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 ...

A new study presents a zero-shot learning (ZSL) framework for maize cob phenotyping, enabling the extraction of geometric traits and estimation of yields in both laboratory and field settings without ...

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, ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

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 ...

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 ...

Gas sensing material screening faces challenges due to costly trial-and-error methods and the complexity of multi-parameter ...

A Charles Sturt University study published in Research in Science Education has mapped a three-stage pathway showing how educator planning, play-based action and reflective practice can work together ...

Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...

Accelerate Learning has published a new guide to help K-12 educators implement the Mathematics Framework for California Public Schools. The free guide, " Building the New California Math Classroom ," ...