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We introduce Rank1, the first reranking model trained to take advantage of test-time compute.
Okapi at trec-3
Stephen E. Robertson, Steve Walker, Susan Jones, Micheline Hancock-Beaulieu, and Mike Gatford · 1994
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MS MARCO: A human generated machine reading comprehension dataset
Tri Nguyen, Mir Rosenberg, Xia Song, Jianfeng Gao, Saurabh Tiwary, Rangan Majumder, and Li Deng · 2016
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Www’18 open challenge: financial opinion mining and question answering
Macedo Maia, Siegfried Handschuh, André Freitas, Brian Davis, Ross McDermott, Manel Zarrouk, and Alexandra Balahur · 2018
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Document expansion by query prediction
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho · 2019
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Overview of the TREC 2019 deep learning track
Nick Craswell, Bhaskar Mitra, Emine Yilmaz, Daniel Campos, and Ellen M Voorhees · 2020
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Fact or fiction: Verifying scientific claims
David Wadden, Shanchuan Lin, Kyle Lo, Lucy Lu Wang, Madeleine van Zuylen, Arman Cohan, and Hannaneh Hajishirzi · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush · 2020
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Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych · 2021
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Task-aware retrieval with instructions
Akari Asai, Timo Schick, Patrick Lewis, Xilun Chen, Gautier Izacard, Sebastian Riedel, Hannaneh Hajishirzi, and Wen-tau Yih · 2022
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Mteb: Massive text embedding benchmark
Niklas Muennighoff, Nouamane Tazi, Loïc Magne, and Nils Reimers · 2022
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One embedder, any task: Instruction-finetuned text embeddings
Hongjin Su, Weijia Shi, Jungo Kasai, Yizhong Wang, Yushi Hu, Mari Ostendorf, Wen-tau Yih, Noah A. Smith, Luke Zettlemoyer, and Tao Yu · 2022
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Can old trec collections reliably evaluate modern neural retrieval models?
Ellen M Voorhees, Ian Soboroff, and Jimmy Lin · 2022
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Nellie: A neuro-symbolic inference engine for grounded, compositional, and explainable reasoning
Nathaniel Weir, Peter Clark, and Benjamin Van Durme · 2022
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NeuralMind-UNICAMP at 2022 TREC NeuCLIR: Large boring rerankers for cross-lingual retrieval
Vitor Jeronymo, Roberto Lotufo, and Rodrigo Nogueira · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica · 2023
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Awq: Activation-aware weight quantization for llm compression and acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Xingyu Dang, and Song Han · 2023
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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
Cited alongside, same era.
Llama 3 model card
AI@Meta · 2024
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Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al · 2024
Cited alongside, same era.
Scaling llm test-time compute optimally can be more effective than scaling model parameters
Charlie Snell, Jaehoon Lee, Kelvin Xu, and Aviral Kumar · 2024
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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, Haisu Liu, Quan Shi, Zachary S Siegel, Michael Tang, et al · 2024
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Systematic evaluation of neural retrieval models on the touché 2020 argument retrieval subset of beir
Nandan Thakur, Luiz Bonifacio, Maik Fröbe, Alexander Bondarenko, Ehsan Kamalloo, Martin Potthast, Matthias Hagen, and Jimmy Lin · 2024
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Multilingual e5 text embeddings: A technical report
Liang Wang, Nan Yang, Xiaolong Huang, Linjun Yang, Rangan Majumder, and Furu Wei · 2024
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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
Cited alongside, same era.
Overview of the trec 2023 neuclir track, 2024
Dawn Lawrie, Sean MacAvaney, James Mayfield, Paul McNamee, Douglas W. Oard, Luca Soldaini, and Eugene Yang · 2024
Cited alongside, same era.
Gecko: Versatile text embeddings distilled from large language models
Jinhyuk Lee, Zhuyun Dai, Xiaoqi Ren, Blair Chen, Daniel Cer, Jeremy R Cole, Kai Hui, Michael Boratko, Rajvi Kapadia, Wen Ding, et al · 2024
Cited alongside, same era.
Bm25s: Orders of magnitude faster lexical search via eager sparse scoring
Xing Han Lù · 2024
Cited alongside, same era.
Fine-tuning llama for multi-stage text retrieval
Xueguang Ma, Liang Wang, Nan Yang, Furu Wei, and Jimmy Lin · 2024
Cited alongside, same era.
On the evaluation of machine-generated reports
James Mayfield, Eugene Yang, Dawn Lawrie, Sean MacAvaney, Paul McNamee, Douglas W Oard, Luca Soldaini, Ian Soboroff, Orion Weller, Efsun Kayi, et al · 2024
Cited alongside, same era.
Generative representational instruction tuning
Niklas Muennighoff, Hongjin Su, Liang Wang, Nan Yang, Furu Wei, Tao Yu, Amanpreet Singh, and Douwe Kiela · 2024
Cited alongside, same era.
Benjamin Warner, Antoine Chaffin, Benjamin Clavié, Orion Weller, Oskar Hallström, Said Taghadouini, Alexis Gallagher, Raja Biswas, Faisal Ladhak, Tom Aarsen, et al · 2024
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Enhancing systematic decompositional natural language inference using informal logic
Nathaniel Weir, Kate Sanders, Orion Weller, Shreya Sharma, Dongwei Jiang, Zhengping Jiang, Bhavana Dalvi Mishra, Oyvind Tafjord, Peter Jansen, Peter Clark, et al · 2024
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al · 2024
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Llamafactory: Unified efficient fine-tuning of 100+ language models
Yaowei Zheng, Richong Zhang, Junhao Zhang, Yanhan Ye, Zheyan Luo, Zhangchi Feng, and Yongqiang Ma · 2024
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Mmteb: Massive multilingual text embedding benchmark
Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, Márton Kardos, Ashwin Mathur, David Stap, Jay Gala, Wissam Siblini, Dominik Krzemiński, Genta Indra Winata, et al · 2025
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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
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Is that your final answer? test-time scaling improves selective question answering
William Jurayj, Jeffrey Cheng, and Benjamin Van Durme · 2025
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Niklas Muennighoff, Zitong Yang, Weijia Shi, Xiang Lisa Li, Li Fei-Fei, Hannaneh Hajishirzi, Luke Zettlemoyer, Percy Liang, Emmanuel Candès, and Tatsunori Hashimoto · 2025
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Reproducing nevir: Negation in neural information retrieval
Coen van Elsen, Francien Barkhof, Thijmen Nijdam, Simon Lupart, and Mohammad Alliannejadi · 2025
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mfollowir: a multilingual benchmark for instruction following in retrieval
Orion Weller, Benjamin Chang, Eugene Yang, Mahsa Yarmohammadi, Sam Barham, Sean MacAvaney, Arman Cohan, Luca Soldaini, Benjamin Van Durme, and Dawn Lawrie · 2025
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