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In this paper, we introduce Rank-R1, a novel LLM-based reranker that performs reasoning over both the user query and candidate documents before performing the ranking task.
Overview of the trec 2019 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M. Voorhees. 2020 · 2003
Earlier work this paper cites.
Overview of the trec 2020 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, and Daniel Campos. 2021 · 2020
Earlier work this paper cites.
Trl: Transformer reinforcement learning
Leandro von Werra, Younes Belkada, Lewis Tunstall, Edward Beeching, Tristan Thrush, Nathan Lambert, Shengyi Huang, Kashif Rasul, and Quentin Gallouédec. 2020 · 2020
Earlier work this paper cites.
Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin, Jheng-Hong Yang, Ronak Pradeep, and Rodrigo Nogueira. 2021 · 2021
Earlier work this paper cites.
LoRA: Low-rank adaptation of large language models
Edward J Hu, yelong shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2022 · 2022
Earlier work this paper cites.
Tevatron: An efficient and flexible toolkit for neural retrieval
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan. 2023 · 2023
Earlier work this paper cites.
Zero-shot listwise document reranking with a large language model
Xueguang Ma, Xinyu Zhang, Ronak Pradeep, and Jimmy Lin. 2023 · 2023
Earlier work this paper cites.
Rankzephyr: Effective and robust zero-shot listwise reranking is a breeze!
Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin. 2023 · 2023
Cited alongside, same era.
Is ChatGPT good at search? investigating large language models as re-ranking agents
Weiwei Sun, Lingyong Yan, Xinyu Ma, Shuaiqiang Wang, Pengjie Ren, Zhumin Chen, Dawei Yin, and Zhaochun Ren. 2023 · 2023
Cited alongside, same era.
Zephyr: Direct distillation of lm alignment
Lewis Tunstall, Edward Beeching, Nathan Lambert, Nazneen Rajani, Kashif Rasul, Younes Belkada, Shengyi Huang, Leandro von Werra, Clémentine Fourrier, Nathan Habib, Nathan Sarrazin, Omar Sanseviero, Alexander M. Rush, and Thomas Wolf. 2023 · 2023
Cited alongside, same era.
Open-source large language models are strong zero-shot query likelihood models for document ranking
Shengyao Zhuang, Bing Liu, Bevan Koopman, and Guido Zuccon. 2023 · 2023
Cited alongside, same era.
Fine-tuning llama for multi-stage text retrieval
An investigation of prompt variations for zero-shot llm-based rankers
Shuoqi Sun, Shengyao Zhuang, Shuai Wang, and Guido Zuccon. 2024 · 2024
Later among the works it cites.
Rankmamba: Benchmarking mamba’s document ranking performance in the era of transformers
Zhichao Xu. 2024 · 2024
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 Bendersky. 2024a · 2024
Later among the works it cites.
Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al. 2025 · 2025
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Xueguang Ma, Liang Wang, Nan Yang, Furu Wei, and Jimmy Lin. 2024 · 2024
Cited alongside, same era.
OpenAI et al. 2024 · 2024
Cited alongside, same era.
Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, Y. K. Li, Y. Wu, and Daya Guo. 2024 · 2024
Cited alongside, same era.
A setwise approach for effective and highly efficient zero-shot ranking with large language models
Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, and Guido Zuccon. 2024b
Cited in the paper.
Qwen et al. 2025 · 2025
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BRIGHT: A realistic and challenging benchmark for reasoning-intensive retrieval
Hongjin SU, Howard Yen, Mengzhou Xia, Weijia Shi, Niklas Muennighoff, Han yu Wang, Liu Haisu, Quan Shi, Zachary S Siegel, Michael Tang, Ruoxi Sun, Jinsung Yoon, Sercan O Arik, Danqi Chen, and Tao Yu. 2025 · 2025
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7b model and 8k examples: Emerging reasoning with reinforcement learning is both effective and efficient
Weihao Zeng, Yuzhen Huang, Wei Liu, Keqing He, Qian Liu, Zejun Ma, and Junxian He. 2025 · 2025
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