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Large language models (LLMs) have been used to generate query expansions augmenting original queries for improving information search.
Improving pseudo-relevance feedback in web information retrieval using web page segmentation
Shipeng Yu, Deng Cai, Ji-Rong Wen, and Wei-Ying Ma. 2003 · 2003
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Selecting good expansion terms for pseudo-relevance feedback
Guihong Cao, Jian-Yun Nie, Jianfeng Gao, and Stephen Robertson. 2008 · 2008
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al. 2009 · 2009
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Positional relevance model for pseudo-relevance feedback
Yuanhua Lv and ChengXiang Zhai. 2010 · 2010
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Image-based recommendations on styles and substitutes
Julian McAuley, Christopher Targett, Qinfeng Shi, and Anton Van Den Hengel. 2015 · 2015
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Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering
Ruining He and Julian McAuley. 2016 · 2016
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The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant. 2018 · 2018
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Query expansion techniques for information retrieval: a survey
Hiteshwar Kumar Azad and Akshay Deepak. 2019 · 2019
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Scalable multi-hop relational reasoning for knowledge-aware question answering
Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, Peifeng Wang, Jun Yan, and Xiang Ren. 2020 · 2020
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Open graph benchmark: Datasets for machine learning on graphs
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, and Jure Leskovec. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Microsoft academic graph: When experts are not enough
Kuansan Wang, Zhihong Shen, Chiyuan Huang, Chieh-Han Wu, Yuxiao Dong, and Anshul Kanakia. 2020 · 2020
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BertGCN: Transductive text classification by combining GNN and BERT
Yuxiao Lin, Yuxian Meng, Xiaofei Sun, Qinghong Han, Kun Kuang, Jiwei Li, and Fei Wu. 2021 · 2021
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QA-GNN: Reasoning with language models and knowledge graphs for question answering
Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, and Jure Leskovec. 2021 · 2021
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KQA pro: A dataset with explicit compositional programs for complex question answering over knowledge base
Shulin Cao, Jiaxin Shi, Liangming Pan, Lunyiu Nie, Yutong Xiang, Lei Hou, Juanzi Li, Bin He, and Hanwang Zhang. 2022 · 2022
Cited alongside, same era.
Improving query representations for dense retrieval with pseudo relevance feedback: A reproducibility study
Hang Li, Shengyao Zhuang, Ahmed Mourad, Xueguang Ma, Jimmy Lin, and Guido Zuccon. 2022 · 2022
Cited alongside, same era.
GreaseLM: Graph REASoning enhanced language models
Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D Manning, and Jure Leskovec. 2022 · 2022
Cited alongside, same era.
Building a knowledge graph to enable precision medicine
Payal Chandak, Kexin Huang, and Marinka Zitnik. 2023 · 2023
Cited alongside, same era.
Precise zero-shot dense retrieval without relevance labels
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan. 2023 · 2023
Cited alongside, same era.
G-retriever: Retrieval-augmented generation for textual graph understanding and question answering
Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh V Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, and Bryan Hooi. 2024 · 2024
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Grag: Graph retrieval-augmented generation
Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, and Liang Zhao. 2024 · 2024
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MILL: Mutual verification with large language models for zero-shot query expansion
Pengyue Jia, Yiding Liu, Xiangyu Zhao, Xiaopeng Li, Changying Hao, Shuaiqiang Wang, and Dawei Yin. 2024 · 2024
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Xinke Jiang, Ruizhe Zhang, Yongxin Xu, Rihong Qiu, Yue Fang, Zhiyuan Wang, Jinyi Tang, Hongxin Ding, Xu Chu, Junfeng Zhao, et al. 2024 · 2024
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Corpus-steered query expansion with large language models
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Rolf Jagerman, Honglei Zhuang, Zhen Qin, Xuanhui Wang, and Michael Bendersky. 2023 · 2023
Cited alongside, same era.
Combining graph neural networks and sentence encoders for knowledge-aware recommendations
Giuseppe Spillo, Cataldo Musto, Marco Polignano, Pasquale Lops, Marco de Gemmis, and Giovanni Semeraro. 2023 · 2023
Cited alongside, same era.
Grapeqa: Graph augmentation and pruning to enhance question-answering
Dhaval Taunk, Lakshya Khanna, Siri Venkata Pavan Kumar Kandru, Vasudeva Varma, Charu Sharma, and Makarand Tapaswi. 2023 · 2023
Cited alongside, same era.
Query2doc: Query expansion with large language models
Liang Wang, Nan Yang, and Furu Wei. 2023 · 2023
Cited alongside, same era.
Large language models for information retrieval: A survey
Yutao Zhu, Huaying Yuan, Shuting Wang, Jiongnan Liu, Wenhan Liu, Chenlong Deng, Haonan Chen, Zhicheng Dou, and Ji-Rong Wen. 2023 · 2023
Cited alongside, same era.
Derian Boer, Fabian Koch, and Stefan Kramer. 2024 · 2024
Cited alongside, same era.
Analyze, generate and refine: Query expansion with LLMs for zero-shot open-domain QA
Xinran Chen, Xuanang Chen, Ben He, Tengfei Wen, and Le Sun. 2024 · 2024
Cited alongside, same era.
Yibin Lei, Yu Cao, Tianyi Zhou, Tao Shen, and Andrew Yates. 2024 · 2024
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Reasoning on graphs: Faithful and interpretable large language model reasoning
Linhao Luo, Yuan-Fang Li, Reza Haf, and Shirui Pan. 2024 · 2024
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Unifying large language models and knowledge graphs: A roadmap
Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu. 2024 · 2024
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Lotus: Enabling semantic queries with llms over tables of unstructured and structured data
Liana Patel, Siddharth Jha, Carlos Guestrin, and Matei Zaharia. 2024 · 2024
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Graph retrieval-augmented generation: A survey
Boci Peng, Yun Zhu, Yongchao Liu, Xiaohe Bo, Haizhou Shi, Chuntao Hong, Yan Zhang, and Siliang Tang. 2024 · 2024
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Retrieval-augmented retrieval: Large language models are strong zero-shot retriever
Tao Shen, Guodong Long, Xiubo Geng, Chongyang Tao, Yibin Lei, Tianyi Zhou, Michael Blumenstein, and Daxin Jiang. 2024 · 2024
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Think-on-graph: Deep and responsible reasoning of large language model on knowledge graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang, Saizhuo Wang, Chen Lin, Yeyun Gong, Lionel Ni, Heung-Yeung Shum, and Jian Guo. 2024 · 2024
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Learning to plan for retrieval-augmented large language models from knowledge graphs
Junjie Wang, Mingyang Chen, Binbin Hu, Dan Yang, Ziqi Liu, Yue Shen, Peng Wei, Zhiqiang Zhang, Jinjie Gu, Jun Zhou, et al. 2024 · 2024
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Retrieval-augmented generation with knowledge graphs for customer service question answering
Zhentao Xu, Mark Jerome Cruz, Matthew Guevara, Tie Wang, Manasi Deshpande, Xiaofeng Wang, and Zheng Li. 2024 · 2024
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