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Large Language Models (LLMs) have quickly become an invaluable assistant for a variety of tasks.
Personalized response generation via generative split memory network
Yuwei Wu, Xuezhe Ma, and Diyi Yang. 2021 · 1970
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A learning algorithm for continually running fully recurrent neural networks
Ronald J Williams and David Zipser. 1989 · 1989
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On the form of forgetting
John T Wixted and Ebbe B Ebbesen. 1991 · 1991
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Okapi at trec-3
Stephen E Robertson, Steve Walker, Susan Jones, Micheline M Hancock-Beaulieu, Mike Gatford, et al. 1995 · 1995
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A fast learning algorithm for deep belief nets
Geoffrey E Hinton, Simon Osindero, and Yee-Whye Teh. 2006 · 2006
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Adam: A method for stochastic optimization
Diederik P Kingma. 2014 · 2014
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Two are better than one: An ensemble of retrieval-and generation-based dialog systems
Yiping Song, Rui Yan, Xiang Li, Dongyan Zhao, and Ming Zhang. 2016 · 2016
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018
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Social IQa: Commonsense reasoning about social interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan Le Bras, and Yejin Choi. 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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Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi. 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, et al. 2020 · 2020
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Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano. 2020 · 2020
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 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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How should ai systems talk to users when collecting their personal information? effects of role framing and self-referencing on human-ai interaction
Mengqi Liao and S Shyam Sundar. 2021 · 2021
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K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuanjing Huang, Jianshu Ji, Guihong Cao, Daxin Jiang, and Ming Zhou. 2021 · 2021
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Knowprompt: Knowledge-aware prompt-tuning with synergistic optimization for relation extraction
Xiang Chen, Ningyu Zhang, Xin Xie, Shumin Deng, Yunzhi Yao, Chuanqi Tan, Fei Huang, Luo Si, and Huajun Chen. 2022 · 2022
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Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave. 2022 · 2022
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Personalized reward learning with interaction-grounded learning (igl)
Jessica Maghakian, Paul Mineiro, Kishan Panaganti, Mark Rucker, Akanksha Saran, and Cheng Tan. 2022 · 2022
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Everyone deserves a reward: Learning customized human preferences
Pengyu Cheng, Jiawen Xie, Ke Bai, Yong Dai, and Nan Du. 2023 · 2023
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Revisiting the knowledge injection frameworks
Peng Fu, Yiming Zhang, Haobo Wang, Weikang Qiu, and Junbo Zhao. 2023 · 2023
Cited alongside, same era.
Learning retrieval augmentation for personalized dialogue generation
Qiushi Huang, Shuai Fu, Xubo Liu, Wenwu Wang, Tom Ko, Yu Zhang, and Lilian Tang. 2023 · 2023
Cited alongside, same era.
Personalized soups: Personalized large language model alignment via post-hoc parameter merging
Joel Jang, Seungone Kim, Bill Yuchen Lin, Yizhong Wang, Jack Hessel, Luke Zettlemoyer, Hannaneh Hajishirzi, Yejin Choi, and Prithviraj Ammanabrolu. 2023 · 2023
Cited alongside, same era.
Openassistant conversations - democratizing large language model alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi Rui Tam, Keith Stevens, Abdullah Barhoum, Duc Nguyen, Oliver Stanley, Richárd Nagyfi, Shahul ES, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, and Alexander Mattick. 2023 · 2023
Cited alongside, same era.
Teach llms to personalize–an approach inspired by writing education
Scale matters: Large language models with billions (rather than millions) of parameters better match neural representations of natural language
Zhuoqiao Hong, Haocheng Wang, Zaid Zada, Harshvardhan Gazula, David Turner, Bobbi Aubrey, Leonard Niekerken, Werner Doyle, Sasha Devore, Patricia Dugan, et al. 2024 · 2024
Closest in time.
Selective prompting tuning for personalized conversations with LLMs
Qiushi Huang, Xubo Liu, Tom Ko, Bo Wu, Wenwu Wang, Yu Zhang, and Lilian Tang. 2024 · 2024
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Longlamp: A benchmark for personalized long-form text generation
Ishita Kumar, Snigdha Viswanathan, Sushrita Yerra, Alireza Salemi, Ryan A Rossi, Franck Dernoncourt, Hanieh Deilamsalehy, Xiang Chen, Ruiyi Zhang, Shubham Agarwal, et al. 2024 · 2024
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Learning to rewrite prompts for personalized text generation
Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, and Michael Bendersky. 2024a · 2024
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Reinforced prompt personalization for recommendation with large language models
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Cheng Li, Mingyang Zhang, Qiaozhu Mei, Yaqing Wang, Spurthi Amba Hombaiah, Yi Liang, and Michael Bendersky. 2023 · 2023
Cited alongside, same era.
