Fetching the paper…
Reading the bibliography…
Large Language Models (LLMs) are gaining increasing attention due to their exceptional performance across numerous tasks.
Medical document anonymization with a semantic lexicon. In AMIA 2000, American Medical Informatics Association Annual Symposium, Los Angeles, CA, USA, November 4-8, 2000 . AMIA
Patrick Ruch, Robert H. Baud, Anne-Marie Rassinoux, Pierrette Bouillon, and Gilbert Robert. 2000 · 2000
Earlier work this paper cites.
Trustzone: Integrated Hardware and Software Security
Thaynara Alves and D. Felton. 2004 · 2004
Earlier work this paper cites.
De-identification algorithm for free-text nursing notes. In Computers in Cardiology, 2005 . 331–334
M.M. Douglass, G.D. Cliffford, A. Reisner, W.J. Long, G.B. Moody, and R.G. Mark. 2005 · 2005
Earlier work this paper cites.
Hiding in the Crowd: Privacy Preservation on Evolving Streams through Correlation Tracking. In Proceedings of the 23rd International Conference on Data Engineering, ICDE 2007, The Marmara Hotel, Istanbul, Turkey, April 15-20, 2007 , Rada Chirkova, Asuman Dogac, M. Tamer Özsu, and Timos K. Sellis (Eds.). IEEE Computer Society, 686–695
Feifei Li, Jimeng Sun, Spiros Papadimitriou, George A. Mihaila, and Ioana Stanoi. 2007 · 2007
Earlier work this paper cites.
Efficient techniques for document sanitization. In Proceedings of the 17th ACM Conference on Information and Knowledge Management, CIKM 2008, Napa Valley, California, USA, October 26-30, 2008 , James G. Shanahan, Sihem Amer-Yahia, Ioana Manolescu, Yi Zhang, David A. Evans, Aleksander Kolcz, Key-Sun Choi, and Abdur Chowdhury (Eds.). ACM, 843–852
Venkatesan T. Chakaravarthy, Himanshu Gupta, Prasan Roy, and Mukesh K. Mohania. 2008 · 2008
Earlier work this paper cites.
Privacy integrated queries: an extensible platform for privacy-preserving data analysis. In Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2009, Providence, Rhode Island, USA, June 29 - July 2, 2009 , Ugur Çetintemel, Stanley B. Zdonik, Donald Kossmann, and Nesime Tatbul (Eds.). ACM, 19–30
Frank McSherry. 2009 · 2009
Earlier work this paper cites.
Airavat: Security and Privacy for MapReduce. In Proceedings of the 7th USENIX Symposium on Networked Systems Design and Implementation, NSDI 2010, April 28-30, 2010, San Jose, CA, USA . USENIX Association, 297–312
Indrajit Roy, Srinath T. V. Setty, Ann Kilzer, Vitaly Shmatikov, and Emmett Witchel. 2010 · 2010
Earlier work this paper cites.
The HybrEx Model for Confidentiality and Privacy in Cloud Computing. In 3rd USENIX Workshop on Hot Topics in Cloud Computing, HotCloud’11, Portland, OR, USA, June 14-15, 2011 , Ion Stoica and John Wilkes (Eds.). USENIX Association
Steven Y. Ko, Kyungho Jeon, and Ramsés Morales. 2011 · 2011
Earlier work this paper cites.
t-Plausibility: Generalizing Words to Desensitize Text
Balamurugan Anandan, Chris Clifton, Wei Jiang, Mummoorthy Murugesan, Pedro Pastrana-Camacho, and Luo Si. 2012 · 2012
Earlier work this paper cites.
Large-scale evaluation of automated clinical note de-identification and its impact on information extraction
Louise Deléger, Katalin Molnár, Guergana Savova, Fei Xia, Todd Lingren, Qi Li, Keith Marsolo, Anil G. Jegga, Megan Kaiser, Laura Stoutenborough, and Imre Solti. 2013 · 2013
Earlier work this paper cites.
The Algorithmic Foundations of Differential Privacy
Cynthia Dwork and Aaron Roth. 2014 · 2014
Earlier work this paper cites.
M2R: Enabling Stronger Privacy in MapReduce Computation. In 24th USENIX Security Symposium, USENIX Security 15, Washington, D.C., USA, August 12-14, 2015 , Jaeyeon Jung and Thorsten Holz (Eds.). USENIX Association, 447–462
Tien Tuan Anh Dinh, Prateek Saxena, Ee-Chien Chang, Beng Chin Ooi, and Chunwang Zhang. 2015 · 2015
Earlier work this paper cites.
