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 ...
The agent acquires a vocabulary of neuro-symbolic concepts for objects, relations, and actions, represented through a ...
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 ...
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 ...
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 ...
Designing effective instruction starts with clarity about what you want students to learn and choosing the right methods to help them get there. The Seven Ways of Learning framework provides a ...
Researchers have developed a novel framework, termed PDJA (Perception–Decision Joint Attack), that leverages artificial ...
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