Memochat: Tuning llms to use memos for consistent long-range open-domain conversation
Junru Lu, Siyu An, Mingbao Lin, Gabriele Pergola, Yulan He, Di Yin, Xing Sun, and Yunsheng Wu. 2023 · 2023
Cited alongside, same era.
An empirical study of catastrophic forgetting in large language models during continual fine-tuning
Yun Luo, Zhen Yang, Fandong Meng, Yafu Li, Jie Zhou, and Yue Zhang. 2023 · 2023
Cited alongside, same era.
Knowledge injection to counter large language model (llm) hallucination
Ariana Martino, Michael Iannelli, and Coleen Truong. 2023 · 2023
Cited alongside, same era.
Membership inference attacks against language models via neighbourhood comparison
Justus Mattern, Fatemehsadat Mireshghallah, Zhijing Jin, Bernhard Schoelkopf, Mrinmaya Sachan, and Taylor Berg-Kirkpatrick. 2023 · 2023
Cited alongside, same era.
Pearl: Personalizing large language model writing assistants with generation-calibrated retrievers
Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, and Tara Safavi. 2023 · 2023
Cited alongside, same era.
Fine-tuning or retrieval? comparing knowledge injection in llms
Oded Ovadia, Menachem Brief, Moshik Mishaeli, and Oren Elisha. 2023 · 2023
Cited alongside, same era.
Integrating summarization and retrieval for enhanced personalization via large language models
Chris Richardson, Yao Zhang, Kellen Gillespie, Sudipta Kar, Arshdeep Singh, Zeynab Raeesy, Omar Zia Khan, and Abhinav Sethy. 2023 · 2023
Cited alongside, same era.
Wenyu Mao, Jiancan Wu, Weijian Chen, Chongming Gao, Xiang Wang, and Xiangnan He. 2024 · 2024
Closest in time.
Injecting new knowledge into large language models via supervised fine-tuning
Nick Mecklenburg, Yiyou Lin, Xiaoxiao Li, Daniel Holstein, Leonardo Nunes, Sara Malvar, Bruno Silva, Ranveer Chandra, Vijay Aski, Pavan Kumar Reddy Yannam, et al. 2024 · 2024
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RAGs to style: Personalizing LLMs with style embeddings
Abhiman Neelakanteswara, Shreyas Chaudhari, and Hamed Zamani. 2024 · 2024
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Principled rlhf from heterogeneous feedback via personalization and preference aggregation
Chanwoo Park, Mingyang Liu, Kaiqing Zhang, and Asuman Ozdaglar. 2024 · 2024
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Personalizing reinforcement learning from human feedback with variational preference learning
Sriyash Poddar, Yanming Wan, Hamish Ivison, Abhishek Gupta, and Natasha Jaques. 2024 · 2024
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Pmg: Personalized multimodal generation with large language models
Xiaoteng Shen, Rui Zhang, Xiaoyan Zhao, Jieming Zhu, and Xi Xiao. 2024 · 2024
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Knowledge graph tuning: Real-time large language model personalization based on human feedback
Jingwei Sun, Zhixu Du, and Yiran Chen. 2024 · 2024
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Democratizing large language models via personalized parameter-efficient fine-tuning
Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, Zheyuan Liu, Bing Yin, and Meng Jiang. 2024 · 2024
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Michelangelo: Long context evaluations beyond haystacks via latent structure queries
Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, et al. 2024 · 2024
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Unims-rag: A unified multi-source retrieval-augmented generation for personalized dialogue systems
Hongru Wang, Wenyu Huang, Yang Deng, Rui Wang, Zezhong Wang, Yufei Wang, Fei Mi, Jeff Z Pan, and Kam-Fai Wong. 2024 · 2024
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Llms are biased teachers: Evaluating llm bias in personalized education
Iain Weissburg, Sathvika Anand, Sharon Levy, and Haewon Jeong. 2024 · 2024
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Personalized large language models
Stanisław Woźniak, Bartłomiej Koptyra, Arkadiusz Janz, Przemysław Kazienko, and Jan Kocoń. 2024 · 2024
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Personarag: Enhancing retrieval-augmented generation systems with user-centric agents
Saber Zerhoudi and Michael Granitzer. 2024 · 2024
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LLM-based medical assistant personalization with short- and long-term memory coordination
Kai Zhang, Yangyang Kang, Fubang Zhao, and Xiaozhong Liu. 2024a · 2024
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Cognitive personalized search integrating large language models with an efficient memory mechanism
Yujia Zhou, Qiannan Zhu, Jiajie Jin, and Zhicheng Dou. 2024 · 2024
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An enhanced knowledge injection model for commonsense generation
Zhihao Fan, Yeyun Gong, Zhongyu Wei, Siyuan Wang, Yameng Huang, Jian Jiao, Xuan-Jing Huang, Nan Duan, and Ruofei Zhang. 2020 · 2025
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