Artificial intelligence has transformed code generation, with large language models (LLMs) for code now integral to software engineering. These models…
Machine Learning
High-performance computing has become crucial for various businesses, including scientific research and Artificial Intelligence (AI), in today’s data-driven society. By…
In the world of information retrieval, one of the most challenging tasks is to create a system that can seamlessly…
This post is co-written with Steven Craig from Hearst. To maintain their competitive edge, organizations are constantly seeking ways to…
The rise of large language models (LLMs) and foundation models (FMs) has revolutionized the field of natural language processing (NLP)…
Video generation has rapidly become a focal point in artificial intelligence research, especially in generating temporally consistent, high-fidelity videos. This…
Generative AI continues to push the boundaries of what’s possible. One area garnering significant attention is the use of generative…
The emergence of generative AI has ushered in a new era of possibilities, enabling the creation of human-like text, images,…
In the rapidly evolving field of artificial intelligence, the focus often lies on large, complex models requiring immense computational resources.…
Automatic differentiation has transformed the development of machine learning models by eliminating complex, application-dependent gradient derivations. This transformation helps to…
The quest to strengthen national security has faced several challenges over the years, especially as the pace of technological advancement…
Current Text-to-Speech (TTS) systems, such as VALL-E and Fastspeech, face persistent challenges related to processing complex linguistic features, managing polyphonic…
Information overload presents significant challenges in extracting insights from documents containing both text and visuals, such as charts, graphs, and…
A fundamental challenge in studying EEG-to-Text models is ensuring that the models learn from EEG inputs and not just memorize…
Understanding the different forms and future directions of Artificial Intelligence (AI) is becoming increasingly important as it evolves. Artificial Narrow…
Tracking dense 3D motion from monocular videos remains challenging, particularly when aiming for pixel-level precision over long sequences. Existing methods…
Neural contextual biasing allows speech recognition models to leverage contextually relevant information, leading to improved transcription accuracy. However, the biasing…
Large language models (LLMs) have become the backbone of many AI systems, contributing significantly to advancements in natural language processing…
Recognition of human motion using time series from mobile and wearable devices is commonly used as key context information for…
Autonomous agents have emerged as a critical focus in machine learning research, especially in reinforcement learning (RL), as researchers work…