@inproceedings{03f1fe4f1f98424b927243acf6508036,
title = "Math Word Problem Generation with Memory Retrieval",
abstract = "The task of math word problem generation (MWPG), which generates a math word problem (MWP) given an equation and several topic words, has increasingly attracted researchers{\textquoteright} attention. In this work, we propose a memory retrieval model to better take advantage of the training data. We first record training MWPs into a memory. Later we use the given equation and topic words to retrieve relevant items from the memory. The retrieved results are then used to complement the process of the MWP generation and improve the generation quality. In addition, we also propose a low-resource setting for MWPG, where only a small number of paired MWPs and a large amount of unpaired MWPs are available. Extensive experiments verify the superior performance and effectiveness of our method.",
keywords = "Low-resource, Math word problem generation, Memory retrieval",
author = "Xiaowei Wang and Wei Qin and Zhenzhen Hu and Lei Wang and Yunshi Lan and Richang Hong",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.; 5th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2022 ; Conference date: 04-11-2022 Through 07-11-2022",
year = "2022",
doi = "10.1007/978-3-031-18913-5\_29",
language = "英语",
isbn = "9783031189128",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "372--385",
editor = "Shiqi Yu and Jianguo Zhang and Zhaoxiang Zhang and Tieniu Tan and Yuen, \{Pong C.\} and Yike Guo and Junwei Han and Jianhuang Lai",
booktitle = "Pattern Recognition and Computer Vision - 5th Chinese Conference, PRCV 2022, Proceedings",
address = "德国",
}