Large reasoning models often show counterintuitive behavior, putting more computational effort into simple tasks than difficult ones while producing worse results overall. Researchers have established ...

It’s been almost a year since DeepSeek made a major AI splash. In January, the Chinese company reported that one of its large language models rivaled an OpenAI counterpart on math and coding ...

In this tutorial, we build an advanced meta-cognitive control agent that learns how to regulate its own depth of thinking. We treat reasoning as a spectrum, ranging from fast heuristics to deep ...

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

When engineers build AI language models like GPT-5 from training data, at least two major processing features emerge: memorization (reciting exact text they’ve seen before, like famous quotes or ...

Recently, Artificial Intelligence (AI) has reached a historic milestone in one of the world’s toughest math contests, the International Mathematical Olympiad (IMO). Google DeepMind’s Gemini Deep Think ...

This paper introduces RegexPSPACE, a new benchmark of PSPACE-complete regex problems, to show that even state-of-the-art LLMs struggle with tasks requiring complex reasoning, thus revealing their ...

Long-running LLM agents equipped with strong reasoning, planning, and execution skills have the potential to transform scientific discovery with high-impact advancements, such as developing new ...

Recent research indicates that LLMs, particularly smaller ones, frequently struggle with robust reasoning. They tend to perform well on familiar questions but falter when those same problems are ...

AI reasoning models were supposed to be the industry's next leap, promising smarter systems able to tackle more complex problems and a path to superintelligence. The latest releases from the major ...