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Advances in generative AI point towards a new era of personalized applications that perform diverse tasks on behalf of users.
Privacy as Contextual Integrity
Nissenbaum, H. 2004 · 2004
Earlier work this paper cites.
Privacy and contextual integrity: framework and applications
Barth, A.; Datta, A.; Mitchell, J. C.; and Nissenbaum, H. 2006 · 2006
Earlier work this paper cites.
Privacy in Context
Nissenbaum, H. 2009 · 2009
Earlier work this paper cites.
Likert scale: Explored and explained
Joshi, A.; Kale, S.; Chandel, S.; and Pal, D. K. 2015 · 2015
Earlier work this paper cites.
VACCINE: Using Contextual Integrity For Data Leakage Detection
Shvartzshnaider, Y.; Pavlinovic, Z.; Balashankar, A.; Wies, T.; Subramanian, L.; Nissenbaum, H.; and Mittal, P. 2019 · 2019
Earlier work this paper cites.
Extracting Training Data from Large Language Models
Carlini, N.; Tramer, F.; Wallace, E.; Jagielski, M.; Herbert-Voss, A.; Lee, K.; Roberts, A.; Brown, T.; Song, D.; Erlingsson, U.; Oprea, A.; and Raffel, C. 2020 · 2020
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Aquilis: Using Contextual Integrity for Privacy Protection on Mobile Devices
Kumar, A.; Braud, T.; Kwon, Y. D.; and Hui, P. 2020 · 2020
Earlier work this paper cites.
Constitutional AI: Harmlessness from AI Feedback
Bai, Y.; Kadavath, S.; Kundu, S.; Askell, A.; Kernion, J.; Jones, A.; Chen, A.; Goldie, A.; Mirhoseini, A.; McKinnon, C.; Chen, C.; Olsson, C.; Olah, C.; Hernandez, D.; Drain, D.; Ganguli, D.; Li, D.; Tran-Johnson, E.; Perez, E.; Kerr, J.; Mueller, J.; Ladish, J.; Landau, J.; Ndousse, K.; Lukosuite, K.; Lovitt, L.; Sellitto, M.; Elhage, N.; Schiefer, N.; Mercado, N.; DasSarma, N.; Lasenby, R.; Larson, R.; Ringer, S.; Johnston, S.; Kravec, S.; El Showk, S.; Fort, S.; Lanham, T.; Telleen-Lawton, T.; Conerly, T.; Henighan, T.; Hume, T.; Bowman, S. R.; Hatfield-Dodds, Z.; Mann, B.; Amodei, D.; Joseph, N.; McCandlish, S.; Brown, T.; and Kaplan, J. 2022 · 2022
Earlier work this paper cites.
Training language models to follow instructions with human feedback
Ouyang, L.; Wu, J.; Jiang, X.; Almeida, D.; Wainwright, C. L.; Mishkin, P.; Zhang, C.; Agarwal, S.; Slama, K.; Ray, A.; Schulman, J.; Hilton, J.; Kelton, F.; Miller, L. E.; Simens, M.; Askell, A.; Welinder, P.; Christiano, P.; Leike, J.; and Lowe, R. J. 2022 · 2022
Earlier work this paper cites.
Memorizing Transformers
Wu, Y.; Rabe, M. N.; Hutchins, D.; and Szegedy, C. 2022 · 2022
Cited alongside, same era.
Extending context window of large language models via positional interpolation
Chen, S.; Wong, S.; Chen, L.; and Tian, Y. 2023 · 2023
Cited alongside, same era.
Reflective linguistic programming (rlp): A stepping stone in socially-aware agi (socialagi)
Fischer, K. A. 2023 · 2023
Cited alongside, same era.
Gemini: a family of highly capable multimodal models
Gemini Team,. 2023 · 2023
Cited alongside, same era.
Memory sandbox: Transparent and interactive memory management for conversational agents
Huang, Z.; Gutierrez, S.; Kamana, H.; and MacNeil, S. 2023 · 2023
Cited alongside, same era.
Yarn: Efficient context window extension of large language models
Peng, B.; Quesnelle, J.; Fan, H.; and Shippole, E. 2023 · 2023
Later among the works it cites.
Sayplan: Grounding large language models using 3d scene graphs for scalable robot task planning
Rana, K.; Haviland, J.; Garg, S.; Abou-Chakra, J.; Reid, I.; and Suenderhauf, N. 2023 · 2023
Later among the works it cites.
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond
Yang, J.; Jin, H.; Tang, R.; Han, X.; Feng, Q.; Jiang, H.; Yin, B.; and Hu, X. 2023 · 2023
Later among the works it cites.
Air gap: Protecting privacy-conscious conversational agents
Bagdasaryan, E.; Yi, R.; Ghalebikesabi, S.; Kairouz, P.; Gruteser, M.; Oh, S.; Balle, B.; and Ramage, D. 2024 · 2024
Closest in time.
The ethics of advanced ai assistants
Gabriel, I.; Manzini, A.; Keeling, G.; Hendricks, L. A.; Rieser, V.; Iqbal, H.; Tomašev, N.; Ktena, I.; Kenton, Z.; Rodriguez, M.; et al. 2024 · 2024
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Pema: Plug-in external memory adaptation for language models
Kim, H.; Kim, Y. J.; and Bak, J. 2023 · 2023
Cited alongside, same era.
Can LLMs keep a secret? Testing privacy implications of language models via contextual integrity theory
Mireshghallah, N.; Kim, H.; Zhou, X.; Tsvetkov, Y.; Sap, M.; Shokri, R.; and Choi, Y. 2023 · 2023
Cited alongside, same era.
Simplyretrieve: A private and lightweight retrieval-centric generative ai tool
Ng, Y.; Miyashita, D.; Hoshi, Y.; Morioka, Y.; Torii, O.; Kodama, T.; and Deguchi, J. 2023 · 2023
Cited alongside, same era.
DecodingTrust: A comprehensive assessment of trustworthiness in GPT models
Wang, B.; Chen, W.; Pei, H.; Xie, C.; Kang, M.; Zhang, C.; Xu, C.; Xiong, Z.; Dutta, R.; Schaeffer, R.; Truong, S. T.; Arora, S.; Mazeika, M.; Hendrycks, D.; Lin, Z.; Cheng, Y.; Koyejo, S.; Song, D.; and Li, B. 2023a
Cited in the paper.
Aligning large Language Models with human: A survey
Wang, Y.; Zhong, W.; Li, L.; Mi, F.; Zeng, X.; Huang, W.; Shang, L.; Jiang, X.; and Liu, Q. 2023b
Cited in the paper.
Closest in time.
Operationalizing Contextual Integrity in Privacy-Conscious Assistants
Ghalebikesabi, S.; Bagdasaryan, E.; Yi, R.; Yona, I.; Shumailov, I.; Pappu, A.; Shi, C.; Weidinger, L.; Stanforth, R.; Berrada, L.; et al. 2024 · 2024
Closest in time.
Trustllm: Trustworthiness in large language models
Sun, L.; Huang, Y.; Wang, H.; Wu, S.; Zhang, Q.; Gao, C.; Huang, Y.; Lyu, W.; Zhang, Y.; Li, X.; et al. 2024 · 2024
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A survey on large language model based autonomous agents
Wang, L.; Ma, C.; Feng, X.; Zhang, Z.; Yang, H.; Zhang, J.; Chen, Z.; Tang, J.; Chen, X.; Lin, Y.; et al. 2024 · 2024
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