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We present the Benchmark of Information Retrieval (IR) tasks with Complex Objectives (BIRCO).
Drop: A reading comprehension benchmark requiring discrete reasoning over paragraphs
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A test collection for matching patients to clinical trials
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HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018 · 2018
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Matthew Kelcey, Jacob Devlin, Kenton Lee, Kristina N. Toutanova, Llion Jones, Ming-Wei Chang, Andrew Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
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Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 2019
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Overview of touché 2020: argument retrieval
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Measuring massive multitask language understanding
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Document ranking with a pretrained sequence-to-sequence model
Rodrigo Nogueira, Zhiying Jiang, Ronak Pradeep, and Jimmy Lin. 2020 · 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 · 2020
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Splade v2: Sparse lexical and expansion model for information retrieval
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SimCSE: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Beir: A heterogeneous benchmark for zero-shot evaluation of information retrieval models
Nandan Thakur, Nils Reimers, Andreas Rücklé, Abhishek Srivastava, and Iryna Gurevych. 2021 · 2021
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Trec-covid: constructing a pandemic information retrieval test collection
Ellen Voorhees, Tasmeer Alam, Steven Bedrick, Dina Demner-Fushman, William R. Hersh, Kyle Lo, Kirk Roberts, Ian Soboroff, and Lucy Lu Wang. 2021 · 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. 2023 · 2023
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Exaranker: Synthetic explanations improve neural rankers
Fernando Ferraretto, Thiago Laitz, Roberto Lotufo, and Rodrigo Nogueira. 2023 · 2023
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Precise zero-shot dense retrieval without relevance labels
Luyu Gao, Xueguang Ma, Jimmy Lin, and Jamie Callan. 2023 · 2023
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New and improved embedding model
Ryan Greene, Ted Sanders, Lilian Weng, and Arvind Neelakantan. 2022 · 2023
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Decomposing complex queries for tip-of-the-tongue retrieval
Kevin Lin, Kyle Lo, Joseph E Gonzalez, and Dan Klein. 2023 · 2023
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RankCSE: Unsupervised sentence representations learning via learning to rank
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DiffCSE: Difference-based contrastive learning for sentence embeddings
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Promptagator: Few-shot dense retrieval from 8 examples
Zhuyun Dai, Vincent Y Zhao, Ji Ma, Yi Luan, Jianmo Ni, Jing Lu, Anton Bakalov, Kelvin Guu, Keith Hall, and Ming-Wei Chang. 2022 · 2022
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From distillation to hard negative sampling: Making sparse neural ir models more effective
Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. 2022 · 2022
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Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch. 2022 · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Holistic evaluation of language models
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, et al. 2022 · 2022
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OpenAI. 2023 · 2023
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Controlretriever: Harnessing the power of instructions for controllable retrieval
Kaihang Pan, Juncheng Li, Hongye Song, Hao Fei, Wei Ji, Shuo Zhang, Jun Lin, Xiaozhong Liu, and Siliang Tang. 2023 · 2023
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StripedHyena: Moving Beyond Transformers with Hybrid Signal Processing Models
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Large language models are effective text rankers with pairwise ranking prompting
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One embedder, any task: Instruction-finetuned text embeddings
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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 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Doris-mae: Scientific document retrieval using multi-level aspect-based queries
Jianyou Wang, Kaicheng Wang, Xiaoyue Wang, Prudhviraj Naidu, Leon Bergen, and Ramamohan Paturi. 2023 · 2023
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MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages
Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, Ehsan Kamalloo, David Alfonso-Hermelo, Xiaoguang Li, Qun Liu, Mehdi Rezagholizadeh, and Jimmy Lin. 2023 · 2023
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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 · 2023
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Together ai
Vipul Ved Prakash, Ce Zhang, Chris Ré, and Percy Liang. 2024 · 2024
Closest in time.
Ir2: Information regularization for information retrieval
Jianyou Wang, Kaicheng Wang, Xiaoyue Wang, Weili Cao, Ramamohan Paturi, and Leon Bergen. 2024 · 2024
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