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We provide a reproducible, end-to-end demonstration of vector search with OpenAI embeddings using Lucene on the popular MS MARCO passage ranking test collection.
What Goes Around Comes Around
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A Comparison of Approaches to Large-Scale Data Analysis. In Proceedings of the 35th ACM SIGMOD International Conference on Management of Data . Providence, Rhode Island, 165–178
Andrew Pavlo, Erik Paulson, Alexander Rasin, Daniel J. Abadi, David J. DeWitt, Samuel Madden, and Michael Stonebraker. 2009 · 2009
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MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, and Tong Wang. 2018 · 2018
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Anserini: Reproducible Ranking Baselines Using Lucene
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Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees. 2019 · 2019
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Billion-scale similarity search with GPUs
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Overview of the TREC 2020 Deep Learning Track. In Proceedings of the Twenty-Ninth Text REtrieval Conference Proceedings (TREC 2020) . Gaithersburg, Maryland
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2020 · 2020
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Dense Passage Retrieval for Open-Domain Question Answering. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) . Online, 6769–6781
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs
Yu A. Malkov and D. A. Yashunin. 2020 · 2020
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Efficiently Teaching an Effective Dense Retriever with Balanced Topic Aware Sampling. In Proceedings of the 44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021) . 113–122
Sebastian Hofstätter, Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin, and Allan Hanbury. 2021 · 2021
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Towards Unsupervised Dense Information Retrieval with Contrastive Learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2021 · 2021
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A Proposed Conceptual Framework for a Representational Approach to Information Retrieval
Jimmy Lin. 2021 · 2021
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Pyserini: A Python Toolkit for Reproducible Information Retrieval Research with Sparse and Dense Representations. In Proceedings of the 44th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2021) . 2356–2362
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, and Rodrigo Nogueira. 2021a · 2021
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In-Batch Negatives for Knowledge Distillation with Tightly-Coupled Teachers for Dense Retrieval. In Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021) . 163–173
Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2021b · 2021
Another Look at DPR: Reproduction of Training and Replication of Retrieval. In Proceedings of the 44th European Conference on Information Retrieval (ECIR 2022), Part I . Stavanger, Norway, 613–626
Xueguang Ma, Kai Sun, Ronak Pradeep, Minghan Li, and Jimmy Lin. 2022b · 2022
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Text and Code Embeddings by Contrastive Pre-Training
Arvind Neelakantan, Tao Xu, Raul Puri, Alec Radford, Jesse Michael Han, Jerry Tworek, Qiming Yuan, Nikolas Tezak, Jong Wook Kim, Chris Hallacy, Johannes Heidecke, Pranav Shyam, Boris Power, Tyna Eloundou Nekoul, Girish Sastry, Gretchen Krueger, David Schnurr, Felipe Petroski Such, Kenny Hsu, Madeleine Thompson, Tabarak Khan, Toki Sherbakov, Joanne Jang, Peter Welinder, and Lilian Weng. 2022 · 2022
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ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Seattle, United States, 3715–3734
Keshav Santhanam, Omar Khattab, Jon Saad-Falcon, Christopher Potts, and Matei Zaharia. 2022 · 2022
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The Expando-Mono-Duo Design Pattern for Text Ranking with Pretrained Sequence-to-Sequence Models
Ronak Pradeep, Rodrigo Nogueira, and Jimmy Lin. 2021 · 2021
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Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval. In Proceedings of the 9th International Conference on Learning Representations (ICLR 2021)
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N. Bennett, Junaid Ahmed, and Arnold Overwijk. 2021 · 2021
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Aligning the Research and Practice of Building Search Applications: Elasticsearch and Pyserini. In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022) . 1573–1576
Josh Devins, Julie Tibshirani, and Jimmy Lin. 2022 · 2022
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From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022) . Madrid, Spain, 2353–2359
Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. 2022 · 2022
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Building a Culture of Reproducibility in Academic Research
Jimmy Lin. 2022 · 2022
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Document Expansions and Learned Sparse Lexical Representations for MS MARCO V1 and V2. In Proceedings of the 45th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2022) . Madrid, Spain, 3187–3197
Xueguang Ma, Ronak Pradeep, Rodrigo Nogueira, and Jimmy Lin. 2022a · 2022
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Retrieval-based Language Models and Applications. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 6: Tutorial Abstracts) . Toronto, Canada, 41–46
Akari Asai, Sewon Min, Zexuan Zhong, and Danqi Chen. 2023 · 2023
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Evaluating Embedding APIs for Information Retrieval. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track) . Toronto, Canada, 518–526
Ehsan Kamalloo, Xinyu Zhang, Odunayo Ogundepo, Nandan Thakur, David Alfonso-hermelo, Mehdi Rezagholizadeh, and Jimmy Lin. 2023 · 2023
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Aggretriever: A Simple Approach to Aggregate Textual Representations for Robust Dense Passage Retrieval
Sheng-Chieh Lin, Minghan Li, and Jimmy Lin. 2023 · 2023
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A Dense Representation Framework for Lexical and Semantic Matching
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Anserini Gets Dense Retrieval: Integration of Lucene’s HNSW Indexes. In Proceedings of the 32nd International Conference on Information and Knowledge Management (CIKM 2023) . Birmingham, the United Kingdom
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Augmented Language Models: a Survey
Grégoire Mialon, Roberto Dessì, Maria Lomeli, Christoforos Nalmpantis, Ram Pasunuru, Roberta Raileanu, Baptiste Rozière, Timo Schick, Jane Dwivedi-Yu, Asli Celikyilmaz, Edouard Grave, Yann LeCun, and Thomas Scialom. 2023 · 2023
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