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Users can divulge sensitive information to proprietary LLM providers, raising significant privacy concerns.
Training production language models without memorizing user data
Swaroop Ramaswamy, Om Thakkar, Rajiv Mathews, Galen Andrew, H Brendan McMahan, and Françoise Beaufays. 2020 · 2009
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A differentially private text perturbation method using a regularized mahalanobis metric
Zekun Xu, Abhinav Aggarwal, Oluwaseyi Feyisetan, and Nathanael Teissier. 2020 · 2010
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Privacy-and utility-preserving textual analysis via calibrated multivariate perturbations
Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, and Tom Diethe. 2020 · 2020
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Extracting training data from large language models
Nicholas Carlini, Florian Tramer, Eric Wallace, Matthew Jagielski, Ariel Herbert-Voss, Katherine Lee, Adam Roberts, Tom Brown, Dawn Song, Ulfar Erlingsson, et al. 2021 · 2021
Earlier work this paper cites.
The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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What does it mean for a language model to preserve privacy?
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, and Florian Tramèr. 2022 · 2022
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Differentially private decoding in large language models
Jimit Majmudar, Christophe Dupuy, Charith Peris, Sami Smaili, Rahul Gupta, and Richard Zemel. 2022 · 2022
Earlier work this paper cites.
Just fine-tune twice: Selective differential privacy for large language models
Weiyan Shi, Ryan Shea, Si Chen, Chiyuan Zhang, Ruoxi Jia, and Zhou Yu. 2022 · 2022
Earlier work this paper cites.
Chatgpt as a therapist assistant: a suitability study
Mahshid Eshghie and Mojtaba Eshghie. 2023 · 2023
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Exploring the role of chatgpt in patient care (diagnosis and treatment) and medical research: A systematic review
Ravindra Kumar Garg, Vijeth L Urs, Akshay Anand Agarwal, Sarvesh Kumar Chaudhary, Vimal Paliwal, and Sujita Kumar Kar. 2023 · 2023
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Chatgpt outperforms crowd workers for text-annotation tasks
Fabrizio Gilardi, Meysam Alizadeh, and Maël Kubli. 2023 · 2023
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Dp-opt: Make large language model your privacy-preserving prompt engineer
Junyuan Hong, Jiachen T Wang, Chenhui Zhang, Zhangheng Li, Bo Li, and Zhangyang Wang. 2023 · 2023
Earlier work this paper cites.
AQ Jiang, A Sablayrolles, A Mensch, C Bamford, DS Chaplot, D de las Casas, F Bressand, G Lengyel, G Lample, L Saulnier, et al. 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
Cited alongside, same era.
Rlaif: Scaling reinforcement learning from human feedback with ai feedback
Harrison Lee, Samrat Phatale, Hassan Mansoor, Thomas Mesnard, Johan Ferret, Kellie Lu, Colton Bishop, Ethan Hall, Victor Carbune, Abhinav Rastogi, et al. 2023 · 2023
Cited alongside, same era.
Personalized tutoring: Chatgpt as a virtual tutor for personalized learning experiences
Fernando Antonio Flores Limo, David Raul Hurtado Tiza, Maribel Mamani Roque, Edward Espinoza Herrera, José Patricio Muñoz Murillo, Jorge Jinchuña Huallpa, Victor Andre Ariza Flores, Alejandro Guadalupe Rincón Castillo, Percy Fritz Puga Peña, Christian Paolo Martel Carranza, et al. 2023 · 2023
Cited alongside, same era.
Direct language model alignment from online ai feedback
Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu, Misha Khalman, Felipe Llinares, Alexandre Rame, Thomas Mesnard, Yao Zhao, Bilal Piot, et al. 2024 · 2024
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Chatgpt rates natural language explanation quality like humans: But on which scales?
Fan Huang, Haewoon Kwak, Kunwoo Park, and Jisun An. 2024 · 2024
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Data exposure from llm apps: An in-depth investigation of openai’s gpts
Evin Jaff, Yuhao Wu, Ning Zhang, and Umar Iqbal. 2024 · 2024
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Propile: Probing privacy leakage in large language models
Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, and Seong Joon Oh. 2024 · 2024
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Trust no bot: Discovering personal disclosures in human-llm conversations in the wild
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Analyzing leakage of personally identifiable information in language models
Nils Lukas, Ahmed Salem, Robert Sim, Shruti Tople, Lukas Wutschitz, and Santiago Zanella-Béguelin. 2023 · 2023
Cited alongside, same era.
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou, Yulia Tsvetkov, Maarten Sap, Reza Shokri, and Yejin Choi. 2023 · 2023
Cited alongside, same era.
Beyond memorization: Violating privacy via inference with large language models
Robin Staab, Mark Vero, Mislav Balunović, and Martin Vechev. 2023 · 2023
Cited alongside, same era.
Assessing the performance of chatgpt in answering questions regarding cirrhosis and hepatocellular carcinoma
Yee Hui Yeo, Jamil S Samaan, Wee Han Ng, Peng-Sheng Ting, Hirsh Trivedi, Aarshi Vipani, Walid Ayoub, Ju Dong Yang, Omer Liran, Brennan Spiegel, et al. 2023 · 2023
Cited alongside, same era.
Red teaming chatgpt via jailbreaking: Bias, robustness, reliability and toxicity
Terry Yue Zhuo, Yujin Huang, Chunyang Chen, and Zhenchang Xing. 2023 · 2023
Cited alongside, same era.
Evaluating privacy leakage and memorization attacks on large language models (llms) in generative ai applications
Harshvardhan Aditya, Siddansh Chawla, Gunika Dhingra, Parijat Rai, Saumil Sood, Tanmay Singh, Zeba Mohsin Wase, Arshdeep Bahga, and Vijay K Madisetti. 2024 · 2024
Cited alongside, same era.
Security and privacy challenges of large language models: A survey
Badhan Chandra Das, M Hadi Amini, and Yanzhao Wu. 2024 · 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.
Niloofar Mireshghallah, Maria Antoniak, Yash More, Yejin Choi, and Golnoosh Farnadi. 2024 · 2024
Closest in time.
Optimizing instructions and demonstrations for multi-stage language model programs
Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, David Broman, Christopher Potts, Matei Zaharia, and Omar Khattab. 2024 · 2024
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Privacylens: Evaluating privacy norm awareness of language models in action
Yijia Shao, Tianshi Li, Weiyan Shi, Yanchen Liu, and Diyi Yang. 2024 · 2024
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De-identifying student personally identifying information with gpt-4
Shreya Singhal, Andres Felipe Zambrano, Maciej Pankiewicz, Xiner Liu, Chelsea Porter, and Ryan S Baker. 2024 · 2024
Closest in time.
Joint prompt optimization of stacked llms using variational inference
Alessandro Sordoni, Eric Yuan, Marc-Alexandre Côté, Matheus Pereira, Adam Trischler, Ziang Xiao, Arian Hosseini, Friederike Niedtner, and Nicolas Le Roux. 2024 · 2024
Closest in time.
Ziqian Zeng, Jianwei Wang, Zhengdong Lu, Huiping Zhuang, and Cen Chen. 2024 · 2024
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Privacyasst: Safeguarding user privacy in tool-using large language model agents
Xinyu Zhang, Huiyu Xu, Zhongjie Ba, Zhibo Wang, Yuan Hong, Jian Liu, Zhan Qin, and Kui Ren. 2024 · 2024
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Wildchat: 1m chatgpt interaction logs in the wild
Wenting Zhao, Xiang Ren, Jack Hessel, Claire Cardie, Yejin Choi, and Yuntian Deng. 2024 · 2024
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