Automatic Document Editing for Improved Ranking
Niv Bardas, Tommy Mordo, Oren Kurland, Moshe Tennenholtz · 2025
We present a study of using large language models (LLMs) to modify a document so as to have it highly ranked for a query by an undisclosed ranking function. We present different prompting methods inspired by work on using LLMs to induce ranking. Empirical evaluation attests to the merits of the best performing methods with respect to human modifications and a highly effective feature-based modification method.