MemRL separates stable reasoning from dynamic memory, giving AI agents continual learning abilities without model fine-tuning ...
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 ...
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 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 ...
Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
Current continual learning methods can utilize labeled data to alleviate catastrophic forgetting effectively. However, ...
Crowdsourcing efficiently delegates tasks to crowd workers for labeling, though their varying expertise can lead to errors. A key task is estimating worker expertise to infer true labels. However, the ...
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 deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
Minister of Labour, Skills and Innovation Joel Chigona has endorsed the National Framework for the Recognition of Prior ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results