Differential Privacy: Now it’s Getting Personal. In Proceedings of the 42nd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, POPL 2015, Mumbai, India, January 15-17, 2015 , Sriram K. Rajamani and David Walker (Eds.). ACM, 69–81
Hamid Ebadi, David Sands, and Gerardo Schneider. 2015 · 2015
Earlier work this paper cites.
Observing and Preventing Leakage in MapReduce. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, Denver, CO, USA, October 12-16, 2015 , Indrajit Ray, Ninghui Li, and Christopher Kruegel (Eds.). ACM, 1570–1581
Olga Ohrimenko, Manuel Costa, Cédric Fournet, Christos Gkantsidis, Markulf Kohlweiss, and Divya Sharma. 2015 · 2015
Earlier work this paper cites.
SEMROD: Secure and Efficient MapReduce Over HybriD Clouds. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data, Melbourne, Victoria, Australia, May 31 - June 4, 2015 , Timos K. Sellis, Susan B. Davidson, and Zachary G. Ives (Eds.). ACM, 153–166
Kerim Yasin Oktay, Sharad Mehrotra, Vaibhav Khadilkar, and Murat Kantarcioglu. 2015 · 2015
Earlier work this paper cites.
Deep Learning with Differential Privacy. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security, Vienna, Austria, October 24-28, 2016 , Edgar R. Weippl, Stefan Katzenbeisser, Christopher Kruegel, Andrew C. Myers, and Shai Halevi (Eds.). ACM, 308–318
Martín Abadi, Andy Chu, Ian J. Goodfellow, H. Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang. 2016 · 2016
Earlier work this paper cites.
C-sanitized: A privacy model for document redaction and sanitization
David Sánchez and Montserrat Batet. 2016 · 2016
Earlier work this paper cites.
Intel® Software Guard Extensions (Intel® SGX) Architecture for Oversubscription of Secure Memory in a Virtualized Environment. In Proceedings of the Hardware and Architectural Support for Security and Privacy, HASP@ISCA 2017, Toronto, ON, Canada, June 25, 2017 . ACM, 7:1–7:8
Somnath Chakrabarti, Rebekah Leslie-Hurd, Mona Vij, Frank McKeen, Carlos V. Rozas, Dror Caspi, Ilya Alexandrovich, and Ittai Anati. 2017 · 2017
Earlier work this paper cites.
De-identification of patient notes with recurrent neural networks
Franck Dernoncourt, Ji Young Lee, Özlem Uzuner, and Peter Szolovits. 2017 · 2017
Earlier work this paper cites.
Collecting Telemetry Data Privately. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA , Isabelle Guyon, Ulrike von Luxburg, Samy Bengio, Hanna M. Wallach, Rob Fergus, S. V. N. Vishwanathan, and Roman Garnett (Eds.). 3571–3580
Bolin Ding, Janardhan Kulkarni, and Sergey Yekhanin. 2017 · 2017
Earlier work this paper cites.
Glamdring: Automatic Application Partitioning for Intel SGX. In 2017 USENIX Annual Technical Conference, USENIX ATC 2017, Santa Clara, CA, USA, July 12-14, 2017 , Dilma Da Silva and Bryan Ford (Eds.). USENIX Association, 285–298
Joshua Lind, Christian Priebe, Divya Muthukumaran, Dan O’Keeffe, Pierre-Louis Aublin, Florian Kelbert, Tobias Reiher, David Goltzsche, David M. Eyers, Rüdiger Kapitza, Christof Fetzer, and Peter R. Pietzuch. 2017 · 2017
Earlier work this paper cites.
Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase
Jianfeng Chi, Emmanuel Owusu, Xuwang Yin, Tong Yu, William Chan, Patrick Tague, and Yuan Tian. 2018 · 2018
Earlier work this paper cites.
Privacy-preserving Neural Representations of Text. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31 - November 4, 2018 , Ellen Riloff, David Chiang, Julia Hockenmaier, and Jun’ichi Tsujii (Eds.). Association for Computational Linguistics, 1–10
Maximin Coavoux, Shashi Narayan, and Shay B. Cohen. 2018 · 2018
Earlier work this paper cites.
SecureMR: secure mapreduce computation using homomorphic encryption and program partitioning. In Proceedings of the 5th Annual Symposium and Bootcamp on Hot Topics in the Science of Security, HoTSoS 2018, Raleigh, North Carolina, USA, April 10-11, 2018 , Munindar P. Singh, Laurie A. Williams, Rick Kuhn, and Tao Xie (Eds.). ACM, 4:1–4:13
Yao Dong, Ana L. Milanova, and Julian Dolby. 2018 · 2018
Earlier work this paper cites.
