When language models guess wrong, they're actually teaching us something unexpected

It's like watching how a student's mistakes reveal *why* they misunderstood the rules, not just *that* they did — by studying where LLM pseudo-labels fail, researchers found a way to make self-training actually work.

This means LLMs adapting to new domains on their own can become more trustworthy by knowing which guesses to be suspicious of.