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Large Language Models (LLMs) are increasingly employed in zero-shot documents ranking, yielding commendable results.
The probabilistic relevance framework: BM25 and beyond
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Overview of the TREC 2019 deep learning track
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Systematic Evaluation of Neural Retrieval Models on the Touché 2020 Argument Retrieval Subset of BEIR. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval
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From distillation to hard negative sampling: Making sparse neural ir models more effective. In Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval . 2353–2359
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Improving passage retrieval with zero-shot question generation
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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 · 2023
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Large language models for information retrieval: A survey
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Zero-shot listwise document reranking with a large language model
Xueguang Ma, Xinyu Zhang, Ronak Pradeep, and Jimmy Lin. 2023 · 2023
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Rankvicuna: Zero-shot listwise document reranking with open-source large language models
Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin. 2023a · 2023
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RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!
Ronak Pradeep, Sahel Sharifymoghaddam, and Jimmy Lin. 2023b · 2023
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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
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Instruction distillation makes large language models efficient zero-shot rankers
Weiwei Sun, Zheng Chen, Xinyu Ma, Lingyong Yan, Shuaiqiang Wang, Pengjie Ren, Zhumin Chen, Dawei Yin, and Zhaochun Ren. 2023a · 2023
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Is chatgpt good at search? investigating large language models as re-ranking agent
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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 · 2024
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Lost in the middle: How language models use long contexts
Nelson F Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang. 2024a · 2024
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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, and Zhicheng Dou. 2024b · 2024
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Demorank: Selecting effective demonstrations for large language models in ranking task
Wenhan Liu, Yutao Zhu, and Zhicheng Dou. 2024c · 2024
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PRP-Graph: Pairwise Ranking Prompting to LLMs with Graph Aggregation for Effective Text Re-ranking. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) . 5766–5776
Jian Luo, Xuanang Chen, Ben He, and Le Sun. 2024 · 2024
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Meta Llama 3
MetaAI. 2024 · 2024
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ListT5: Listwise Reranking with Fusion-in-Decoder Improves Zero-shot Retrieval
Soyoung Yoon, Eunbi Lee, Jiyeon Kim, Yireun Kim, Hyeongu Yun, and Seung-won Hwang. 2024 · 2024
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