Artificial intelligence (AI) has been advancing in developing agents capable of executing complex tasks across digital platforms. These agents, often powered by large language models (LLMs), have the ...

Medical question-answering systems have become a research focus due to their potential to assist clinicians in making accurate diagnoses and treatment decisions. These systems utilize large language ...

Mathematical formula recognition has progressed significantly, driven by deep learning techniques and the Transformer architecture. Traditional OCR methods prove insufficient due to the complex ...

Large language models (LLMs) are widely implemented in sociotechnical systems like healthcare and education. However, these models often encode societal norms from the data used during training, ...

Multiobjective optimization (MOO) is pivotal in machine learning, enabling researchers to balance multiple conflicting objectives in real-world applications. These applications include robotics, fair ...

Cognitive psychology aims to understand how humans process, store, and recall information, with Kahneman’s dual-system theory providing an important framework. This theory distinguishes between System ...

Researchers from Answer.AI released the Byaldi project, which addresses the challenge of making ColPALI—a complex, late-interaction multi-modal model—more accessible for developers and researchers.

Large codebases in Git repositories can be complicated for developers and organizations to manage and comprehend. As repositories grow, it becomes harder to keep track of the overall structure, ...

Predicting At-Risk University Students Using a Machine Learning Algorithm: University education plays a critical role in societal progress, making it essential for students to succeed in their courses ...

In today’s data-driven world, organizations are overwhelmed with large and diverse datasets that require extensive cleaning, transformation, and analysis to extract meaningful insights. Manual ...

Recent advancements in SSL have led to the development of foundation models (FMs) that analyze extensive biomedical data, enhancing health outcomes. Continuous Glucose Monitoring (CGM) offers rich, ...

Machine Learning Models for Predicting Prime Editing Efficiency: The success of prime editing is highly dependent on both the prime editing guide RNA (pegRNA) design and the target locus. To address ...