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Retrieval Augmented Generation (RAG) frameworks have shown significant promise in leveraging external knowledge to enhance the performance of large language models (LLMs).
Openie6: Iterative grid labeling and coordination analysis for open information extraction
Keshav Kolluru, Vaibhav Adlakha, Samarth Aggarwal, Soumen Chakrabarti, and 1 others. 2020 · 2010
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Multilevel text alignment with cross-document attention
Xuhui Zhou, Nikolaos Pappas, and Noah A Smith. 2020 · 2010
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The acl anthology network corpus
Dragomir R Radev, Pradeep Muthukrishnan, Vahed Qazvinian, and Amjad Abu-Jbara. 2013 · 2013
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Content-based citation recommendation
Chandra Bhagavatula, Sergey Feldman, Russell Power, and Waleed Ammar. 2018 · 2018
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Retrieval augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Mingwei Chang. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick SH Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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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, and 1 others. 2020 · 2020
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Competency problems: On finding and removing artifacts in language data
Matt Gardner, William Merrill, Jesse Dodge, Matthew E Peters, Alexis Ross, Sameer Singh, and Noah Smith. 2021 · 2021
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Online learning: A comprehensive survey
Steven CH Hoi, Doyen Sahoo, Jing Lu, and Peilin Zhao. 2021 · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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LlamaIndex
Jerry Liu. 2022 · 2022
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Mteb: Massive text embedding benchmark
Niklas Muennighoff, Nouamane Tazi, Loïc Magne, and Nils Reimers. 2022 · 2022
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Self-rag: Learning to retrieve, generate, and critique through self-reflection
Akari Asai, Zeqiu Wu, Yizhong Wang, Avirup Sil, and Hannaneh Hajishirzi. 2023 · 2023
Cited alongside, same era.
Retrieval-augmented generation for large language models: A survey
Yunfan Gao, Yun Xiong, Xinyu Gao, Kangxiang Jia, Jinliu Pan, Yuxi Bi, Yi Dai, Jiawei Sun, and Haofen Wang. 2023 · 2023
Cited alongside, same era.
Continual pre-training of language models
Zixuan Ke, Yijia Shao, Haowei Lin, Tatsuya Konishi, Gyuhak Kim, and Bing Liu. 2023 · 2023
Cited alongside, same era.
Towards general text embeddings with multi-stage contrastive learning
Zehan Li, Xin Zhang, Yanzhao Zhang, Dingkun Long, Pengjun Xie, and Meishan Zhang. 2023 · 2023
Cited alongside, same era.
A survey on rag meeting llms: Towards retrieval-augmented large language models
Wenqi Fan, Yujuan Ding, Liangbo Ning, Shijie Wang, Hengyun Li, Dawei Yin, Tat-Seng Chua, and Qing Li. 2024 · 2024
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Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Alex Vaughan, and 1 others. 2024 · 2024
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Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, and 1 others. 2024 · 2024
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Online training of large language models: Learn while chatting
Juhao Liang, Ziwei Wang, Zhuoheng Ma, Jianquan Li, Zhiyi Zhang, Xiangbo Wu, and Benyou Wang. 2024 · 2024
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Pingchuan Ma, Rui Ding, Shuai Wang, Shi Han, and Dongmei Zhang. 2023 · 2023
Cited alongside, same era.
Zero-and few-shots knowledge graph triplet extraction with large language models
Andrea Papaluca, Daniel Krefl, Sergio Mendez Rodriguez, Artem Lensky, and Hanna Suominen. 2023 · 2023
Cited alongside, same era.
Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy
Zhihong Shao, Yeyun Gong, Yelong Shen, Minlie Huang, Nan Duan, and Weizhu Chen. 2023 · 2023
Cited alongside, same era.
Revisiting relation extraction in the era of large language models
Somin Wadhwa, Silvio Amir, and Byron C Wallace. 2023 · 2023
Cited alongside, same era.
Insight miner: A large-scale multimodal model for insight mining from time series
Yunkai Zhang, Yawen Zhang, Ming Zheng, Kezhen Chen, Chongyang Gao, Ruian Ge, Siyuan Teng, Amine Jelloul, Jinmeng Rao, Xiaoyuan Guo, and 1 others. 2023 · 2023
Cited alongside, same era.
Mindful-rag: A study of points of failure in retrieval augmented generation
Garima Agrawal, Tharindu Kumarage, Zeyad Alghamdi, and Huan Liu. 2024 · 2024
Cited alongside, same era.
Seven failure points when engineering a retrieval augmented generation system
Scott Barnett, Stefanus Kurniawan, Srikanth Thudumu, Zach Brannelly, and Mohamed Abdelrazek. 2024 · 2024
Cited alongside, same era.
Lora learns less and forgets less
Dan Biderman, Jacob Portes, Jose Javier Gonzalez Ortiz, Mansheej Paul, Philip Greengard, Connor Jennings, Daniel King, Sam Havens, Vitaliy Chiley, Jonathan Frankle, and 1 others. 2024 · 2024
Cited alongside, same era.
Umair Muhammad, Tangina Sultana, and Young Koo Lee. 2024 · 2024
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From text to insight: large language models for materials science data extraction
Mara Schilling-Wilhelmi, Martiño Ríos-García, Sherjeel Shabih, María Victoria Gil, Santiago Miret, Christoph T Koch, José A Márquez, and Kevin Maik Jablonka. 2024 · 2024
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Fei Wang, Xingchen Wan, Ruoxi Sun, Jiefeng Chen, and Sercan Ö Arık. 2024 · 2024
Later among the works it cites.
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, and 1 others. 2025 · 2025
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Nolima: Long-context evaluation beyond literal matching
Ali Modarressi, Hanieh Deilamsalehy, Franck Dernoncourt, Trung Bui, Ryan A Rossi, Seunghyun Yoon, and Hinrich Schütze. 2025 · 2025
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Openai o3-mini system card
OpenAI. 2025 · 2025
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Pouya Pezeshkpour and Estevam Hruschka. 2025 · 2025
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