No Answer Needed: Predicting LLM Answer Accuracy from Question-Only Linear Probes

Researchers developed linear probes that can predict whether large language models will answer questions correctly by analyzing neural activations before any answer is generated. The method works across different model sizes and generalizes to out-of-distribution datasets, though it struggles with mathematical reasoning tasks.