@inproceedings{e5b6f743d46a46868aaae81a206a132c,
title = "Automatic Document Editing for Improved Ranking",
abstract = "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.",
keywords = "competitive search, LLM",
author = "Niv Bardas and Tommy Mordo and Oren Kurland and Moshe Tennenholtz",
note = "Publisher Copyright: {\textcopyright} 2025 Copyright held by the owner/author(s).; 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2025 ; Conference date: 13-07-2025 Through 18-07-2025",
year = "2025",
month = jul,
day = "13",
doi = "10.1145/3726302.3730168",
language = "אנגלית",
series = "SIGIR 2025 - Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval",
pages = "2779--2783",
booktitle = "SIGIR 2025 - Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval",
}