@inproceedings{f81a664b99f5417ca112cf43105e61ff,
title = "MURRE: Multi-Hop Table Retrieval with Removal for Open-Domain Text-to-SQL",
abstract = "The open-domain text-to-SQL task aims to retrieve question-relevant tables from massive databases and generate SQL. However, the performance of current methods is constrained by single-hop retrieval, and existing multi-hop retrieval of open-domain question answering is not directly applicable due to the tendency to retrieve tables similar to the retrieved ones but irrelevant to the question. Since the questions in text-to-SQL usually contain all required information, while previous multi-hop retrieval supplements the questions with retrieved documents. Therefore, we propose the multi-hop table retrieval with removal (MURRE), which removes previously retrieved information from the question to guide the retriever towards unretrieved relevant tables. Our experiments on two open-domain text-to-SQL datasets demonstrate an average improvement of 5.7\% over the previous state-of-the-art results.",
author = "Xuanliang Zhang and Dingzirui Wang and Longxu Dou and Qingfu Zhu and Wanxiang Che",
note = "Publisher Copyright: {\textcopyright} 2025 Association for Computational Linguistics.; 31st International Conference on Computational Linguistics, COLING 2025 ; Conference date: 19-01-2025 Through 24-01-2025",
year = "2025",
language = "英语",
series = "Proceedings - International Conference on Computational Linguistics, COLING",
publisher = "Association for Computational Linguistics (ACL)",
pages = "5789--5806",
editor = "Owen Rambow and Leo Wanner and Marianna Apidianaki and Hend Al-Khalifa and \{Di Eugenio\}, Barbara and Steven Schockaert",
booktitle = "Main Conference",
address = "澳大利亚",
}