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Retrieval augmented generation has emerged as an effective method to enhance large language model performance.
Term-weighting approaches in automatic text retrieval
Gerard Salton and Christopher Buckley · 1988
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Predicting clicks: estimating the click-through rate for new ads
Matthew Richardson, Ewa Dominowska, and Robert Ragno · 2007
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al · 2009
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Beyond clicks: dwell time for personalization
Xing Yi, Liangjie Hong, Erheng Zhong, Nanthan Nan Liu, and Suju Rajan · 2014
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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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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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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al · 2021
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Internet-augmented dialogue generation
Mojtaba Komeili, Kurt Shuster, and Jason Weston · 2022
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Internet-augmented language models through few-shot prompting for open-domain question answering
Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, and Nikolai Grigorev · 2022
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Lider: an efficient high-dimensional learned index for large-scale dense passage retrieval
Yifan Wang, Haodi Ma, and Daisy Zhe Wang · 2022
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Plin: A persistent learned index for non-volatile memory with high performance and instant recovery
Zhou Zhang, Zhaole Chu, Peiquan Jin, Yongping Luo, Xike Xie, Shouhong Wan, Yun Luo, Xufei Wu, Peng Zou, Chunyang Zheng, et al · 2022
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Treeline: an update-in-place key-value store for modern storage
Geoffrey X Yu, Markos Markakis, Andreas Kipf, Per-Åke Larson, Umar Farooq Minhas, and Tim Kraska · 2022
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Pantheon: Private retrieval from public key-value store
Ishtiyaque Ahmad, Divyakant Agrawal, Amr El Abbadi, and Trinabh Gupta · 2022
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The web can be your oyster for improving large language models
Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jingyuan Wang, Jian-Yun Nie, and Ji-Rong Wen · 2023
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Dotori: A key-value ssd based kv store
Carl Duffy, Jaehoon Shim, Sang-Hoon Kim, and Jin-Soo Kim · 2023
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Sparkly: A simple yet surprisingly strong tf/idf blocker for entity matching
Derek Paulsen, Yash Govind, and AnHai Doan · 2023
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Towards efficient index construction and approximate nearest neighbor search in high-dimensional spaces
Xi Zhao, Yao Tian, Kai Huang, Bolong Zheng, and Xiaofang Zhou · 2023
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Learned index: A comprehensive experimental evaluation
Zhaoyan Sun, Xuanhe Zhou, and Guoliang Li · 2023
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Dili: A distribution-driven learned index
Pengfei Li, Hua Lu, Rong Zhu, Bolin Ding, Long Yang, and Gang Pan · 2023
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Pre-trained embeddings for entity resolution: an experimental analysis
Alexandros Zeakis, George Papadakis, Dimitrios Skoutas, and Manolis Koubarakis · 2023
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Adaptive indexing in high-dimensional metric spaces
Konstantinos Lampropoulos, Fatemeh Zardbani, Nikos Mamoulis, and Panagiotis Karras · 2023
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Bonsaikv: Towards fast, scalable, and persistent key-value stores with tiered, heterogeneous memory system
Miao Cai, Junru Shen, Yifan Yuan, Zhihao Qu, and Baoliu Ye · 2023
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Experimental analysis of large-scale learnable vector storage compression
Hailin Zhang, Penghao Zhao, Xupeng Miao, Yingxia Shao, Zirui Liu, Tong Yang, and Bin Cui · 2023
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Mirrorkv: An efficient key-value store on hybrid cloud storage with balanced performance of compaction and querying
Zhiqi Wang and Zili Shao · 2023
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Learning to optimize lsm-trees: Towards a reinforcement learning based key-value store for dynamic workloads
Dingheng Mo, Fanchao Chen, Siqiang Luo, and Caihua Shan · 2023
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Vexless: A serverless vector data management system using cloud functions
Yongye Su, Yinqi Sun, Minjia Zhang, and Jianguo Wang · 2024
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Openai gpt-4o, 2024
OpenAI · 2024
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Yi: Open foundation models by 01. ai
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The claude 3 model family: Opus, sonnet, haiku, 2024
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Ruler: What’s the real context size of your long-context language models?
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Zachary Levonian, Chenglu Li, Wangda Zhu, Anoushka Gade, Owen Henkel, Millie-Ellen Postle, and Wanli Xing · 2023
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Query rewriting in retrieval-augmented large language models
Xinbei Ma, Yeyun Gong, Pengcheng He, Hai Zhao, and Nan Duan · 2023
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Llmtest needle in a haystack - pressure testing llms
gkamradt · 2023
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Large language models can be lazy learners: Analyze shortcuts in in-context learning
Ruixiang Tang, Dehan Kong, Longtao Huang, and Hui Xue · 2023
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https://github.com/multipledata/MTQA , 2023
Mtqa · 2023
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Improving the domain adaptation of retrieval augmented generation (rag) models for open domain question answering
Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen, Tharindu Kaluarachchi, Rajib Rana, and Suranga Nanayakkara · 2023
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Search augmented instruction learning
Hongyin Luo, Tianhua Zhang, Yung-Sung Chuang, Yuan Gong, Yoon Kim, Xixin Wu, Helen Meng, and James Glass · 2023
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Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, Shantanu Acharya, Dima Rekesh, Fei Jia, and Boris Ginsburg · 2024
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Weihang Su, Yichen Tang, Qingyao Ai, Zhijing Wu, and Yiqun Liu · 2024
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Rq-rag: Learning to refine queries for retrieval augmented generation
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A database of ambiguous chinese characters with measures for meaning dominance and meaning balance
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Extreme speed and scale for dl training and inference
Microsoft · 2024
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Jianlv Chen, Shitao Xiao, Peitian Zhang, Kun Luo, Defu Lian, and Zheng Liu · 2024
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
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Judging llm-as-a-judge with mt-bench and chatbot arena
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The faiss library
Matthijs Douze, Alexandr Guzhva, Chengqi Deng, Jeff Johnson, Gergely Szilvasy, Pierre-Emmanuel Mazaré, Maria Lomeli, Lucas Hosseini, and Hervé Jégou · 2024
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Needlebench: Can llms do retrieval and reasoning in 1 million context window?, 2024
Mo Li, Songyang Zhang, Yunxin Liu, and Kai Chen · 2024
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Multi-task inference: Can large language models follow multiple instructions at once?
Guijin Son, Sangwon Baek, Sangdae Nam, Ilgyun Jeong, and Seungone Kim · 2024
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Multi-task inference: Can large language models follow multiple instructions at once?
Guijin Son, Sangwon Baek, Sangdae Nam, Ilgyun Jeong, and Seungone Kim · 2024
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Making retrieval-augmented language models robust to irrelevant context
Ori Yoran, Tomer Wolfson, Ori Ram, and Jonathan Berant · 2024
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Rankrag: Unifying context ranking with retrieval-augmented generation in llms
Yue Yu, Wei Ping, Zihan Liu, Boxin Wang, Jiaxuan You, Chao Zhang, Mohammad Shoeybi, and Bryan Catanzaro · 2024
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