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Retrieval-augmented generation (RAG) has proven effective in integrating knowledge into large language models (LLMs).
The hippocampal memory indexing theory
Timothy J Teyler and Pascal DiScenna · 1986
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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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Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor · 2008
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Wikidata: a free collaborative knowledgebase
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Leveraging linguistic structure for open domain information extraction
Gabor Angeli, Melvin Jose Johnson Premkumar, and Christopher D Manning · 2015
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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Scott Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
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Ms marco: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng · 2016
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl · 2017
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Deep learning scaling is predictable, empirically
Joel Hestness, Sharan Narang, Newsha Ardalani, Gregory Diamos, Heewoo Jun, Hassan Kianinejad, Md Mostofa Ali Patwary, Yang Yang, and Yanqi Zhou · 2017
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D Manning · 2018
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Learning dense representations for entity retrieval
Dan Gillick, Sayali Kulkarni, Larry Lansing, Alessandro Presta, Jason Baldridge, Eugene Ie, and Diego Garcia-Olano · 2019
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PubMedQA: A dataset for biomedical research question answering
Qiao Jin, Bhuwan Dhingra, Zhengping Liu, William Cohen, and Xinghua Lu · 2019
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The TechQA dataset
Vittorio Castelli, Rishav Chakravarti, Saswati Dana, Anthony Ferritto, Radu Florian, Martin Franz, Dinesh Garg, Dinesh Khandelwal, Scott McCarley, Michael McCawley, Mohamed Nasr, Lin Pan, Cezar Pendus, John Pitrelli, Saurabh Pujar, Salim Roukos, Andrzej Sakrajda, Avi Sil, Rosario Uceda-Sosa, Todd Ward, and Rong Zhang · 2020
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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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Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei · 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
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and S Yu Philip · 2020
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Question answering over electronic devices: A new benchmark dataset and a multi-task learning based QA framework
Abhilash Nandy, Soumya Sharma, Shubham Maddhashiya, Kapil Sachdeva, Pawan Goyal, and NIloy Ganguly · 2021
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Sentence-transformers all-mpnet-base-v2, 2021
SBERT · 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
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Neural bellman-ford networks: A general graph neural network framework for link prediction
Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, and Jian Tang · 2021
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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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Large dual encoders are generalizable retrievers
Jianmo Ni, Chen Qu, Jing Lu, Zhuyun Dai, Gustavo Hernandez Abrego, Ji Ma, Vincent Zhao, Yi Luan, Keith Hall, Ming-Wei Chang, et al · 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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Musique: Multihop questions via single-hop question composition
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, and Ashish Sabharwal · 2022
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Making a miracl: Multilingual information retrieval across a continuum of languages
Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, Ehsan Kamalloo, David Alfonso-Hermelo, Xiaoguang Li, Qun Liu, Mehdi Rezagholizadeh, and Jimmy Lin · 2022
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A survey on neural open information extraction: Current status and future directions
Shaowen Zhou, Bowen Yu, Aixin Sun, Cheng Long, Jingyang Li, and Jian Sun · 2022
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Regression compatible listwise objectives for calibrated ranking with binary relevance
Aijun Bai, Rolf Jagerman, Zhen Qin, Le Yan, Pratyush Kar, Bing-Rong Lin, Xuanhui Wang, Michael Bendersky, and Marc Najork · 2023
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Bge m3-embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation, 2023
Jianlv Chen, Shitao Xiao, Peitian Zhang, Kun Luo, Defu Lian, and Zheng Liu · 2023
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Scaling vision transformers to 22 billion parameters
Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, et al · 2023
G-retriever: Retrieval-augmented generation for textual graph understanding and question answering
Xiaoxin He, Yijun Tian, Yifei Sun, Nitesh Chawla, Thomas Laurent, Yann LeCun, Xavier Bresson, and Bryan Hooi · 2024
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Adaptive-rag: Learning to adapt retrieval-augmented large language models through question complexity
Soyeong Jeong, Jinheon Baek, Sukmin Cho, Sung Ju Hwang, and Jong C Park · 2024
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Reaper: Reasoning based retrieval planning for complex rag systems
Ashutosh Joshi, Sheikh Muhammad Sarwar, Samarth Varshney, Sreyashi Nag, Shrivats Agrawal, and Juhi Naik · 2024
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Bridging law and data: Augmenting reasoning via a semi-structured dataset with irac methodology
