Emotional framing in prompts is a weak, task-dependent signal that rarely helps across the board, but adaptive emotional selection can provide modest, reliable improvements—especially for socially-grounded reasoning tasks.
This paper investigates whether emotional language in prompts affects how well large language models perform on tasks like math, medical reasoning, and reading comprehension. The researchers found that adding emotional framing to prompts produces only small, inconsistent changes in accuracy—except in socially-grounded tasks where emotional context matters more.