Bibliografías temáticas / Text privacy

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Literatura académica sobre el tema "Text privacy"

Autor: Grafiati
Publicado: 25 de mayo de 2024
Última modificación: 19 de julio de 2025

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Artículos de revistas sobre el tema "Text privacy"

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Kanyar, Mohammad Naeem. "Differential Privacy “Working Towards Differential Privacy for Sensitive Text “." International Journal of Engineering and Computer Science 12, no. 04 (2023): 25691–99. http://dx.doi.org/10.18535/ijecs/v12i04.4727.

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The differential-privacy idea states that maintaining privacy often includes adding noise to a data set to make it more challenging to identify data that corresponds to specific individuals. The accuracy of data analysis is typically decreased when noise is added, and differential privacy provides a technique to evaluate the accuracy-privacy trade-off. Although it may be more difficult to discern between analyses performed on somewhat dissimilar data sets, injecting random noise can also reduce the usefulness of the analysis. If not, enough noise is supplied to a very tiny data collection, ana
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Shree, A. N. Ramya, and Kiran P. "Privacy Preserving Text Document Summarization." Journal of Engineering Research and Sciences 1, no. 7 (2022): 7–14. http://dx.doi.org/10.55708/js0107002.

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Dopierała, Renata. "Społeczne wyobrażenia prywatności." Kultura i Społeczeństwo 50, no. 1-2 (2006): 307–19. http://dx.doi.org/10.35757/kis.2006.50.1-2.14.

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In the paper author considers social representations of privacy based on empirical research — The Unfinished Sentences Test. The main goals of the text are to begin defining such terms as: private life and private sphere, and to discuss functions of privacy, how it is experienced and its role in individual and social life. It also deals with the threats to privacy in contemporary societies.
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Bihani, Geetanjali. "Interpretable Privacy Preservation of Text Representations Using Vector Steganography." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (2022): 12872–73. http://dx.doi.org/10.1609/aaai.v36i11.21573.

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Contextual word representations generated by language models learn spurious associations present in the training corpora. Adversaries can exploit these associations to reverse-engineer the private attributes of entities mentioned in the training corpora. These findings have led to efforts towards minimizing the privacy risks of language models. However, existing approaches lack interpretability, compromise on data utility and fail to provide privacy guarantees. Thus, the goal of my doctoral research is to develop interpretable approaches towards privacy preservation of text representations tha
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Liang, Zi, Pinghui Wang, Ruofei Zhang, et al. "MERGE: Fast Private Text Generation." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 18 (2024): 19884–92. http://dx.doi.org/10.1609/aaai.v38i18.29964.

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The drastic increase in language models' parameters has led to a new trend of deploying models in cloud servers, raising growing concerns about private inference for Transformer-based models. Existing two-party privacy-preserving techniques, however, only take into account natural language understanding (NLU) scenarios. Private inference in natural language generation (NLG), crucial for applications like translation and code completion, remains underexplored. In addition, previous privacy-preserving techniques suffer from convergence issues during model training and exhibit poor inference spee
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Wunderlich, Dominik, Daniel Bernau, Francesco Aldà, Javier Parra-Arnau, and Thorsten Strufe. "On the Privacy–Utility Trade-Off in Differentially Private Hierarchical Text Classification." Applied Sciences 12, no. 21 (2022): 11177. http://dx.doi.org/10.3390/app122111177.

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Hierarchical text classification consists of classifying text documents into a hierarchy of classes and sub-classes. Although Artificial Neural Networks have proved useful to perform this task, unfortunately, they can leak training data information to adversaries due to training data memorization. Using differential privacy during model training can mitigate leakage attacks against trained models, enabling the models to be shared safely at the cost of reduced model accuracy. This work investigates the privacy–utility trade-off in hierarchical text classification with differential privacy guara
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Pang, Hweehwa, Jialie Shen, and Ramayya Krishnan. "Privacy-preserving similarity-based text retrieval." ACM Transactions on Internet Technology 10, no. 1 (2010): 1–39. http://dx.doi.org/10.1145/1667067.1667071.

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Vadlapati, Praneeth. "TokEncryption: Enhanced Hashing of Text using Tokenization." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–8. https://doi.org/10.55041/ijsrem20280.