Towards Robust and Privacy-preserving Text Representations. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, Melbourne, Australia, July 15-20, 2018, Volume 2: Short Papers , Iryna Gurevych and Yusuke Miyao (Eds.). Association for Computational Linguistics, 25–30
Yitong Li, Timothy Baldwin, and Trevor Cohn. 2018 · 2018
Earlier work this paper cites.
Learning Differentially Private Recurrent Language Models. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings . OpenReview.net
H. Brendan McMahan, Daniel Ramage, Kunal Talwar, and Li Zhang. 2018 · 2018
Earlier work this paper cites.
Scalable Private Learning with PATE. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings . OpenReview.net
Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Úlfar Erlingsson. 2018 · 2018
Cited alongside, same era.
ATOMO: Communication-efficient Learning via Atomic Sparsification. In Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, December 3-8, 2018, Montréal, Canada , Samy Bengio, Hanna M. Wallach, Hugo Larochelle, Kristen Grauman, Nicolò Cesa-Bianchi, and Roman Garnett (Eds.). 9872–9883
Hongyi Wang, Scott Sievert, Shengchao Liu, Zachary Charles, Dimitris S. Papailiopoulos, and Stephen J. Wright. 2018 · 2018
Cited alongside, same era.
Towards Federated Learning at Scale: System Design. In Proceedings of Machine Learning and Systems 2019, MLSys 2019, Stanford, CA, USA, March 31 - April 2, 2019 , Ameet Talwalkar, Virginia Smith, and Matei Zaharia (Eds.). mlsys.org
Kallista A. Bonawitz, Hubert Eichner, Wolfgang Grieskamp, Dzmitry Huba, Alex Ingerman, Vladimir Ivanov, Chloé Kiddon, Jakub Konečný, Stefano Mazzocchi, Brendan McMahan, Timon Van Overveldt, David Petrou, Daniel Ramage, and Jason Roselander. 2019 · 2019
Cited alongside, same era.
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy. In CCS ’21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15 - 19, 2021 , Yongdae Kim, Jong Kim, Giovanni Vigna, and Elaine Shi (Eds.). ACM, 1266–1288
Linkang Du, Zhikun Zhang, Shaojie Bai, Changchang Liu, Shouling Ji, Peng Cheng, and Jiming Chen. 2021a · 2021
Later among the works it cites.
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy. In CCS ’21: 2021 ACM SIGSAC Conference on Computer and Communications Security, Virtual Event, Republic of Korea, November 15 - 19, 2021 , Yongdae Kim, Jong Kim, Giovanni Vigna, and Elaine Shi (Eds.). ACM, 1266–1288
Linkang Du, Zhikun Zhang, Shaojie Bai, Changchang Liu, Shouling Ji, Peng Cheng, and Jiming Chen. 2021b · 2021
Later among the works it cites.
Learning and Evaluating a Differentially Private Pre-trained Language Model. In Findings of the Association for Computational Linguistics: EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 16-20 November, 2021 , Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih (Eds.). Association for Computational Linguistics, 1178–1189
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks. In 28th USENIX Security Symposium, USENIX Security 2019, Santa Clara, CA, USA, August 14-16, 2019 , Nadia Heninger and Patrick Traynor (Eds.). USENIX Association, 267–284
Nicholas Carlini, Chang Liu, Úlfar Erlingsson, Jernej Kos, and Dawn Song. 2019 · 2019
Cited alongside, same era.
Partitioned Data Security on Outsourced Sensitive and Non-Sensitive Data. In 35th IEEE International Conference on Data Engineering, ICDE 2019, Macao, China, April 8-11, 2019 . IEEE, 650–661
Sharad Mehrotra, Shantanu Sharma, Jeffrey D. Ullman, and Anurag Mishra. 2019 · 2019
Cited alongside, same era.
Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge. In 2019 IEEE International Conference on Communications, ICC 2019, Shanghai, China, May 20-24, 2019 . IEEE, 1–7
Takayuki Nishio and Ryo Yonetani. 2019 · 2019
Cited alongside, same era.
Local SGD Converges Fast and Communicates Little. In 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019 . OpenReview.net
Sebastian U. Stich. 2019 · 2019
Cited alongside, same era.
