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 ...

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 ...

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

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, ...

Structural economic models, while parsimonious and interpretable, often exhibit poor data fit and limited forecasting performance. Machine learning models, by contrast, offer substantial flexibility ...

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 ...

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 ...

Cambodia is not alone in facing capacity limitations in the production and timely release of key official statistics needed for data-driven policy decisions. This paper demonstrates that combining ...

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