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In the current digital space, the security of sensitive information, such as passwords and private data, is of high importance. Traditional hashing methods might not adequately address data privacy concerns or vulnerabilities created due to weak passwords. Tokenization methods are utilized in natural language processing (NLP). This paper introduces a method called “TokEncryption” to utilize tokens for one-way encryption of text called hashing. A tokenizer is used to generate tokens for an input text, which are utilized to encrypt the text to create secure encrypted text. Different characters o
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Zhu, You-wen, Liu-sheng Huang, Dong Li, and Wei Yang. "Privacy-preserving Text Information Hiding Detecting Algorithm." Journal of Electronics & Information Technology 33, no. 2 (2011): 278–83. http://dx.doi.org/10.3724/sp.j.1146.2010.00375.

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Tejaswini, G. "Cipher Text Policy Privacy Attribute-Based Security." International Journal of Reliable Information and Assurance 5, no. 1 (2017): 15–20. http://dx.doi.org/10.21742/ijria.2017.5.1.03.

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Tesis sobre el tema "Text privacy"

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Aryasomayajula, Naga Srinivasa Baradwaj. "Machine Learning Models for Categorizing Privacy Policy Text." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535633397362514.

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Hammoud, Khodor. "Trust in online data : privacy in text, and semantic-based author verification in micro-messages." Electronic Thesis or Diss., Université Paris Cité, 2021. http://www.theses.fr/2021UNIP5203.

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De nombreux problèmes émanent de la diffusion et l'utilisation des données sur les réseaux sociaux. Il est nécessaire de promouvoir la confiance sur les plateformes sociales, quant au partage et l’utilisation des données. Les données en ligne sont principalement sous forme textuelle, ce qui pose des problèmes aux solutions d'automatisation en raison de la richesse du langage naturel. De plus, l'utilisation des micro-messages comme principal moyen de communication sur les médias sociaux rend le problème beaucoup plus difficile en raison de la rareté des fonctionnalités à analyser par corps de t
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Connelly, Eric M. "[Redacted Text] and Surveillance: An Ideographic Analysis of the Struggle between National Security and Privacy." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/communication_theses/66.

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In the aftermath of the events of 9/11, the U.S. executive branch has repeatedly maintained that its need for action to secure the nation requires a revised interpretation of individual liberties. This study will explore the tensions between the positive ideographs and in response to the negative ideograph in a contemporary United States court ruling. Using Burke’s pentad, and cluster analysis, as well as Brummett’s notion of strategic silence, the study examines how the FISCR substantially changed the interrelationship between the two ideographs. The study concludes that the FISCR situated
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Rekanar, Kaavya. "Text Classification of Legitimate and Rogue online Privacy Policies : Manual Analysis and a Machine Learning Experimental Approach." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-13363.

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Mysore, Gopinath Abhijith Athreya. "Automatic Detection of Section Title and Prose Text in HTML Documents Using Unsupervised and Supervised Learning." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1535371714338677.

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Liu, Meng-Chang. "Achieving privacy-preserving distributed statistical computation." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/achieving-privacypreserving-distributed-statistical-computation(6831db5c-d605-4a38-9711-7592d2b94e01).html.

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The growth of the Internet has opened up tremendous opportunities for cooperative computations where the results depend on the private data inputs of distributed participating parties. In most cases, such computations are performed by multiple mutually untrusting parties. This has led the research community into studying methods for performing computation across the Internet securely and efficiently. This thesis investigates security methods in the search for an optimum solution to privacy- preserving distributed statistical computation problems. For this purpose, the nonparametric sign test a
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Steiner, Wolfgang Ernst. "Justifying limitations on privacy: the influence of the proportionality test in South African and German law." Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/4738.

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Baldwin, Lind Paula. "Looking for privacy in Shakespeare : woman's place and space in a selection of plays and early modern texts." Thesis, University of Birmingham, 2015. http://etheses.bham.ac.uk//id/eprint/5848/.

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Grounded in a multi-faceted theoretical framework that examines the dynamic interaction between the public and the private spheres of Elizabethan everyday life, this thesis aims to trace how the concept of privacy and its associated terms were developed, constructed, evoked, and configured both in Shakespearean drama and in other illustrative early modern texts. The author suggests that Shakespeare's configuration of space results from a combination of the conditions of representation - empty stages - metaphorical language, technical dramatic devices, and textual markers that create a sense of
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Chow, Mark A. (Mark Andrew) 1972. "A rating system to test private investment decisions in public infrastructure projects." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/50511.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 1998.<br>Includes bibliographical references (p. 167-168).<br>This thesis will develop a basic method to evaluate the overall quality of proposed infrastructure projects for private sector financial investment. INFRATEST is meant to aid both potential private infrastructure developers and public entities, which desire to privatize certain infrastructure projects, in selection of the most appropriate infrastructure projects to benefit from the advantages of free enterprise. INFRATEST is premised
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Brodin, Gustav. "Privatekonomi i läroböcker : En läroboksstudie i samhällsvetenskap om privatekonomins kvantitet och innehåll." Thesis, Karlstads universitet, Institutionen för samhälls- och kulturvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-28147.

