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Personalization of Large Language Models (LLMs) has recently become increasingly important with a wide range of applications.
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A large-scale evaluation and analysis of personalized search strategies
Zhicheng Dou, Ruihua Song, and Ji-Rong Wen · 2007
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Building user profiles for recommender systems from incomplete preference relations
Luis G Perez, Manuel Barranco, and Luis Martinez · 2007
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Collaborative filtering recommender systems
J Ben Schafer, Dan Frankowski, Jon Herlocker, and Shilad Sen · 2007
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Web search personalization with ontological user profiles
Ahu Sieg, Bamshad Mobasher, and Robin Burke · 2007
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Addressing cold-start problem in recommendation systems
Xuan Nhat Lam, Thuc Vu, Trong Duc Le, and Anh Duc Duong · 2008
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Pairwise preference regression for cold-start recommendation
Seung-Taek Park and Wei Chu · 2009
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Towards query log based personalization using topic models
Mark J Carman, Fabio Crestani, Morgan Harvey, and Mark Baillie · 2010
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On-demand feature recommendations derived from mining public product descriptions
Horatiu Dumitru, Marek Gibiec, Negar Hariri, Jane Cleland-Huang, Bamshad Mobasher, Carlos Castro-Herrera, and Mehdi Mirakhorli · 2011
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The filter bubble: How the new personalized web is changing what we read and how we think
Eli Pariser · 2011
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Understanding and predicting personal navigation
Jaime Teevan, Daniel J Liebling, and Gayathri Ravichandran Geetha · 2011
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Modeling the impact of short-and long-term behavior on search personalization
Paul N Bennett, Ryen W White, Wei Chu, Susan T Dumais, Peter Bailey, Fedor Borisyuk, and Xiaoyuan Cui · 2012
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Building user profiles from topic models for personalised search
Morgan Harvey, Fabio Crestani, and Mark J Carman · 2013
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Enhancing personalized search by mining and modeling task behavior
Ryen W White, Wei Chu, Ahmed Hassan, Xiaodong He, Yang Song, and Hongning Wang · 2013
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Personalized document re-ranking based on bayesian probabilistic matrix factorization
Fei Cai, Shangsong Liang, and Maarten De Rijke · 2014
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Sentiment analysis algorithms and applications: A survey
Walaa Medhat, Ahmed Hassan, and Hoda Korashy · 2014
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Adapting deep ranknet for personalized search
Yang Song, Hongning Wang, and Xiaodong He · 2014
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Improving search personalisation with dynamic group formation
Thanh Tien Vu, Dawei Song, Alistair Willis, Son Ngoc Tran, and Jingfei Li · 2014
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Yelp dataset challenge, 2014
Yelp · 2014
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The movielens datasets: History and context
F Maxwell Harper and Joseph A Konstan · 2015
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Session-based recommendations with recurrent neural networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk · 2015
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Trust region policy optimization
John Schulman, Sergey Levine, Pieter Abbeel, Michael Jordan, and Philipp Moritz · 2015
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Temporal latent topic user profiles for search personalisation
Thanh Vu, Alistair Willis, Son N Tran, and Dawei Song · 2015
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Alignment for advanced machine learning systems
Jessica Taylor, Eliezer Yudkowsky, Patrick LaVictoire, and Andrew Critch · 2016
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Bias and Fairness in Large Language Models: A Survey
Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, Md Mehrab Tanjim, Sungchul Kim, Franck Dernoncourt, Tong Yu, Ruiyi Zhang, and Nesreen K. Ahmed · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Collaborative filtering and deep learning based recommendation system for cold start items
Jian Wei, Jianhua He, Kai Chen, Yi Zhou, and Zuoyin Tang · 2017
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Can Large Language Models Transform Computational Social Science?
