RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation

Reciprocal rank fusion outperforms condorcet and individual rank learning methods

Gordon V. Cormack, Charles L A Clarke, and Stefan Buettcher. 2009 · 2009

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Exploiting query reformulations for web search result diversification

Rodrygo L.T. Santos, Craig Macdonald, and Iadh Ounis. 2010 · 2010

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Diversity by proportionality: an election-based approach to search result diversification

Van Dang and W. Bruce Croft. 2012 · 2012

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Decoupled weight decay regularization

Ilya Loshchilov and Frank Hutter. 2019 · 2019

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Retrieval-augmented generation for knowledge-intensive nlp tasks

Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020 · 2020

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Dvgan: A minimax game for search result diversification combining explicit and implicit features

Jiongnan Liu, Zhicheng Dou, Xiaojie Wang, Shuqi Lu, and Ji-Rong Wen. 2020 · 2020

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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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Exploring the limits of transfer learning with a unified text-to-text transformer

Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020

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WikiAsp: A dataset for multi-domain aspect-based summarization

Hiroaki Hayashi, Prashant Budania, Peng Wang, Chris Ackerson, Raj Neervannan, and Graham Neubig. 2021 · 2021

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Leveraging passage retrieval with generative models for open domain question answering

Gautier Izacard and Edouard Grave. 2021 · 2021

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Improving language models by retrieving from trillions of tokens

Sebastian Borgeaud, Arthur Mensch, Jordan Hoffmann, Trevor Cai, Eliza Rutherford, Katie Millican, George Bm Van Den Driessche, Jean-Baptiste Lespiau, Bogdan Damoc, Aidan Clark, Diego De Las Casas, Aurelia Guy, Jacob Menick, Roman Ring, Tom Hennigan, Saffron Huang, Loren Maggiore, Chris Jones, Albin Cassirer, Andy Brock, Michela Paganini, Geoffrey Irving, Oriol Vinyals, Simon Osindero, Karen Simonyan, Jack Rae, Erich Elsen, and Laurent Sifre. 2022 · 2022

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Scaling instruction-finetuned language models

Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Zhao, Yanping Huang, Andrew Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, and Jason Wei. 2022 · 2022

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Hindsight: Posterior-guided training of retrievers for improved open-ended generation

Ashwin Paranjape, Omar Khattab, Christopher Potts, Matei Zaharia, and Christopher D. Manning. 2022 · 2022

Cited alongside, same era.

Gar-meets-rag paradigm for zero-shot information retrieval

Original

Daman Arora, Anush Kini, Sayak Ray Chowdhury, Nagarajan Natarajan, Gaurav Sinha, and Amit Sharma. 2023 · 2023

Cited alongside, same era.

Active retrieval augmented generation

Zhengbao Jiang, Frank Xu, Luyu Gao, Zhiqing Sun, Qian Liu, Jane Dwivedi-Yu, Yiming Yang, Jamie Callan, and Graham Neubig. 2023 · 2023

Cited alongside, same era.

Decomposed prompting: A modular approach for solving complex tasks

Original

Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, and Ashish Sabharwal. 2023 · 2023

Cited alongside, same era.

Ra-dit: Retrieval-augmented dual instruction tuning

Original

C-pack: Packaged resources to advance general chinese embedding

Original

Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff. 2023 · 2023

Later among the works it cites.

Recomp: Improving retrieval-augmented lms with compression and selective augmentation

Original

Fangyuan Xu, Weijia Shi, and Eunsol Choi. 2023 · 2023

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React: Synergizing reasoning and acting in language models

Original

Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2023 · 2023

Later among the works it cites.

Augmentation-adapted retriever improves generalization of language models as generic plug-in

Zichun Yu, Chenyan Xiong, Shi Yu, and Zhiyuan Liu. 2023 · 2023

Later among the works it cites.

Self-RAG: Learning to retrieve, generate, and critique through self-reflection