A paper list on large language models for ranking. This list is currently maintained by Qi Liu at Gaoling School of Artificial Intelligence, Renmin University of China.
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Passage Re-ranking with BERT.
Rodrigo Nogueira, Kyunghyun Cho.
2019.10 [pdf] -
Document Ranking with a Pretrained Sequence-to-Sequence Model.
Rodrigo Nogueira, Zhiying Jiang, and Jimmy Lin.
2020.5 [pdf] -
The expando-mono-duo design pattern for text ranking with pretrained sequence-to-sequence models.
Ronak Pradeep, Rodrigo Nogueira, Jimmy Lin.
2021.1 [pdf] -
Improving Passage Retrieval with Zero-Shot Question Generation.
Devendra Sachan, Mike Lewis, Mandar Joshi, Armen Aghajanyan, Wen-tau Yih, Joelle Pineau, and Luke Zettlemoyer.
2022.4 [pdf] -
Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent.
Weiwei Sun, Lingyong Yan, Xinyu Ma, Pengjie Ren, Dawei Yin, and Zhaochun Ren.
2023.4 [pdf] -
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, Michael Bendersky.
2023.6 [pdf] -
Fine-Tuning LLaMA for Multi-Stage Text Retrieval.
Xueguang Ma, Liang Wang, Nan Yang, Furu Wei, Jimmy Lin.
2023.10 [pdf]
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RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses.
Honglei Zhuang, Zhen Qin, Rolf Jagerman, Kai Hui, Ji Ma, Jing Lu, Jianmo Ni, Xuanhui Wang, and Michael Bendersky.
2022.10 [pdf] -
Zero-Shot Listwise Document Reranking with a Large Language Model.
Xueguang Ma, Xinyu Zhang, Ronak Pradeep, and Jimmy Lin.
2023.5 [pdf] -
Found in the Middle: Permutation Self-Consistency Improves Listwise Ranking in Large Language Models.
Raphael Tang, Xinyu Zhang, Xueguang Ma, Jimmy Lin, and Ferhan Ture.
2023.10 [pdf] -
RankVicuna: Zero-Shot Listwise Document Reranking with Open-Source Large Language Models.
Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin.
2023.9 [pdf] -
RankZephyr: Effective and Robust Zero-Shot Listwise Reranking Is a Breeze!
Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin.
2023.12 [pdf] -
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.
2023.10 [pdf] -
PaRaDe: Passage Ranking Using Demonstrations with Large Language Models.
Andrew Drozdov, Honglei Zhuang, Zhuyun Dai, Zhen Qin, Razieh Rahimi, Xuanhui Wang, Dana Alon, Mohit Iyyer, Andrew McCallum, Donald Metzler, Kai Hui.
2023.10 [pdf] -
A Two-Stage Adaptation of Large Language Models for Text Ranking.
Longhui Zhang, Yanzhao Zhang, Dingkun Long, Pengjun Xie, Meishan Zhang, Min Zhang.
2023.11 [pdf] -
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.
2023.12 [pdf] -
ListT5: Listwise Reranking with Fusion-in-Decoder Improves Zero-Shot Retrieval.
Soyoung Yoon, Eunbi Choi, Jiyeon Kim, Hyeongu Yun, Yireun Kim, and Seung-won Hwang.
2024.2 [pdf] -
Consolidating Ranking and Relevance Predictions of Large Language Models through Post-Processing.
Le Yan, Zhen Qin, Honglei Zhuang, Rolf Jagerman, Xuanhui Wang, Michael Bendersky, and Harrie Oosterhuis.
2024.4 [pdf] -
Generating Diverse Criteria On-the-Fly to Improve Point-Wise LLM Rankers.
Fang Guo, Wenyu Li, Honglei Zhuang, Yun Luo, Yafu Li, Le Yan, and Yue Zhang.
2024.4 [pdf] -
LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-Based Ranking.
Yifan Zeng, Ojas Tendolkar, Raymond Baartmans, Qingyun Wu, Huazheng Wang, and Lizhong Chen.
