. Automation ...

Artificial Intelligence (AI) has been making significant advances with an exponentially growing trajectory, incorporating vast amounts of data and building more complex Large Language Models (LLMs).

Agentic AI systems are fundamentally reshaping how tasks are automated, and goals are achieved in various domains. These systems are distinct from conventional AI tools in that they can adaptively ...

Neural machine translation (NMT) is a sophisticated branch of natural language processing that automates text conversion between languages using machine learning models. Over the years, it has become ...