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Barn och ungas skulder som registrerats hos Kronofogden har under de senaste åren aldrig varit flera. Skolan har ett ansvar att försöka hindra denna oroväckande utveckling. Denna uppsats handlar om privatekonomins förekomst i tre olika läroböcker för samhällskunskap 1A1 på gymnasiet och har som mål att undersöka vilken hjälp dessa böcker ger lärare och elever på gymnasiet. I den senaste läroplanen SKOLFS 2011 har privatekonomi lagts till och är numera ett gymnasiegemensamt ämne som alla elever läser. Genom ett kodschema har jag kunnat identifiera förekomsten av privatekonomin och bestämma kvan
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Libros sobre el tema "Text privacy"

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Aryeh Greenfield-A.G. Publications (Israel), ed. Protection of Privacy: Full text English translation of the Protection of Privacy Law 5741-1981 and of relevant subsidiary legislation correct as of November 1, 2011. 6th ed. Aryeh Greenfield-A.G. Publications, 2011.

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United States. Federal Aviation Administration., ed. Private pilot test guide. Aviation Supplies & Academics, 1992.

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McCarthy, Steven J. Unbroken record: Electronic communication, forever undigitized. Steven McCarthy, 2014.

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United States. Federal Aviation Administration. Office of Flight Standards., ed. Private pilot: Practical test standards. U.S. Dept. of Transportation, Federal Aviation Administration, Office of Flight Standards, 1987.

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United States. Federal Aviation Administration. Office of Flight Standards Service., ed. Private pilot: Practical test standards. Flight Standards Service, 1995.

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United States. Federal Aviation Administration. Office of Flight Standards Service., ed. Private pilot: Practical test standards. Flight Standards Service, 1995.

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Benson, Peter. Theory of private law: Selected topics and text. Faculty of Law, University of Toronto, 2013.

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United States. Health Care Financing Administration. Medicare and private health insurance: A training text. U.S. Department of Health and Human Services, Health Care Financing Administration, 1985.

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Benson, Peter. Theory of private law: Selected topics and text. Faculty of Law, University of Toronto, 2014.

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Benson, Peter. Theory of private law: Selected topics and text. Faculty of Law, University of Toronto, 2010.

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Capítulos de libros sobre el tema "Text privacy"

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Salomon, David. "Data Hiding in Text." In Data Privacy and Security. Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21707-9_11.

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Hart, Michael, Pratyusa Manadhata, and Rob Johnson. "Text Classification for Data Loss Prevention." In Privacy Enhancing Technologies. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22263-4_2.

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Garg, Vaibhav, L. Jean Camp, Katherine Connelly, and Lesa Lorenzen-Huber. "Risk Communication Design: Video vs. Text." In Privacy Enhancing Technologies. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31680-7_15.

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Danezis, George, Claudia Diaz, Carmela Troncoso, and Ben Laurie. "$\text{Drac}$ : An Architecture for Anonymous Low-Volume Communications." In Privacy Enhancing Technologies. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14527-8_12.

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Müller, Nicolas M., Daniel Kowatsch, Pascal Debus, Donika Mirdita, and Konstantin Böttinger. "On GDPR Compliance of Companies’ Privacy Policies." In Text, Speech, and Dialogue. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-27947-9_13.

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Haralabopoulos, Giannis, Mercedes Torres Torres, Ioannis Anagnostopoulos, and Derek McAuley. "Privacy-Preserving Text Labelling Through Crowdsourcing." In Artificial Intelligence Applications and Innovations. AIAI 2021 IFIP WG 12.5 International Workshops. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79157-5_35.

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Manzanares-Salor, Benet, David Sánchez, and Pierre Lison. "Automatic Evaluation of Disclosure Risks of Text Anonymization Methods." In Privacy in Statistical Databases. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-13945-1_12.

