Reasoning Expands Factual Recall in Language Models

Google's controlled experiments showed that enabling reasoning improved single-hop factual recall in LLMs by acting as a computational buffer and by generating related facts that help retrieve answers, though hallucinated intermediate facts increased final-answer errors.