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Pyserini is an easy-to-use Python toolkit that supports replicable IR research by providing effective first-stage retrieval in a multi-stage ranking architecture.
Report on the SIGIR 2015 Workshop on Reproducibility, Inexplicability, and Generalizability of Results (RIGOR)
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TensorFlow: A system for large-scale machine learning. In Proceedings of the 12th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’16) . 265–283
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Toward Reproducible Baselines: The Open-Source IR Reproducibility Challenge. In Proceedings of the 38th European Conference on Information Retrieval (ECIR 2016) . Padua, Italy, 408–420
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Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2017 · 2017
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Anserini: Enabling the Use of Lucene for Information Retrieval Research. In Proceedings of the 40th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017) . Tokyo, Japan, 1253–1256
Peilin Yang, Hui Fang, and Jimmy Lin. 2017 · 2017
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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
Peilin Yang, Hui Fang, and Jimmy Lin. 2018 · 2018
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Applying BERT to Document Retrieval with Birch. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations . Hong Kong, China, 19–24
Zeynep Akkalyoncu Yilmaz, Shengjin Wang, Wei Yang, Haotian Zhang, and Jimmy Lin. 2019 · 2019
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From doc2query to docTTTTTquery
Rodrigo Nogueira and Jimmy Lin. 2019 · 2019
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Multi-Stage Document Ranking with BERT
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin. 2019a · 2019
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Document Expansion by Query Prediction
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho. 2019b · 2019
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PyTorch: An Imperative Style, High-Performance Deep Learning Library. In Advances in Neural Information Processing Systems . 8024–8035
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
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A Lightweight Environment for Learning Experimental IR Research Practices. In Proceedings of the 43rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020) . 2113–2116
Zeynep Akkalyoncu Yilmaz, Charles L. A. Clarke, and Jimmy Lin. 2020 · 2020
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RRF102: Meeting the TREC-COVID Challenge with a 100+ Runs Ensemble
Michael Bendersky, Honglei Zhuang, Ji Ma, Shuguang Han, Keith Hall, and Ryan McDonald. 2020 · 2020
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Cydex: Neural Search Infrastructure for the Scholarly Literature. In Proceedings of the First Workshop on Scholarly Document Processing . 168–173
Shane Ding, Edwin Zhang, and Jimmy Lin. 2020 · 2020
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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Document Ranking with a Pretrained Sequence-to-Sequence Model. In Findings of the Association for Computational Linguistics: EMNLP 2020 . 708–718
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020 · 2020
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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Transformers: State-of-the-Art Natural Language Processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations . 38–45
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Andre Esteva, Anuprit Kale, Romain Paulus, Kazuma Hashimoto, Wenpeng Yin, Dragomir Radev, and Richard Socher. 2020 · 2020
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From MaxScore to Block-Max WAND: The Story of How Lucene Significantly Improved Query Evaluation Performance. In Proceedings of the 42nd European Conference on Information Retrieval, Part II (ECIR 2020) . 20–27
Adrien Grand, Robert Muir, Jim Ferenczi, and Jimmy Lin. 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) . 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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ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020) . 39–48
Omar Khattab and Matei Zaharia. 2020 · 2020
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Pretrained Transformers for Text Ranking: BERT and Beyond
Jimmy Lin, Rodrigo Nogueira, and Andrew Yates. 2020a · 2020
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Distilling Dense Representations for Ranking using Tightly-Coupled Teachers
Sheng-Chieh Lin, Jheng-Hong Yang, and Jimmy Lin. 2020b · 2020
Cited alongside, same era.
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2020 · 2020
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Capreolus: A Toolkit for End-to-End Neural Ad Hoc Retrieval. In Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM 2020) . Houston, Texas, 861–864
Andrew Yates, Siddhant Arora, Xinyu Zhang, Wei Yang, Kevin Martin Jose, and Jimmy Lin. 2020a · 2020
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Flexible IR Pipelines with Capreolus. In Proceedings of the 29th International Conference on Information and Knowledge Management (CIKM 2020) . 3181–3188
Andrew Yates, Kevin Martin Jose, Xinyu Zhang, and Jimmy Lin. 2020b · 2020
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Covidex: Neural Ranking Models and Keyword Search Infrastructure for the COVID-19 Open Research Dataset. In Proceedings of the First Workshop on Scholarly Document Processing . 31–41
Edwin Zhang, Nikhil Gupta, Raphael Tang, Xiao Han, Ronak Pradeep, Kuang Lu, Yue Zhang, Rodrigo Nogueira, Kyunghyun Cho, Hui Fang, and Jimmy Lin. 2020 · 2020
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Improving Efficient Neural Ranking Models with Cross-Architecture Knowledge Distillation
Sebastian Hofstätter, Sophia Althammer, Michael Schröder, Mete Sertkan, and Allan Hanbury. 2021 · 2021
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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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