Caleb Ziems, William Held, Omar Shaikh, Jiaao Chen, Zhehao Zhang, and Diyi Yang · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Political discourse on social media: Echo chambers, gatekeepers, and the price of bipartisanship
Kiran Garimella, Gianmarco De Francisci Morales, Aristides Gionis, and Michael Mathioudakis · 2018
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Training millions of personalized dialogue agents
Pierre-Emmanuel Mazaré, Samuel Humeau, Martin Raison, and Antoine Bordes · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Finbert: Financial sentiment analysis with pre-trained language models
Dogu Araci · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou · 2019
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Melu: Meta-learned user preference estimator for cold-start recommendation
Hoyeop Lee, Jinbae Im, Seongwon Jang, Hyunsouk Cho, and Sehee Chung · 2019
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer · 2019
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From zero-shot learning to cold-start recommendation
Jingjing Li, Mengmeng Jing, Ke Lu, Lei Zhu, Yang Yang, and Zi Huang · 2019
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Towards controllable and personalized review generation
Pan Li and Alexander Tuzhilin · 2019
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Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov · 2019
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Generating personalized recipes from historical user preferences
Bodhisattwa Prasad Majumder, Shuyang Li, Jianmo Ni, and Julian McAuley · 2019
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Justifying recommendations using distantly-labeled reviews and fine-grained aspects
Jianmo Ni, Jiacheng Li, and Julian McAuley · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych · 2019
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Computational Social Roles
Diyi Yang · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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The second conversational intelligence challenge (convai2)
Emily Dinan, Varvara Logacheva, Valentin Malykh, Alexander Miller, Kurt Shuster, Jack Urbanek, Douwe Kiela, Arthur Szlam, Iulian Serban, Ryan Lowe, et al · 2020
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Artificial intelligence, values, and alignment
Iason Gabriel · 2020
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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A Smith · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih · 2020
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Survey of personalization techniques for federated learning
Viraj Kulkarni, Milind Kulkarni, and Aniruddha Pant · 2020
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Generate neural template explanations for recommendation
Lei Li, Yongfeng Zhang, and Li Chen · 2020
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Gender bias in neural natural language processing
Kaiji Lu, Piotr Mardziel, Fangjing Wu, Preetam Amancharla, and Anupam Datta · 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
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Mpnet: Masked and permuted pre-training for language understanding
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu · 2020
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Mind: A large-scale dataset for news recommendation
Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, Chuhan Wu, Tao Qi, Jianxun Lian, Danyang Liu, Xing Xie, Jianfeng Gao, Winnie Wu, et al · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi · 2020
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Predicting efficiency/effectiveness trade-offs for dense vs. sparse retrieval strategy selection
Negar Arabzadeh, Xinyi Yan, and Charles L. A. Clarke · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al · 2021
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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Glm: General language model pretraining with autoregressive blank infilling
Zhengxiao Du, Yujie Qian, Xiao Liu, Ming Ding, Jiezhong Qiu, Zhilin Yang, and Jie Tang · 2021
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Balancing out bias: Achieving fairness through balanced training
Xudong Han, Timothy Baldwin, and Trevor Cohn · 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
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Leveraging passage retrieval with generative models for open domain question answering
Gautier Izacard and Edouard Grave · 2021
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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 · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant · 2021
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A survey on representation learning for user modeling
Sheng Li and Handong Zhao · 2021
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Ditto: Fair and robust federated learning through personalization
Tian Li, Shengyuan Hu, Ahmad Beirami, and Virginia Smith · 2021
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Mitigating political bias in language models through reinforced calibration
Ruibo Liu, Chenyan Jia, Jason Wei, Guangxuan Xu, Lili Wang, and Soroush Vosoughi · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al · 2021
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Sentence-t5: Scalable sentence encoders from pre-trained text-to-text models
Jianmo Ni, Gustavo Hernandez Abrego, Noah Constant, Ji Ma, Keith B Hall, Daniel Cer, and Yinfei Yang · 2021
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Retrieval augmentation reduces hallucination in conversation
Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, and Jason Weston · 2021
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Towards user-centric text-to-text generation: A survey
Diyi Yang and Lucie Flek · 2021
