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

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

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 ...

Back in engineering school, I had a professor who used to glory in the misleading assignment. He would ask questions containing elements of dubious relevance to the topic at hand in the hopes that it ...

Large language models (LLMs) can learn complex reasoning tasks without relying on large datasets, according to a new study by researchers at Shanghai Jiao Tong University. Their findings show that ...

As language models (LMs) improve at tasks like image generation, trivia questions, and simple math, you might think that human-like reasoning is around the corner. In reality, they still trail us by a ...

CAMBRIDGE, MA – For all their impressive capabilities, large language models (LLMs) often fall short when given challenging new tasks that require complex reasoning skills. While an accounting firm’s ...

Artificial intelligence may have impressive inferencing powers, but don't count on it to have anything close to human reasoning powers anytime soon. The march to so-called artificial general ...

Despite rapid generation of functional code, LLMs are introducing critical, compounding security flaws, posing serious risks ...

Although chatbots such as ChatGPT, which are powered by large language models (LLMs), have some sense of time, it is conceptualized in a completely different way. As we increasingly interact with them ...