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We study ranked list truncation (RLT) from a novel "retrieve-then-re-rank" perspective, where we optimize re-ranking by truncating the retrieved list (i.e., trim re-ranking candidates).
The Kolmogorov-Smirnov, Cramer-Von Mises Tests
Donald A Darling. 1957 · 1957
Earlier work this paper cites.
Statistical Inference Using Extreme Order Statistics
James Pickands III. 1975 · 1975
Earlier work this paper cites.
Modeling Score Distributions for Combining the Outputs of Search Engines. In SIGIR . 267–275
Raghavan Manmatha, Toni Rath, and Fangfang Feng. 2001 · 2001
Earlier work this paper cites.
Efficient Query Evaluation using a Two-Level Retrieval Process. In CIKM . 426–434
Andrei Z Broder, David Carmel, Michael Herscovici, Aya Soffer, and Jason Zien. 2003 · 2003
Earlier work this paper cites.
Overview of the TREC 2007 Legal Track.. In TREC
Stephen Tomlinson, Douglas W Oard, Jason R Baron, and Paul Thompson. 2007 · 2007
Earlier work this paper cites.
Where to Stop Reading a Ranked List? Threshold Optimization using Truncated Score Distributions. In SIGIR . 524–531
Avi Arampatzis, Jaap Kamps, and Stephen Robertson. 2009 · 2009
Earlier work this paper cites.
The Probabilistic Relevance Framework: BM25 and Beyond
Stephen Robertson and Hugo Zaragoza. 2009 · 2009
Earlier work this paper cites.
Learning to Efficiently Rank. In SIGIR . 138–145
Lidan Wang, Jimmy Lin, and Donald Metzler. 2010 · 2010
Earlier work this paper cites.
A Cascade Ranking Model for Efficient Ranked Retrieval. In SIGIR . 105–114
Lidan Wang, Jimmy Lin, and Donald Metzler. 2011 · 2011
Earlier work this paper cites.
Effectiveness/Efficiency Tradeoffs for Candidate Generation in Multi-Stage Retrieval Architectures. In SIGIR . 997–1000
Nima Asadi and Jimmy Lin. 2013 · 2013
Earlier work this paper cites.
Patent Retrieval
Mihai Lupu and Allan Hanbury. 2013 · 2013
Earlier work this paper cites.
Efficient and Effective Retrieval using Selective Pruning. In WSDM . 63–72
Nicola Tonellotto, Craig Macdonald, and Iadh Ounis. 2013 · 2013
Earlier work this paper cites.
Distributed Representations of Sentences and Documents. In ICML . PMLR, 1188–1196
Quoc Le and Tomas Mikolov. 2014 · 2014
Earlier work this paper cites.
Adam: A Method for Stochastic Optimization. In ICLR
Diederik P Kingma and Jimmy Ba. 2015 · 2015
Earlier work this paper cites.
Dynamic Cutoff Prediction in Multi-Stage Retrieval Systems. In Proceedings of the 21st Australasian Document Computing Symposium . 17–24
J Shane Culpepper, Charles LA Clarke, and Jimmy Lin. 2016 · 2016
Earlier work this paper cites.
Attention Is All You Need. In NeurIPS . 5998–6008
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Overview of the TREC 2019 Deep Learning Track. In TREC
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M Voorhees. 2019 · 2019
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In NAACL . 4171–4186
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
An Assumption-Free Approach to the Dynamic Truncation of Ranked Lists. In ICTIR . 79–82
Yen-Chieh Lien, Daniel Cohen, and W Bruce Croft. 2019 · 2019
Earlier work this paper cites.
Rodrigo Nogueira and Kyunghyun Cho. 2019 · 2019
Earlier work this paper cites.
Multi-Stage Document Ranking with BERT
Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, and Jimmy Lin. 2019 · 2019
Earlier work this paper cites.
Choppy: Cut Transformer for Ranked List Truncation. In SIGIR . 1513–1516
Dara Bahri, Yi Tay, Che Zheng, Donald Metzler, and Andrew Tomkins. 2020 · 2020
Cited alongside, same era.
Overview of the TREC 2020 Deep Learning Track. In TREC
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2020 · 2020
Cited alongside, same era.
Understanding BERT Rankers Under Distillation. In SIGIR . 149–152
Luyu Gao, Zhuyun Dai, and Jamie Callan. 2020 · 2020
Cited alongside, same era.
Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking. In ECAI 2020 24th European Conference on Artificial Intelligence, 29 August-8 September 2020, Santiago de Compostela, Spain-Including 10th Conference on Prestigious Applications of Artificial Intelligence (PAIS 2020) . IOS Press, 1–8
Sebastian Hofstätter, Markus Zlabinger, and Allan Hanbury. 2020 · 2020
Cited alongside, same era.
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations. In SIGIR . 49–58
Sean MacAvaney, Franco Maria Nardini, Raffaele Perego, Nicola Tonellotto, Nazli Goharian, and Ophir Frieder. 2020 · 2020
MtCut: A Multi-Task Framework for Ranked List Truncation. In WSDM . 1054–1062
Dong Wang, Jianxin Li, Tianchen Zhu, Haoyi Zhou, Qishan Zhu, Yuxin Wen, and Hongming Piao. 2022 · 2022
Later among the works it cites.
Stochastic Retrieval-Conditioned Reranking. In ICTIR . 81–91
Hamed Zamani, Michael Bendersky, Donald Metzler, Honglei Zhuang, and Xuanhui Wang. 2022 · 2022
Later among the works it cites.
