Can Computation from Earlier Problems Help LLMs Solve New Ones?
The research investigates if computation from previous problems helps LLMs solve new ones. They tested retaining historical context by comparing models that kept earlier problem data against those that didn't. They introduced STAIR, a mechanism that learns to emphasize or suppress historical states during prompt processing, achieving significant accuracy gains on reasoning benchmarks like AIME 2025.