Researchers are debating whether large reasoning models (LRMs) truly reason or just mimic human-like responses through "wishful mnemonics," a mix of shorthand and suspended disbelief. The actual processes driving LRM performance remain unclear, with some arguing that the models' outputs are more a result of clever training and data manipulation than genuine reasoning.