Conclave: secure multi-party computation on big data. In Proceedings of the Fourteenth EuroSys Conference 2019, Dresden, Germany, March 25-28, 2019 , George Candea, Robbert van Renesse, and Christof Fetzer (Eds.). ACM, 3:1–3:18
Nikolaj Volgushev, Malte Schwarzkopf, Ben Getchell, Mayank Varia, Andrei Lapets, and Azer Bestavros. 2019 · 2019
Cited alongside, same era.
PrivKV: Key-Value Data Collection with Local Differential Privacy. In 2019 IEEE Symposium on Security and Privacy, SP 2019, San Francisco, CA, USA, May 19-23, 2019 . IEEE, 317–331
Qingqing Ye, Haibo Hu, Xiaofeng Meng, and Huadi Zheng. 2019 · 2019
Cited alongside, same era.
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations. In WSDM ’20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020 , James Caverlee, Xia (Ben) Hu, Mounia Lalmas, and Wei Wang (Eds.). ACM, 178–186
Oluwaseyi Feyisetan, Borja Balle, Thomas Drake, and Tom Diethe. 2020 · 2020
Cited alongside, same era.
PoWER-BERT: Accelerating BERT Inference via Progressive Word-vector Elimination. In Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event (Proceedings of Machine Learning Research, Vol. 119) . PMLR, 3690–3699
Saurabh Goyal, Anamitra Roy Choudhury, Saurabh Raje, Venkatesan T. Chakaravarthy, Yogish Sabharwal, and Ashish Verma. 2020 · 2020
Cited alongside, same era.
PCKV: Locally Differentially Private Correlated Key-Value Data Collection with Optimized Utility. In 29th USENIX Security Symposium, USENIX Security 2020, August 12-14, 2020 , Srdjan Capkun and Franziska Roesner (Eds.). USENIX Association, 967–984
Xiaolan Gu, Ming Li, Yueqiang Cheng, Li Xiong, and Yang Cao. 2020 · 2020
Cited alongside, same era.
Shlomo Hoory, Amir Feder, Avichai Tendler, Sofia Erell, Alon Peled-Cohen, Itay Laish, Hootan Nakhost, Uri Stemmer, Ayelet Benjamini, Avinatan Hassidim, and Yossi Matias. 2021 · 2021
Later among the works it cites.
Survey: Leakage and Privacy at Inference Time
Marija Jegorova, Chaitanya Kaul, Charlie Mayor, Alison Q. O’Neil, Alexander Weir, Roderick Murray-Smith, and Sotirios A. Tsaftaris. 2021 · 2021
Later among the works it cites.
Federated Multi-Task Learning under a Mixture of Distributions. In Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual , Marc’Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, and Jennifer Wortman Vaughan (Eds.). 15434–15447
Othmane Marfoq, Giovanni Neglia, Aurélien Bellet, Laetitia Kameni, and Richard Vidal. 2021 · 2021
Later among the works it cites.
Tempered Sigmoid Activations for Deep Learning with Differential Privacy. In Thirty-Fifth AAAI Conference on Artificial Intelligence, AAAI 2021, Thirty-Third Conference on Innovative Applications of Artificial Intelligence, IAAI 2021, The Eleventh Symposium on Educational Advances in Artificial Intelligence, EAAI 2021, Virtual Event, February 2-9, 2021 . AAAI Press, 9312–9321
Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, and Úlfar Erlingsson. 2021 · 2021
Later among the works it cites.
CAPE: Context-Aware Private Embeddings for Private Language Learning. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 7-11 November, 2021 , Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih (Eds.). Association for Computational Linguistics, 7970–7978
Richard Plant, Dimitra Gkatzia, and Valerio Giuffrida. 2021 · 2021
Later among the works it cites.
DPlis: Boosting Utility of Differentially Private Deep Learning via Randomized Smoothing
Wenxiao Wang, Tianhao Wang, Lun Wang, Nanqing Luo, Pan Zhou, Dawn Song, and Ruoxi Jia. 2021 · 2021
Later among the works it cites.
TR-BERT: Dynamic Token Reduction for Accelerating BERT Inference. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2021, Online, June 6-11, 2021 , Kristina Toutanova, Anna Rumshisky, Luke Zettlemoyer, Dilek Hakkani-Tür, Iz Beltagy, Steven Bethard, Ryan Cotterell, Tanmoy Chakraborty, and Yichao Zhou (Eds.). Association for Computational Linguistics, 5798–5809
Deming Ye, Yankai Lin, Yufei Huang, and Maosong Sun. 2021 · 2021
Later among the works it cites.
