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 ...

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 ...

Large language models (LLMs) are increasingly capable of complex reasoning through “inference-time scaling,” a set of techniques that allocate more computational resources during inference to generate ...

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 ...

AI reasoning models were supposed to be the industry’s next leap, promising smarter systems able to tackle more complex problems. Now, a string of research is calling that into question. Researchers ...

A new study by Apple has ignited controversy in the AI field by showing how reasoning models undergo 'complete accuracy collapse' when overloaded with complex problems. When you purchase through links ...