Solving Inequality Proofs with Large Language Models

Understand

Inequality proving, crucial across diverse scientific and mathematical fields, tests advanced reasoning skills such as discovering tight bounds and strategic theorem application.

• This makes it a distinct, demanding frontier for large language models (LLMs), offering insights beyond general mathematical problem-solving.
• Progress in this area is hampered by existing datasets that are often scarce, synthetic, or rigidly formal.
• We address this by proposing an informal yet verifiable task formulation, recasting inequality proving into two automatically checkable subtasks: bound estimation and relation prediction.