Differential Privacy for Text Analytics via Natural Text Sanitization. In Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, Online Event, August 1-6, 2021 (Findings of ACL, Vol. ACL/IJCNLP 2021) , Chengqing Zong, Fei Xia, Wenjie Li, and Roberto Navigli (Eds.). Association for Computational Linguistics, 3853–3866
Xiang Yue, Minxin Du, Tianhao Wang, Yaliang Li, Huan Sun, and Sherman S. M. Chow. 2021 · 2021
Later among the works it cites.
What Does it Mean for a Language Model to Preserve Privacy?. In FAccT ’22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21 - 24, 2022 . ACM, 2280–2292
Hannah Brown, Katherine Lee, Fatemehsadat Mireshghallah, Reza Shokri, and Florian Tramèr. 2022 · 2022
Later among the works it cites.
THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption. In Findings of the Association for Computational Linguistics: ACL 2022, Dublin, Ireland, May 22-27, 2022 , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, 3510–3520
Tianyu Chen, Hangbo Bao, Shaohan Huang, Li Dong, Binxing Jiao, Daxin Jiang, Haoyi Zhou, Jianxin Li, and Furu Wei. 2022a · 2022
Later among the works it cites.
AdapLeR: Speeding up Inference by Adaptive Length Reduction. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2022, Dublin, Ireland, May 22-27, 2022 , Smaranda Muresan, Preslav Nakov, and Aline Villavicencio (Eds.). Association for Computational Linguistics, 1–15
Ali Modarressi, Hosein Mohebbi, and Mohammad Taher Pilehvar. 2022 · 2022
Later among the works it cites.
The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization
Ildikó Pilán, Pierre Lison, Lilja Øvrelid, Anthi Papadopoulou, David Sánchez, and Montserrat Batet. 2022 · 2022
Later among the works it cites.
Selective Differential Privacy for Language Modeling. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022, Seattle, WA, United States, July 10-15, 2022 , Marine Carpuat, Marie-Catherine de Marneffe, and Iván Vladimir Meza Ruíz (Eds.). Association for Computational Linguistics, 2848–2859
Weiyan Shi, Aiqi Cui, Evan Li, Ruoxi Jia, and Zhou Yu. 2022 · 2022
Later among the works it cites.
Differentially Private Fine-tuning of Language Models. In The Tenth International Conference on Learning Representations, ICLR 2022, Virtual Event, April 25-29, 2022 . OpenReview.net
Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A. Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee, Andre Manoel, Lukas Wutschitz, Sergey Yekhanin, and Huishuai Zhang. 2022 · 2022
Later among the works it cites.
Xin Zhou, Jinzhu Lu, Tao Gui, Ruotian Ma, Zichu Fei, Yuran Wang, Yong Ding, Yibo Cheung, Qi Zhang, and Xuanjing Huang. [n. d.] · 2022
Later among the works it cites.
FedBot: Enhancing Privacy in Chatbots with Federated Learning
Addi Ait-Mlouk, Sadi Alawadi, Salman Toor, and Andreas Hellander. 2023 · 2023
Closest in time.
Chuan Chen, Zhenpeng Wu, Yanyi Lai, Wenlin Ou, Tianchi Liao, and Zibin Zheng. 2023 · 2023
Closest in time.
Exploring the Feasibility of ChatGPT for Event Extraction
Jun Gao, Huan Zhao, Changlong Yu, and Ruifeng Xu. 2023 · 2023
Closest in time.
FLARE: A Fast, Secure, and Memory-Efficient Distributed Analytics Framework (Flavor: Systems)
Xiang Li, Fabing Li, and Mingyu Gao. 2023 · 2023
Closest in time.
Differentially Private In-Context Learning
Ashwinee Panda, Tong Wu, Jiachen T. Wang, and Prateek Mittal. 2023 · 2023
Closest in time.
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, Aurélien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023
Closest in time.
A survey on privacy inference attacks and defenses in cloud-based Deep Neural Network
Xiaoyu Zhang, Chao Chen, Yi Xie, Xiaofeng Chen, Jun Zhang, and Yang Xiang. 2023 · 2023
Closest in time.
CRYPTOGRU: Low Latency Privacy-Preserving Text Analysis With GRU. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, EMNLP 2021, Virtual Event / Punta Cana, Dominican Republic, 7-11 November, 2021 , Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih (Eds.). Association for Computational Linguistics, 2052–2057
Bo Feng, Qian Lou, Lei Jiang, and Geoffrey C. Fox. 2021 · 2057
Closest in time.