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 ...

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 ...

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

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: ...

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

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

Want to learn English more effectively? This video covers five strategies used by successful language learners around the world. We go through practical techniques like immersion, repetition, and ...

If there’s a legal reckoning to come over the use of intellectual property in training AI, there are also several methods of ...

A Guidelines of Development Learning Enthusiasm for First-Year Student’s Faculty of Information Engineering at Nanning University ...

In A Nutshell A new study found that even the best AI models stumbled on roughly one in four structured coding tasks, raising ...

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.