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Group based personalized search by integrating search behaviour and friend network
Yujia Zhou, Zhicheng Dou, Bingzheng Wei, Ruobing Xie, and Ji-Rong Wen · 2021
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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Ew-tune: A framework for privately fine-tuning large language models with differential privacy
Rouzbeh Behnia, Mohammadreza Reza Ebrahimi, Jason Pacheco, and Balaji Padmanabhan · 2022
Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al · 2023
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What should data science education do with large language models
Xinming Tu, James Zou, Weijie J Su, and Linjun Zhang · 2023
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Accuracy is not enough: Evaluating personalization in summarizers
Rahul Vansh, Darsh Rank, Sourish Dasgupta, and Tanmoy Chakraborty · 2023
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Are personalized stochastic parrots more dangerous? evaluating persona biases in dialogue systems
Yixin Wan, Jieyu Zhao, Nanyun Peng, Kai-Wei Chang, and Aman Chadha · 2023
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Zero-shot next-item recommendation using large pretrained language models
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A personalized dialogue generator with implicit user persona detection
Itsugun Cho, Dongyang Wang, Ryota Takahashi, and Hiroaki Saito · 2022
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Retrieval-augmented generative question answering for event argument extraction
Xinya Du and Heng Ji · 2022
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Understanding dataset difficulty with 𝒱 \mathcal{V} -usable information
Kawin Ethayarajh, Yejin Choi, and Swabha Swayamdipta · 2022
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An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned
Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, et al · 2022
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Seungju Han, Beomsu Kim, Jin Yong Yoo, Seokjun Seo, Sangbum Kim, Enkhbayar Erdenee, and Buru Chang · 2022
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Estimating the personality of white-box language models
Saketh Reddy Karra, Son The Nguyen, and Theja Tulabandhula · 2022
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Lei Wang and Ee-Peng Lim · 2023
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Rose E Wang and Dorottya Demszky · 2023
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A prompt pattern catalog to enhance prompt engineering with chatgpt
Jules White, Quchen Fu, Sam Hays, Michael Sandborn, Carlos Olea, Henry Gilbert, Ashraf Elnashar, Jesse Spencer-Smith, and Douglas C Schmidt · 2023
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Towards open-world recommendation with knowledge augmentation from large language models
Yunjia Xi, Weiwen Liu, Jianghao Lin, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, and Yong Yu · 2023
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Expertprompting: Instructing large language models to be distinguished experts
Benfeng Xu, An Yang, Junyang Lin, Quan Wang, Chang Zhou, Yongdong Zhang, and Zhendong Mao · 2023
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Palr: Personalization aware llms for recommendation, 2023
Fan Yang, Zheng Chen, Ziyan Jiang, Eunah Cho, Xiaojiang Huang, and Yanbin Lu · 2023
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Heterogeneous knowledge fusion: A novel approach for personalized recommendation via llm
Bin Yin, Junjie Xie, Yu Qin, Zixiang Ding, Zhichao Feng, Xiang Li, and Wei Lin · 2023
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Large language models for healthcare data augmentation: An example on patient-trial matching
Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, and Xia Hu · 2023
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Disc-lawllm: Fine-tuning large language models for intelligent legal services
Shengbin Yue, Wei Chen, Siyuan Wang, Bingxuan Li, Chenchen Shen, Shujun Liu, Yuxuan Zhou, Yao Xiao, Song Yun, Wei Lin, et al · 2023
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A personalized dense retrieval framework for unified information access
Hansi Zeng, Surya Kallumadi, Zaid Alibadi, Rodrigo Nogueira, and Hamed Zamani · 2023
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Mitigating biases in hate speech detection from a causal perspective
Zhehao Zhang, Jiaao Chen, and Diyi Yang · 2023
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A survey of large language models
Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, et al · 2023
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Characterglm: Customizing chinese conversational ai characters with large language models
Jinfeng Zhou, Zhuang Chen, Dazhen Wan, Bosi Wen, Yi Song, Jifan Yu, Yongkang Huang, Libiao Peng, Jiaming Yang, Xiyao Xiao, et al · 2023
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Multi-VALUE: A framework for cross-dialectal English NLP
Caleb Ziems, William Held, Jingfeng Yang, Jwala Dhamala, Rahul Gupta, and Diyi Yang · 2023
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Knowledge-infused llm-powered conversational health agent: A case study for diabetes patients
Mahyar Abbasian, Zhongqi Yang, Elahe Khatibi, Pengfei Zhang, Nitish Nagesh, Iman Azimi, Ramesh Jain, and Amir M Rahmani · 2024
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Llms instead of human judges? a large scale empirical study across 20 nlp evaluation tasks
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Leveraging the potential of large language models in education through playful and game-based learning
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Identity decoupling for multi-subject personalization of text-to-image models
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