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 ...

Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach focuses ...

Students may associate history class with memorizing dates, but they should be learning the skills of evidence collection and ...

MIT researchers have developed a generative artificial intelligence-driven approach for planning long-term visual tasks, like robot navigation, that ...

After the students leave, I print the task cards, place one inside each egg, and hide them around the room. On the day of the hunt, students work in small groups and are assigned a specific egg ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025 ...

Real-world AI for robots is hard and expensive to create. Or is it? Researchers at a UK university just showed us how to teach robots like humans ...

I remember the first time I attended a linguistics lecture as an undergraduate in Argentina. The lecturer asked a simple question: where does language come from? My instinctive answer was: books.

Hu, D. (2026) Transformer-Based Automatic Item Generation for Course-Based Test Items: A Case Study of Translation Tasks in China’s Context. Open Journal of Modern Linguistics, 16, 115-128. doi: ...

Nvidia's KV Cache Transform Coding (KVTC) compresses LLM key-value cache by 20x without model changes, cutting GPU memory costs and time-to-first-token by up to 8x for multi-turn AI applications.

Functional connectivity reveals brain attractors that match predictions of free‑energy‑minimizing attractor theory, yielding an interpretable generative model of brain dynamics in rest, task, and ...