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

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

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 ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

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 ...

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

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 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 ...

A context-driven memory model simulates a wide range of characteristics of waking and sleeping hippocampal replay, providing a new account of how and why replay occurs.