2024.5 [pdf] -
TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy.
Yiqun Chen, Qi Liu, Yi Zhang, Weiwei Sun, Daiting Shi, Jiaxin Mao, and Dawei Yin.
2024.6 [pdf] -
Improving Zero-Shot LLM Re-Ranker with Risk Minimization.
Xiaowei Yuan, Zhao Yang, Yequan Wang, Jun Zhao, and Kang Liu.
2024.6 [pdf] -
APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking.
Can Jin, Hongwu Peng, Shiyu Zhao, Zhenting Wang, Wujiang Xu, Ligong Han, Jiahui Zhao, Kai Zhong, Sanguthevar Rajasekaran, and Dimitris N. Metaxas.
2024.6 [pdf] -
DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking Task.
Wenhan Liu, Yutao Zhu, and Zhicheng Dou.
2024.6 [pdf] -
PRP-Graph: Pairwise Ranking Prompting to LLMs with Graph Aggregation for Effective Text Re-ranking.
Jian Luo, Xuanang Chen, Ben He, Le Sun.
2024.6 [pdf] -
Few-Shot Prompting for Pairwise Ranking: An Effective Non-Parametric Retrieval Model.
Nilanjan Sinhababu, Andrew Parry, Debasis Ganguly, Debasis Samanta, Pabitra Mitra.
2024.10 [pdf] -
ChainRank-DPO: Chain Rank Direct Preference Optimization.
Haowei Liu, Xuyang Wu, Guohao Sun, Zhiqiang Tao, Yi Fang.
2024.12 [pdf] -
Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models.
Wenhan Liu, Xinyu Ma, Yutao Zhu, Ziliang Zhao, Shuaiqiang Wang, Dawei Yin, Zhicheng Dou.
2024.12 [pdf] -
Batched Self-Consistency Improves LLM Relevance Assessment and Ranking.
Anton Korikov, Pan Du, Scott Sanner, Navid Rekabsaz.
2025.5 [pdf] -
InsertRank: LLMs Can Reason over BM25 Scores to Improve Listwise Reranking.
Rahul Seetharaman, Kaustubh D. Dhole, Aman Bansal.
2025.6 [pdf] -
GroupRank: A Ranking Method Based on Group Preference.
Duolin Sun, Meixiu Long, Dan Yang, Yihan Jiao, Zhehao Tan, Jie Feng, Junjie Wang, Yue Shen, Peng Wei, Jian Wang, Jinjie Gu.
2025.11 [pdf]
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A Setwise Approach for Effective and Highly Efficient Zero-Shot Ranking with Large Language Models.
Shengyao Zhuang, Honglei Zhuang, Bevan Koopman, and Guido Zuccon.
2023.10 [pdf] -
Ranked List Truncation for Large Language Model-Based Re-Ranking.
Chuan Meng, Negar Arabzadeh, Arian Askari, Mohammad Aliannejadi, and Maarten de Rijke.
2024.4 [pdf] -
Top-Down Partitioning for Efficient List-Wise Ranking.
Andrew Parry, Sean MacAvaney, and Debasis Ganguly.
2024.5 [pdf] -
Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models.
Qi Liu, Bo Wang, Nan Wang, and Jiaxin Mao.
2024.6 [pdf] -
FIRST: Faster Improved Listwise Reranking with Single Token Decoding.
Revanth Gangi Reddy, JaeHyeok Doo, Yifei Xu, Md Arafat Sultan, Deevya Swain, Avirup Sil, Heng Ji.
2024.6 [pdf] -
Attention in Large Language Models Yields Efficient Zero-Shot Re-Rankers.
Shijie Chen, Bernal Jiménez Gutiérrez, and Yu Su.
2024.10 [pdf] -
Self-Calibrated Listwise Reranking with Large Language Models.
Ruiyang Ren, Yuhao Wang, Kun Zhou, Wayne Xin Zhao, Wenjie Wang, Jing Liu, Ji-Rong Wen, Tat-Seng Chua.