LLM-based Retrieval and Generation Pipelines for TREC Interactive Knowledge Assistance Track (iKAT) 2023. In TREC
Zahra Abbasiantaeb, Chuan Meng, David Rau, Antonis Krasakis, Hossein A Rahmani, and Mohammad Aliannejadi. 2023 · 2023
Later among the works it cites.
Surprise: Result List Truncation via Extreme Value Theory. In SIGIR . 2404–2408
Dara Bahri, Che Zheng, Yi Tay, Donald Metzler, and Andrew Tomkins. 2023 · 2023
Later among the works it cites.
Efficient and Effective Tree-based and Neural Learning to Rank
Sebastian Bruch, Claudio Lucchese, and Franco Maria Nardini. 2023 · 2023
Later among the works it cites.
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Cited alongside, same era.
Reranking for Efficient Transformer-based Answer Selection. In SIGIR . 1577–1580
Yoshitomo Matsubara, Thuy Vu, and Alessandro Moschitti. 2020 · 2020
Cited alongside, same era.
Document Ranking with a Pretrained Sequence-to-Sequence Model. In EMNLP . 708–718
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020 · 2020
Cited alongside, same era.
The Cascade Transformer: an Application for Efficient Answer Sentence Selection. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . 5697–5708
Luca Soldaini and Alessandro Moschitti. 2020 · 2020
Cited alongside, same era.
Early Exiting BERT for Efficient Document Ranking. In Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing . 83–88
Ji Xin, Rodrigo Nogueira, Yaoliang Yu, and Jimmy Lin. 2020 · 2020
Cited alongside, same era.
Not All Relevance Scores are Equal: Efficient Uncertainty and Calibration Modeling for Deep Retrieval Models. In SIGIR . 654–664
Daniel Cohen, Bhaskar Mitra, Oleg Lesota, Navid Rekabsaz, and Carsten Eickhoff. 2021 · 2021
Cited alongside, same era.
A Modern Perspective on Query Likelihood with Deep Generative Retrieval Models. In ICTIR . 185–195
Oleg Lesota, Navid Rekabsaz, Daniel Cohen, Klaus Antonius Grasserbauer, Carsten Eickhoff, and Markus Schedl. 2021 · 2021
Cited alongside, same era.
Initiative-Aware Self-Supervised Learning for Knowledge-Grounded Conversations. In SIGIR . 522–532
Chuan Meng, Pengjie Ren, Zhumin Chen, Zhaochun Ren, Tengxiao Xi, and Maarten de Rijke. 2021 · 2021
Cited alongside, same era.
PaRaDe: Passage Ranking using Demonstrations with LLMs. In Findings of EMNLP . 14242–14252
Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, et al · 2023
Later among the works it cites.
Fine-Tuning LLaMA for Multi-Stage Text Retrieval
Xueguang Ma, Liang Wang, Nan Yang, Furu Wei, and Jimmy Lin. 2023a · 2023
Later among the works it cites.
Zero-Shot Listwise Document Reranking with a Large Language Model
Xueguang Ma, Xinyu Zhang, Ronak Pradeep, and Jimmy Lin. 2023b · 2023
Later among the works it cites.
Performance Prediction for Conversational Search Using Perplexities of Query Rewrites. In QPP++2023 . 25–28
Chuan Meng, Mohammad Aliannejadi, and Maarten de Rijke. 2023a · 2023
Later among the works it cites.
RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models
Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin. 2023a · 2023
Later among the works it cites.
RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!
Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin. 2023b · 2023
Later among the works it cites.
Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting
Zhen Qin, Rolf Jagerman, Kai Hui, Honglei Zhuang, Junru Wu, Jiaming Shen, Tianqi Liu, Jialu Liu, Donald Metzler, Xuanhui Wang, et al · 2023
Later among the works it cites.
Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent. In EMNLP . 14918–14937
Weiwei Sun, Lingyong Yan, Xinyu Ma, Pengjie Ren, Dawei Yin, and Zhaochun Ren. 2023 · 2023
Later among the works it cites.
Rank-without-GPT: Building GPT-Independent Listwise Rerankers on Open-Source Large Language Models
Xinyu Zhang, Sebastian Hofstätter, Patrick Lewis, Raphael Tang, and Jimmy Lin. 2023 · 2023
Later among the works it cites.
Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels
Honglei Zhuang, Zhen Qin, Kai Hui, Junru Wu, Le Yan, Xuanhui Wang, and Michael Berdersky. 2023b · 2023
Later among the works it cites.
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking
Shengyao Zhuang, Bing Liu, Bevan Koopman, and Guido Zuccon. 2023a · 2023
Later among the works it cites.
A Setwise Approach for Effective and Highly Efficient Zero-shot Ranking with Large Language Models
Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, and Guido Zuccon. 2023c · 2023
Later among the works it cites.
Query Performance Prediction: From Fundamentals to Advanced Techniques. In ECIR . Springer, 381–388
Negar Arabzadeh, Chuan Meng, Mohammad Aliannejadi, and Ebrahim Bagheri. 2024 · 2024
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Query Performance Prediction for Conversational Search and Beyond. In SIGIR
Chuan Meng. 2024 · 2024
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Query Performance Prediction using Relevance Judgments Generated by Large Language Models
Chuan Meng, Negar Arabzadeh, Arian Askari, Mohammad Aliannejadi, and Maarten de Rijke. 2024 · 2024
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