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The recently developed retrieval-augmented generation (RAG) technology has enabled the efficient construction of domain-specific applications.
From data to wisdom
Russell L Ackoff · 1989
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Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval
Stephen E. Robertson and Steve Walker · 1994
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Understanding the difference between information management and knowledge management
Jose Claudio Terra and Terezinha Angeloni · 2003
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Conceptnet—a practical commonsense reasoning tool-kit
Hugo Liu and Push Singh · 2004
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The data, information, knowledge, wisdom chain: the metaphorical link
Jonathan Hey · 2004
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Duc 2005: Evaluation of question-focused summarization systems
Hoa Trang Dang · 2006
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Semantics and complexity of sparql
Jorge Pérez, Marcelo Arenas, and Claudio Gutierrez · 2006
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Knowledge retrieval (kr)
Yiyu Yao, Yi Zeng, Ning Zhong, and Xiangji Huang · 2007
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Information extraction
Sunita Sarawagi et al · 2008
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From information to knowledge: harvesting entities and relationships from web sources
Gerhard Weikum and Martin Theobald · 2010
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Knowledge-based systems for development
Priti Srinivas Sajja and Rajendra Akerkar · 2010
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Semantic web for the working ontologist: effective modeling in RDFS and OWL
Dean Allemang and James Hendler · 2011
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Data, information, knowledge, wisdom (dikw): A semiotic theoretical and empirical exploration of the hierarchy and its quality dimension
Sasa Baskarada and Andy Koronios · 2013
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Information extraction: Past, present and future
Jakub Piskorski and Roman Yangarber · 2013
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Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang · 2013
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Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch · 2014
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Knowledge graph refinement: A survey of approaches and evaluation methods
Heiko Paulheim · 2016
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Dialog-to-action: Conversational question answering over a large-scale knowledge base
Daya Guo, Duyu Tang, Nan Duan, Ming Zhou, and Jian Yin · 2018
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A schema-first formalism for labeled property graph databases: Enabling structured data loading and analytics
Chandan Sharma and Roopak Sinha · 2019
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Fine-tuning language models from human preferences
Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving · 2019
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Constructing A multi-hop QA dataset for comprehensive evaluation of reasoning steps
Xanh Ho, Anh-Khoa Duong Nguyen, Saku Sugawara, and Akiko Aizawa · 2020
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A simple yet strong pipeline for hotpotqa
Dirk Groeneveld, Tushar Khot, Mausam, and Ashish Sabharwal · 2020
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Chinese medical question answer matching based on interactive sentence representation learning
Xiongtao Cui and Jungang Han · 2020
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Retrieval-augmented generation for knowledge-intensive NLP tasks
Patrick S. H. Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela · 2020
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Aser: A large-scale eventuality knowledge graph
Hongming Zhang, Xin Liu, Haojie Pan, Yangqiu Song, and Cane Wing-Ki Leung · 2020
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Discos: Bridging the gap between discourse knowledge and commonsense knowledge
Tianqing Fang, Hongming Zhang, Weiqi Wang, Yangqiu Song, and Bin He · 2021
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Beyond i.i.d.: Three levels of generalization for question answering on knowledge bases
Yu Gu, Sue Kase, Michelle Vanni, Brian Sadler, Percy Liang, Xifeng Yan, and Yu Su · 2021
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Conversational question answering over knowledge graphs with transformer and graph attention networks
Endri Kacupaj, Joan Plepi, Kuldeep Singh, Harsh Thakkar, Jens Lehmann, and Maria Maleshkova · 2021
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Modeling transitions of focal entities for conversational knowledge base question answering
Yunshi Lan and Jing Jiang · 2021
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Leveraging abstract meaning representation for knowledge base question answering
Pavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, Salim Roukos, Alexander G. Gray, Ramón Fernandez Astudillo, Maria Chang, et al · 2021
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Evaluating the knowledge base completion potential of GPT
Blerta Veseli, Simon Razniewski, Jan-Christoph Kalo, and Gerhard Weikum · 2023
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Chatrule: Mining logical rules with large language models for knowledge graph reasoning
Linhao Luo, Jiaxin Ju, Bo Xiong, Yuan-Fang Li, Gholamreza Haffari, and Shirui Pan · 2023
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Complex logical reasoning over knowledge graphs using large language models