2024.11 [pdf] -
Query-Focused Retrieval Heads Improve Long-Context Reasoning and Re-ranking.
Wuwei Zhang, Fangcong Yin, Howard Yen, Danqi Chen, Xi Ye.
2025.6 [pdf] -
AcuRank: Uncertainty-Aware Adaptive Computation for Listwise Reranking.
Soyoung Yoon, Gyuwan Kim, Gyu-Hwung Cho, Seung-won Hwang.
2025.5 [pdf] -
Matryoshka Re-Ranker: Learning to Route Document Pairs for Efficient and Effective Listwise Reranking.
Zheng Liu, Chaofan Li, Shitao Xiao, Chaozhuo Li, Defu Lian, Yingxia Shao.
2025.1 [pdf] -
ListConRanker: Listwise Contrastive Reranker for Large Language Model.
Junlong Liu, Yue Ma, Ruihui Zhao, Junhao Zheng, Qianli Ma, Yangyang Kang.
2025.1 [pdf] -
E2R-FLOPs: Efficiency-Effectiveness Reranking FLOPs for LLM-Based Rerankers.
Zhiyuan Peng, Ting-ruen Wei, Tingyu Song, Yilun Zhao, Yi Fang.
2025.7 [pdf] -
Contrastive Retrieval Heads Improve Attention-Based Re-Ranking.
Linh Tran, Yulong Li, Radu Florian, Wei Sun.
2025.10 [pdf] -
E2Rank: Efficient Embedding for LLM-based Listwise Reranking.
Qi Liu, Yanzhao Zhang, Mingxin Li, Dingkun Long, Pengjun Xie, Jiaxin Mao.
2025.10 [pdf]
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ReasoningRank: Teaching Student Models to Rank through Reasoning-Based Knowledge Distillation.
Yuelyu Ji, Zhuochun Li, Rui Meng, and Daqing He.
2024.10 [pdf] -
JudgeRank: Leveraging Large Language Models for RAG-Enhanced Reranking.
Tong Niu, Shafiq Joty, Ye Liu, Caiming Xiong, Yingbo Zhou, Semih Yavuz.
2024.10 [pdf] -
Rank1: Test-Time Compute for Reranking.
Orion Weller, Kathryn Ricci, Eugene Yang, Andrew Yates, Dawn Lawrie, Benjamin Van Durme.
2025.2 [pdf] -
Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning.
Shengyao Zhuang, Xueguang Ma, Bevan Koopman, Jimmy Lin, Guido Zuccon.
2025.3 [pdf] -
REARANK: Reasoning Re-ranking Agent via Reinforcement Learning.
Le Zhang, Bo Wang, Xipeng Qiu, Siva Reddy, Aishwarya Agrawal.
2025.5 [pdf] -
ERank: Fusing Supervised Fine-Tuning and Reinforcement Learning for Effective and Efficient Text Reranking.
Yuzheng Cai, Yanzhao Zhang, Dingkun Long, Mingxin Li, Pengjun Xie, Weiguo Zheng.
2025.8 [pdf] -
Don't "Overthink" Passage Reranking: Is Reasoning Truly Necessary?
Nour Jedidi, Yung-Sung Chuang, James Glass, Jimmy Lin.
2025.5 [pdf] -
TFRank: Think-Free Reasoning Enables Practical Pointwise LLM Ranking.
Yongqi Fan, Xiaoyang Chen, Dezhi Ye, Jie Liu, Haijin Liang, Jin Ma, Ben He, Yingfei Sun, Tong Ruan.
2025.8 [pdf] -
Rank-K: Test-Time Reasoning for Listwise Reranking.
Eugene Yang, Andrew Yates, Kathryn Ricci, Orion Weller, Vivek Chari, Benjamin Van Durme, Dawn Lawrie.
2025.5 [pdf] -
LimRank: Less is More for LLM-based Reasoning-Intensive Reranking.
Tingyu Song, Yilun Zhao, Siyue Zhang, Chen Zhao, Arman Cohan.
2025.10 [pdf]