Xiaoxi Kang, Lizhen Qu, Lay-Ki Soon, Zhuang Li, and Adnan Trakic · 2024
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Nv-embed: Improved techniques for training llms as generalist embedding models
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Retrieval-augmented generation for large language models: A survey
Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, and Haofen Wang · 2023
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A theory of link prediction via relational weisfeiler-leman on knowledge graphs
Xingyue Huang, Miguel Romero, Ismail Ceylan, and Pablo Barceló · 2023
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Active retrieval augmented generation
Zhengbao Jiang, Frank F Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, and Graham Neubig · 2023
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Hagrid: A human-llm collaborative dataset for generative information-seeking with attribution
Ehsan Kamalloo, Aref Jafari, Xinyu Zhang, Nandan Thakur, and Jimmy Lin · 2023
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Graph reasoning for question answering with triplet retrieval
Shiyang Li, Yifan Gao, Haoming Jiang, Qingyu Yin, Zheng Li, Xifeng Yan, Chao Zhang, and Bing Yin · 2023
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Expertqa: Expert-curated questions and attributed answers
Chaitanya Malaviya, Subin Lee, Sihao Chen, Elizabeth Sieber, Mark Yatskar, and Dan Roth · 2023
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DelucionQA: Detecting hallucinations in domain-specific question answering
Mobashir Sadat, Zhengyu Zhou, Lukas Lange, Jun Araki, Arsalan Gundroo, Bingqing Wang, Rakesh Menon, Md Parvez, and Zhe Feng · 2023
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Chankyu Lee, Rajarshi Roy, Mengyao Xu, Jonathan Raiman, Mohammad Shoeybi, Bryan Catanzaro, and Wei Ping · 2024
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Kag: Boosting llms in professional domains via knowledge augmented generation
Lei Liang, Mengshu Sun, Zhengke Gui, Zhongshu Zhu, Zhouyu Jiang, Ling Zhong, Yuan Qu, Peilong Zhao, Zhongpu Bo, Jin Yang, et al · 2024
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Understanding the ranking loss for recommendation with sparse user feedback
Zhutian Lin, Junwei Pan, Shangyu Zhang, Ximei Wang, Xi Xiao, Shudong Huang, Lei Xiao, and Jie Jiang · 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
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Position: Graph foundation models are already here
Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, and Jiliang Tang · 2024
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Gnn-rag: Graph neural retrieval for large language model reasoning
Costas Mavromatis and George Karypis · 2024
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Build the future of ai with meta llama 3, 2024
Meta · 2024
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Nv-retriever: Improving text embedding models with effective hard-negative mining
Gabriel de Souza P Moreira, Radek Osmulski, Mengyao Xu, Ronay Ak, Benedikt Schifferer, and Even Oldridge · 2024
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A survey on open information extraction from rule-based model to large language model
Liu Pai, Wenyang Gao, Wenjie Dong, Lin Ai, Ziwei Gong, Songfang Huang, Li Zongsheng, Ehsan Hoque, Julia Hirschberg, and Yue Zhang · 2024
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Holmes: Hyper-relational knowledge graphs for multi-hop question answering using llms
Pranoy Panda, Ankush Agarwal, Chaitanya Devaguptapu, Manohar Kaul, and Prathosh Ap · 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
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Understanding expressivity of gnn in rule learning
Haiquan Qiu, Yongqi Zhang, Yong Li, et al · 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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DRAGIN: Dynamic retrieval augmented generation based on the real-time information needs of large language models
Weihang Su, Yichen Tang, Qingyao Ai, Zhijing Wu, and Yiqun Liu · 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
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GFT: Graph foundation model with transferable tree vocabulary
Zehong Wang, Zheyuan Zhang, Nitesh V Chawla, Chuxu Zhang, and Yanfang Ye · 2024
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Opengraph: Towards open graph foundation models
Lianghao Xia, Ben Kao, and Chao Huang · 2024
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An Yang, Baosong Yang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Zhou, Chengpeng Li, Chengyuan Li, Dayiheng Liu, Fei Huang, Guanting Dong, Haoran Wei, Huan Lin, Jialong Tang, Jialin Wang, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Ma, Jin Xu, Jingren Zhou, Jinze Bai, Jinzheng He, Junyang Lin, Kai Dang, Keming Lu, Keqin Chen, Kexin Yang, Mei Li, Mingfeng Xue, Na Ni, Pei Zhang, Peng Wang, Ru Peng, Rui Men, Ruize Gao, Runji Lin, Shijie Wang, Shuai Bai, Sinan Tan, Tianhang Zhu, Tianhao Li, Tianyu Liu, Wenbin Ge, Xiaodong Deng, Xiaohuan Zhou, Xingzhang Ren, Xinyu Zhang, Xipin Wei, Xuancheng Ren, Yang Fan, Yang Yao, Yichang Zhang, Yu Wan, Yunfei Chu, Yuqiong Liu, Zeyu Cui, Zhenru Zhang, and Zhihao Fan · 2024
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Simple is effective: The roles of graphs and large language models in knowledge-graph-based retrieval-augmented generation
Mufei Li, Siqi Miao, and Pan Li · 2025
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Graph foundation models: Concepts, opportunities and challenges
Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S Yu, et al · 2025
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