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Dalianis, Hercules. "Ethics and Privacy of Patient Records for Clinical Text Mining Research." In Clinical Text Mining. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78503-5_9.

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Fernandes, Natasha, Mark Dras, and Annabelle McIver. "Generalised Differential Privacy for Text Document Processing." In Lecture Notes in Computer Science. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-17138-4_6.

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Gusain, Vaibhav, and Douglas Leith. "Towards Quantifying the Privacy of Redacted Text." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28238-6_32.

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Actas de conferencias sobre el tema "Text privacy"

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Zhan, Huixin, Liyuan Gao, and Victor S. Sheng. "Privacy-Preserving Unsupervised Spherical Text Embeddings." In 2024 International Joint Conference on Neural Networks (IJCNN). IEEE, 2024. http://dx.doi.org/10.1109/ijcnn60899.2024.10650028.

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Yang, Yuchen, Bo Hui, Haolin Yuan, Neil Gong, and Yinzhi Cao. "SneakyPrompt: Jailbreaking Text-to-image Generative Models." In 2024 IEEE Symposium on Security and Privacy (SP). IEEE, 2024. http://dx.doi.org/10.1109/sp54263.2024.00123.

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Papadopoulou, Anthi, Yunhao Yu, Pierre Lison, and Lilja Øvrelid. "Neural Text Sanitization with Explicit Measures of Privacy Risk." In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.aacl-main.18.

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Liu, Shuofeng, Mengyao Ma, Minhui Xue, and Guangdong Bai. "Modifier Unlocked: Jailbreaking Text-to-Image Models Through Prompts." In 2025 IEEE Symposium on Security and Privacy (SP). IEEE, 2025. https://doi.org/10.1109/sp61157.2025.00242.

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Zhang, Xinyu, Hanbin Hong, Yuan Hong, et al. "Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks." In 2024 IEEE Symposium on Security and Privacy (SP). IEEE, 2024. http://dx.doi.org/10.1109/sp54263.2024.00053.

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Shan, Shawn, Wenxin Ding, Josephine Passananti, Stanley Wu, Haitao Zheng, and Ben Y. Zhao. "Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models." In 2024 IEEE Symposium on Security and Privacy (SP). IEEE, 2024. http://dx.doi.org/10.1109/sp54263.2024.00207.

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Shahriar, Sakib, and Rozita Dara. "PriSM: Privacy-Preserving Social Media Text Processing and Analytics Framework." In 2024 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2024. https://doi.org/10.1109/icdmw65004.2024.00014.

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Meisenbacher, Stephen, Alexandra Klymenko, Alexander Karpp, and Florian Matthes. "Investigating User Perspectives on Differentially Private Text Privatization." In Proceedings of the Sixth Workshop on Privacy in Natural Language Processing. Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.privatenlp-main.8.

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Arnold, Stefan. "Inspecting the Representation Manifold of Differentially-Private Text." In Proceedings of the Sixth Workshop on Privacy in Natural Language Processing. Association for Computational Linguistics, 2025. https://doi.org/10.18653/v1/2025.privatenlp-main.5.

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Wang, WenHao, Xiaoyu Liang, Rui Ye, Jingyi Chai, Siheng Chen, and Yanfeng Wang. "KnowledgeSG: Privacy-Preserving Synthetic Text Generation with Knowledge Distillation from Server." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.438.

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Informes sobre el tema "Text privacy"

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Maerz, Seraphine. Using AI for Text Analysis: Advanced Applications. Instats Inc., 2024. https://doi.org/10.61700/nqumt3vu2zq3k1816.

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This one-day workshop provides an advanced exploration of AI-driven text analysis, focusing on the application and fine-tuning of open-source large language models to enhance research across various academic disciplines. Participants will gain practical skills in setting up local environments and employing sophisticated AI methodologies, empowering them to conduct independent and impactful text analysis while ensuring data security and privacy.
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Cantor, Amy G., Rebecca M. Jungbauer, Andrea C. Skelly, et al. Respectful Maternity Care: Dissemination and Implementation of Perinatal Safety Culture To Improve Equitable Maternal Healthcare Delivery and Outcomes. Agency for Healthcare Research and Quality (AHRQ), 2024. http://dx.doi.org/10.23970/ahrqepccer269.