Nurendra Choudhary and Chandan K. Reddy · 2023
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Benchmarking large language models in retrieval-augmented generation
Jiawei Chen, Hongyu Lin, Xianpei Han, and Le Sun · 2024
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A survey on rag meeting llms: Towards retrieval-augmented large language models
Wenqi Fan, Yujuan Ding, Liangbo Ning, Shijie Wang, Hengyun Li, Dawei Yin, Tat-Seng Chua, and Qing Li · 2024
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Case-based reasoning for natural language queries over knowledge bases
Rajarshi Das, Manzil Zaheer, Dung Thai, Ameya Godbole, Ethan Perez, Jay Yoon Lee, Lizhen Tan, Lazaros Polymenakos, and Andrew McCallum · 2021
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Knowledge base question answering: A semantic parsing perspective, 2022
Yu Gu, Vardaan Pahuja, Gong Cheng, and Yu Su · 2022
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Musique: Multihop questions via single-hop question composition
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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Overview of BioASQ 2022: The tenth BioASQ challenge on large-scale biomedical semantic indexing and question answering
Anastasios Nentidis, Georgios Katsimpras, Eirini Vandorou, Anastasia Krithara, Antonio Miranda-Escalada, Luis Gasco, Martin Krallinger, and Georgios Paliouras · 2022
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Colbertv2: Effective and efficient retrieval via lightweight late interaction
Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, and Matei Zaharia · 2022
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Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave · 2022
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From local to global: A graph rag approach to query-focused summarization, 2024
Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, and Jonathan Larson · 2024
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Dawei Li, Shu Yang, Zhen Tan, Jae Young Baik, Sunkwon Yun, Joseph Lee, Aaron Chacko, Bojian Hou, Duy Duong-Tran, Ying Ding, et al · 2024
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Shengjie Ma, Chengjin Xu, Xuhui Jiang, Muzhi Li, Huaren Qu, and Jian Guo · 2024
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Grag: Graph retrieval-augmented generation, 2024
Yuntong Hu, Zhihan Lei, Zheng Zhang, Bo Pan, Chen Ling, and Liang Zhao · 2024
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Gnn-rag: Graph neural retrieval for large language model reasoning, 2024
Costas Mavromatis and George Karypis · 2024
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Hipporag: Neurobiologically inspired long-term memory for large language models
Bernal Jiménez Gutiérrez, Yiheng Shu, Yu Gu, Michihiro Yasunaga, and Yu Su · 2024
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Integrating multi-head convolutional encoders with cross-attention for improved sparql query translation, 2024
Yi-Hui Chen, Eric Jui-Lin Lu, and Kwan-Ho Cheng · 2024
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How easily do irrelevant inputs skew the responses of large language models?
Siye Wu, Jian Xie, Jiangjie Chen, Tinghui Zhu, Kai Zhang, and Yanghua Xiao · 2024
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Iepile: Unearthing large-scale schema-based information extraction corpus
Honghao Gui, Hongbin Ye, Lin Yuan, Ningyu Zhang, Mengshu Sun, Lei Liang, and Huajun Chen · 2024
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Retrieve, summarize, plan: Advancing multi-hop question answering with an iterative approach
Zhouyu Jiang, Mengshu Sun, Lei Liang, and Zhiqiang Zhang · 2024
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Efficient knowledge infusion via KG-LLM alignment
Zhouyu Jiang, Ling Zhong, Mengshu Sun, Jun Xu, Rui Sun, Hui Cai, Shuhan Luo, and Zhiqiang Zhang · 2024
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Onegen: Efficient one-pass unified generation and retrieval for llms, 2024
Jintian Zhang, Cheng Peng, Mengshu Sun, Xiang Chen, Lei Liang, Zhiqiang Zhang, Jun Zhou, Huajun Chen, and Ningyu Zhang · 2024
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RAPTOR: recursive abstractive processing for tree-organized retrieval
Parth Sarthi, Salman Abdullah, Aditi Tuli, Shubh Khanna, Anna Goldie, and Christopher D. Manning · 2024
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From local to global: A graph rag approach to query-focused summarization
Darren Edge, Ha Trinh, Newman Cheng, Joshua Bradley, Alex Chao, Apurva Mody, Steven Truitt, and Jonathan Larson · 2024
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Bhaskarjit Sarmah, Benika Hall, Rohan Rao, Sunil Patel, Stefano Pasquali, and Dhagash Mehta · 2024
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Codekgc: Code language model for generative knowledge graph construction
Zhen Bi, Jing Chen, Yinuo Jiang, Feiyu Xiong, Wei Guo, Huajun Chen, and Ningyu Zhang · 2024
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Chatkbqa: A generate-then-retrieve framework for knowledge base question answering with fine-tuned large language models
Haoran Luo, Haihong E, Zichen Tang, Shiyao Peng, Yikai Guo, Wentai Zhang, Chenghao Ma, Guanting Dong, Meina Song, Wei Lin, Yifan Zhu, and Luu Anh Tuan · 2024
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Making large language models perform better in knowledge graph completion
Yichi Zhang, Zhuo Chen, Wen Zhang, and Huajun Chen · 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, Jeff Z. Pan, Wen Zhang, and Huajun Chen · 2024
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Knowledge graph enhanced large language model editing
Mengqi Zhang, Xiaotian Ye, Qiang Liu, Pengjie Ren, Shu Wu, and Zhumin Chen · 2024
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