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Personalizing Large Language Models (LLMs) has become a critical step in facilitating their widespread application to enhance individual life experiences.
A lexical, syntactic, and semantic perspective for understanding style in text
Gaurav Verma and Balaji Vasan Srinivasan. 2019 · 1909
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Some methods for classification and analysis of multivariate observations
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Abnormality as a positive characteristic: The development and validation of a scale measuring need for uniqueness
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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METEOR: an automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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The probabilistic relevance framework: BM25 and beyond
Stephen E. Robertson and Hugo Zaragoza. 2009 · 2009
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You like what i like, but i don’t like what you like: Uniqueness motivations in product preferences
Caglar Irmak, Beth Vallen, and Sankar Sen. 2010 · 2010
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Uniqueness: The human pursuit of difference
Charles R Snyder and Howard L Fromkin. 2012 · 2012
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Detecting factual and non-factual content in news articles
Ishan Sahu and Debapriyo Majumdar. 2017 · 2017
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Justifying recommendations using distantly-labeled reviews and fine-grained aspects
Jianmo Ni, Jiacheng Li, and Julian McAuley. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
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Tallrec: An effective and efficient tuning framework to align large language model with recommendation
Keqin Bao, Jizhi Zhang, Yang Zhang, Wenjie Wang, Fuli Feng, and Xiangnan He. 2023 · 2023
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Large language models for user interest journeys
Konstantina Christakopoulou, Alberto Lalama, Cj Adams, Iris Qu, Yifat Amir, Samer Chucri, Pierce Vollucci, Fabio Soldo, Dina Bseiso, Sarah Scodel, et al. 2023 · 2023
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Kiana Kheiri and Hamid Karimi. 2023 · 2023
Cited alongside, same era.
Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
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G-eval: NLG evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 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.
Automated evaluation of personalized text generation using large language models
Pacar: Automated fact-checking with planning and customized action reasoning using large language models
Xiaoyan Zhao, Lingzhi Wang, Zhanghao Wang, Hong Cheng, Rui Zhang, and Kam-Fai Wong. 2024b · 2024
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Harnessing large language models for text-rich sequential recommendation
Zhi Zheng, Wenshuo Chao, Zhaopeng Qiu, Hengshu Zhu, and Hui Xiong. 2024 · 2024
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HYDRA: model factorization framework for black-box LLM personalization
Yuchen Zhuang, Haotian Sun, Yue Yu, Rushi Qiang, Qifan Wang, Chao Zhang, and Bo Dai. 2024 · 2024
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Personalized graph-based retrieval for large language models
Steven Au, Cameron J Dimacali, Ojasmitha Pedirappagari, Namyong Park, Franck Dernoncourt, Yu Wang, Nikos Kanakaris, Hanieh Deilamsalehy, Ryan A Rossi, and Nesreen K Ahmed. 2025 · 2025
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Large language models empowered personalized web agents
Hongru Cai, Yongqi Li, Wenjie Wang, Fengbin Zhu, Xiaoyu Shen, Wenjie Li, and Tat-Seng Chua. 2025 · 2025
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Yaqing Wang, Jiepu Jiang, Mingyang Zhang, Cheng Li, Yi Liang, Qiaozhu Mei, and Michael Bendersky. 2023 · 2023
Cited alongside, same era.
Decoding matters: Addressing amplification bias and homogeneity issue in recommendations for large language models
Keqin Bao, Jizhi Zhang, Yang Zhang, Xinyue Huo, Chong Chen, and Fuli Feng. 2024 · 2024
Cited alongside, same era.
On softmax direct preference optimization for recommendation
Yuxin Chen, Junfei Tan, An Zhang, Zhengyi Yang, Leheng Sheng, Enzhi Zhang, Xiang Wang, and Tat-Seng Chua. 2024b · 2024
Cited alongside, same era.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
Cited alongside, same era.
Customizing language model responses with contrastive in-context learning
Xiang Gao and Kamalika Das. 2024 · 2024
Cited alongside, same era.
Bridging language and items for retrieval and recommendation
Yupeng Hou, Jiacheng Li, Zhankui He, An Yan, Xiusi Chen, and Julian McAuley. 2024 · 2024
Cited alongside, same era.
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
Cited alongside, same era.
Pearl: Personalizing large language model writing assistants with generation-calibrated retrievers
Sheshera Mysore, Zhuoran Lu, Mengting Wan, Longqi Yang, Bahareh Sarrafzadeh, Steve Menezes, Tina Baghaee, Emmanuel Barajas Gonzalez, Jennifer Neville, and Tara Safavi. 2024 · 2024
Cited alongside, same era.
Closest in time.
PAD: personalized alignment of llms at decoding-time
Ruizhe Chen, Xiaotian Zhang, Meng Luo, Wenhao Chai, and Zuozhu Liu. 2025 · 2025
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Dependeval: Benchmarking llms for repository dependency understanding
Junjia Du, Yadi Liu, Hongcheng Guo, Jiawei Wang, Haojian Huang, Yunyi Ni, and Zhoujun Li. 2025 · 2025
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Alphaedit: Null-space constrained knowledge editing for language models
Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Jie Shi, Xiang Wang, Xiangnan He, and Tat-Seng Chua. 2025 · 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 · 2025
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Moxin Li, Yuantao Zhang, Wenjie Wang, Wentao Shi, Zhuo Liu, Fuli Feng, and Tat-Seng Chua. 2025 · 2025
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Reasoning-enhanced self-training for long-form personalized text generation
Alireza Salemi, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, Tao Chen, Zhuowan Li, Michael Bendersky, and Hamed Zamani. 2025 · 2025
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Persona-db: Efficient large language model personalization for response prediction with collaborative data refinement
Chenkai Sun, Ke Yang, Revanth Gangi Reddy, Yi Ren Fung, Hou Pong Chan, Kevin Small, ChengXiang Zhai, and Heng Ji. 2025 · 2025
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Longmemeval: Benchmarking chat assistants on long-term interactive memory
Di Wu, Hongwei Wang, Wenhao Yu, Yuwei Zhang, Kai-Wei Chang, and Dong Yu. 2025 · 2025
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Personalized image generation with large multimodal models
Yiyan Xu, Wenjie Wang, Yang Zhang, Biao Tang, Peng Yan, Fuli Feng, and Xiangnan He. 2025a · 2025
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Do llms recognize your preferences? evaluating personalized preference following in llms
Siyan Zhao, Mingyi Hong, Yang Liu, Devamanyu Hazarika, and Kaixiang Lin. 2025a · 2025
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