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Objective. To summarize current research defining and measuring respectful maternity care (RMC) and evaluate the effectiveness of RMC and implementation strategies to improve health outcomes, particularly for populations at risk for health disparities. Data sources. Ovid MEDLINE®, Embase®, and Cochrane CENTRAL from inception to November 2022 and SocINDEX to July 2023; manual review of reference lists and responses to a Federal Register Notice. Review methods. Dual review of eligible abstracts and full-text articles using predefined criteria. Data abstraction and quality assessment dual reviewe
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Andrabi, Tahir, Natalie Bau, Jishnu Das, and Asim I. Khwaja. Heterogeneity in School Value-Added and the Private Premium. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsg-risewp_2022/116.

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Using rich panel data from Pakistan, we compute test score based measures of quality (School Value-Addeds or SVAs) for more than 800 schools across 112 villages and verify that they are valid and unbiased. With the SVA measures, we then document three striking features of the schooling environment. First, there is substantial within-village variation in quality. The annualized difference in learning between the best and worst performing school in the same village is 0.4 sd; compounded over 5 years of primary schooling, this difference is similar in size to the test score gap between low- and h
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Agüero, Jorge M., and Verónica Frisancho. Systematic Bias in Sensitive Health Behaviors and Its Impact on Treatment Effects: An Application to Violence against Women. Inter-American Development Bank, 2017. http://dx.doi.org/10.18235/0007031.

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Violence against women takes place mainly in the private sphere and isperpetrated by people close to the victim. These features can introduce large biases into its reporting in specialized surveys as well as to the authorities. We test for the existence of measurement error in the reporting of such violence using experimental methods in Peru, a country with several specialized surveys but one lacking reliable administrative data. We ask women to report past experiences of violent acts by randomly assigning them one of two questionnaires, one that replicates current surveys and another that rel
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Andrabi, Tahir, Natalie Bau, Jishnu Das, Naureen Karachiwalla, and Asim I. Khwaja. Crowding in Private Quality: The Equilibrium Effects of Public Spending in Education. Research on Improving Systems of Education (RISE), 2023. http://dx.doi.org/10.35489/bsg-rise-wp_2023/124.

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We estimate the equilibrium effects of a public school grant program administered through school councils in Pakistani villages with multiple public and private schools and clearly defined catchment boundaries. The program was randomized at the village-level, allowing us to estimate its causal impact on the market. Four years after the start of the program, test scores were 0.2 sd higher in public schools. We find evidence of an education multiplier: test scores in private schools were also 0.2 sd higher in treated markets. Consistent with standard models of product differentiation, the educat
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Bonaldi, Pietro, and Mauricio Villamizar-Villegas. An Auction-Based Test of Private Information in an Interdealer FX Market. Banco de la República, 2018. http://dx.doi.org/10.32468/be.1049.

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Bronnenberg, Bart, Jean-Pierre Dubé, and Robert Sanders. Consumer Misinformation and the Brand Premium: A Private Label Blind Taste Test. National Bureau of Economic Research, 2018. http://dx.doi.org/10.3386/w25214.

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Ahwireng-Obeng, Asabea Shirley, and Frederick Ahwireng-Obeng. Private Philanthropic Cross-Border Flows and Sustainable Development in Africa. Centre on African Philanthropy and Social Investment, 2011. http://dx.doi.org/10.47019/2021.ra1.

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The paper examines the simultaneous impact of private philanthropic cross-border funding from international foundations on the economic, social, and environmental dimensions of sustainable development in Africa. The vector error correction model (VECM) was used, and contrary to expectations drawn from past studies, funding from this source improves economic growth, advances human development, and enhances environmental quality. Causality test results also disconfirmed the assumption that interactions among the three dimensions were positive and complementary in the long term. The environment v
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Gan, Li, Feng Huang, and Adalbert Mayer. A Simple Test of Private Information in the Insurance Markets with Heterogeneous Insurance Demand. National Bureau of Economic Research, 2011. http://dx.doi.org/10.3386/w16738.

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Borger, Michael, Gregory Elacqua, Isabel Jacas, Christopher Neilson, and Anne Sofie Westh Olsen. Report Cards: Parental Preferences, Information and School Choice in Haiti. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0004933.

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This paper studies school choice and information in the context of education markets in rural Haiti. Using a market level randomized control trial, we evaluate the aggregate effect of providing test score information on subsequent test scores, prices, and enrollment. After the intervention, we find that private schools have higher test scores, with an average increase of 0.3 standard deviations in treated markets. However, we are unable to detect significant changes to prices and market shares. These findings suggest that providing information in poor education markets can improve market effic
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