Detecting subliminal learning in language models through readable prompts

An author announcing a new paper describes subliminal learning as language models passing traits—such as a fondness for cats—through seemingly unrelated data, such as numbers. The team says it can proactively detect these effects as readable prompts, using models’ ability to verbalize learned soft prompts.