By feeding centuries-old nursery rhymes and folklore recordings into their own model, linguists in Louisiana hope to help a ...

Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — and save money.

Agentic workflows are artificial intelligence-powered software systems that chain together multiple models and external tools ...

The Eleventh Conference on Machine Translation (WMT26) has moved into its active evaluation phase, with test data releases and submission windows now opening across several of the conference’s shared ...

Spelling methods that teach nonspeakers to point to letters to spell words are controversial because they require a ...

Virtual reality and artificial intelligence can support nervous students to progress from silence to speaking confidently in foreign language classes ...

Researchers around the world are racing to develop new quantum-based systems for sensing, communication, computing and ...

Schools are often the first stable institution that refugee-background learners encounter, but they can also be a space of challenges, discrimination and exclusion. Predictable routines, ...

AI automation typically requires task-level fixed costs, such as model training or fine-tuning. We develop a quantitative task-based framework in which automation depends jointly on relative marginal ...

Task-Based Language Teaching and Learning (TBLT) is a communicative approach that positions authentic language tasks as the central unit of instruction. Originating from the communicative language ...

In classrooms across the state, children are learning to read from teachers required to use new tools, research and instruction. Known as the “science of reading,” this approach draws upon decades of ...

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...