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Recently, substantial progress has been made in text ranking based on pretrained language models such as BERT.
Language models are few-shot learners
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Learning-to-Rank with BERT in TF-Ranking
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Learning to Rank for Information Retrieval
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The probabilistic relevance framework: BM25 and beyond
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Pretrained transformers for text ranking: BERT and beyond
Jimmy Lin, Rodrigo Nogueira, and Andrew Yates. 2020 · 2010
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Introducing LETOR 4.0 datasets
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MS MARCO: A human generated machine reading comprehension dataset
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An analysis of the softmax cross entropy loss for learning-to-rank with binary relevance
Sebastian Bruch, Xuanhui Wang, Michael Bendersky, and Marc Najork. 2019 · 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 · 2019
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Matthew Kelcey, Jacob Devlin, Kenton Lee, Kristina N. Toutanova, Llion Jones, Ming-Wei Chang, Andrew Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
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Beyond [CLS] through Ranking by Generation
Cicero dos Santos, Xiaofei Ma, Ramesh Nallapati, Zhiheng Huang, and Bing Xiang. 2020 · 2020
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Modularized transfomer-based ranking framework
Luyu Gao, Zhuyun Dai, and Jamie Callan. 2020 · 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 · 2020
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Are Neural Rankers still Outperformed by Gradient Boosted Decision Trees?
Zhen Qin, Le Yan, Honglei Zhuang, Yi Tay, Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, and Marc Najork. 2021 · 2021
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RocketQA: An optimized training approach to dense passage retrieval for open-domain question answering
Yingqi Qu, Yuchen Ding, Jing Liu, Kai Liu, Ruiyang Ren, Wayne Xin Zhao, Daxiang Dong, Hua Wu, and Haifeng Wang. 2021 · 2021
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RocketQAv2: A joint training method for dense passage retrieval and passage re-ranking
Ruiyang Ren, Yingqi Qu, Jing Liu, Wayne Xin Zhao, Qiaoqiao She, Hua Wu, Haifeng Wang, and Ji-Rong Wen. 2021 · 2021
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BEIR: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
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Deep Query Likelihood Model for Information Retrieval
Shengyao Zhuang, Hang Li, and Guido Zuccon. 2021 · 2021
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Col-BERT: Efficient and Effective Passage Search via Contextualized late Interaction over BERT
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Efficient document re-ranking for transformers by precomputing term representations
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Document Ranking with a Pretrained Sequence-to-Sequence Model
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N Bennett, Junaid Ahmed, and Arnold Overwijk. 2020 · 2020
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Rethink training of BERT rerankers in multi-stage retrieval pipeline
Luyu Gao, Zhuyun Dai, and Jamie Callan. 2021 · 2021
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Text-to-text multi-view learning for passage re-ranking
Jia-Huei Ju, Jheng-Hong Yang, and Chuan-Ju Wang. 2021 · 2021
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TILDE: Term Independent Likelihood moDEl for Passage Re-ranking
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PaLM: Scaling language modeling with pathways
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ED2LM: Encoder-decoder to language model for faster document re-ranking inference
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Large dual encoders are generalizable retrievers
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No parameter left behind: How distillation and model size affect zero-shot retrieval
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Improving passage retrieval with zero-shot question generation
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Transformer memory as a differentiable search index
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