A marriage of formal methods and LLMs seeks to harness the strengths of both.

Choose appropriate methods or models for a given problem, using information from observation or knowledge of the system being studied. Employ quantitative methods, mathematical models, statistics, and ...

Engineers at the University of California San Diego have developed a new way to train artificial intelligence systems to ...

This course is intended for students who are not ready for or interested in the Pre-calculus/Calculus pathway their senior year but still want to continue developing their mathematical knowledge and ...

Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks.

A team of math and AI researchers at Microsoft Asia has designed and developed a small language model (SLM) that can be used ...

Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning. The ...

Back in 2019, a group of computer scientists performed a now-famous experiment with far-reaching consequences for artificial intelligence research. At the time, machine vision algorithms were becoming ...

AI in finance is shifting from cold maths to reasoning-native models—systems that explain, verify, and build trust in banking and compliance. For years, artificial intelligence in finance has dazzled ...

Nvidia researchers developed dynamic memory sparsification (DMS), a technique that compresses the KV cache in large language models by up to 8x while maintaining reasoning accuracy — and it can be ...