The development of humans and other animals unfolds gradually over time, with cells taking on specific roles and functions ...

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...

Microsoft Research has developed a new reinforcement learning framework that trains large language models for complex reasoning tasks at a fraction of the usual computational cost. The framework, ...

(a) An illustrative map for Crack-Net, including the initial features, looping solver for data generation, model training, and prediction performance. (b) The Crack-Net architecture, which utilizes ...

The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

As the use of Unmanned Aerial Vehicles (UAVs) expands across various fields, there is growing interest in leveraging Federated Learning (FL) to enhance the efficiency of UAV networks. However, ...

Physical learning environments (PLEs)—including classrooms, schools, and networks of facilities—play a critical role in shaping educational outcomes. The World Bank’s RIGHT+ framework offers guidance ...

Have you ever found yourself deep in the weeds of training a language model, wishing for a simpler way to make sense of its learning process? If you’ve struggled with the complexity of configuring ...

Businesses play a critical role in building a new, integrated system of learning and work because they see change first. They ...