Governing Open Vocabulary Data Leaks Using an Edge LLM through Programming by Example

Imad M. Abbadi and Muntaha Alawneh. 2008. Preventing Insider Information Leakage for Enterprises. In 2008 Second International Conference on Emerging Security Information, Systems and Technologies. 99--106. https://doi.org/10.1109/SECURWARE.2008.14

Almas Abdibayev, Dongkai Chen, Haipeng Chen, Deepti Poluru, and V. S. Subrahmanian. 2021. Using Word Embeddings to Deter Intellectual Property Theft through Automated Generation of Fake Documents. ACM Trans. Manage. Inf. Syst. 12, 2, Article 13 (feb 2021), 22 pages. https://doi.org/10.1145/3418289

Mistral AI. 2023. Mistral 7B. https://mistral.ai/news/announcing-mistral-7b/.

Hanan Alhindi, Issa Traore, and Isaac Woungang. 2021. Preventing Data Leak through Semantic Analysis. Internet of Things 14 (2021), 100073. https://doi.org/10.1016/j.iot.2019.100073

Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko, Karen Khatamifard, Minsik Cho, Carlo C Del Mundo, Mohammad Rastegari, and Mehrdad Farajtabar. 2023. Llm in a flash: Efficient large language model inference with limited memory. arXiv preprint arXiv:2312.11514 (2023).

Sultan Alneyadi, Elankayer Sithirasenan, and Vallipuram Muthukkumarasamy. 2015. Detecting Data Semantic: A Data Leakage Prevention Approach. In 2015 IEEE Trustcom/BigDataSE/ISPA, Vol. 1. 910--917. https://doi.org/10.1109/Trustcom.2015.464

Matthias Bastian. 2023. Microsoft offers "Private ChatGPT" as a free Azure app. https://fhe-decoder.com/microsoft-offers-private-chatgpt-as-a-free-azure-app/. (Accessed on 08/14/2023).

Rajarshi Bhowmik and Gerard de Melo. 2018. Generating Fine-Grained Open Vocabulary Entity Type Descriptions. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Iryna Gurevych and Yusuke Miyao (Eds.). Association for Computational Linguistics, Melbourne, Australia, 877--888. https://doi.org/10.18653/v1/P18-1081

Joshua Bloch. 2006. How to design a good API and why it matters. In Companion to the 21st ACM SIGPLAN symposium on Object-oriented programming systems, languages, and applications. 506--507.

Virginia Braun and Victoria Clarke. 2006. Using thematic analysis in psychology. Qualitative research in psychology 3, 2 (2006), 77--101.

Broadcom. 2023. DLP File Reader Restarts Excessively. https://knowledge.broadcom.com/external/article/160141/dlp-file-reader-restarts-excessively.html#mcetoc_1fgibl2n0b.

John Brooke et al. 1996. SUS-A quick and dirty usability scale. Usability evaluation in industry 189, 194 (1996), 4--7.

Tanmoy Chakraborty, Sushil Jajodia, Jonathan Katz, Antonio Picariello, Giancarlo Sperli, and V. S. Subrahmanian. 2021. A Fake Online Repository Generation Engine for Cyber Deception. IEEE Transactions on Dependable and Secure Computing 18, 2 (2021), 518--533. https://doi.org/10.1109/TDSC.2019.2898661

Yu Chen, Tingxin Li, Huiming Liu, and Yang Yu. 2023. Hide and Seek (HaS): A Lightweight Framework for Prompt Privacy Protection. arXiv:2309.03057 [cs.CR] https://arxiv.org/abs/2309.03057

Yi Chen, Rui Wang, Haiyun Jiang, Shuming Shi, and Ruifeng Xu. 2023. Exploring the use of large language models for reference-free text quality evaluation: An empirical study. In Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023 (Findings). 361--374.

Cheng-Han Chiang and Hung-yi Lee. 2023. Can large language models be an alternative to human evaluations? arXiv preprint arXiv:2305.01937 (2023).

Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023. Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90% ChatGPT Quality. https://lmsys.org/blog/2023-03-30-vicuna/

Cameron Coles. 2023. 11% of data employees paste into ChatGPT is confidential. https://www.cyberhaven.com/blog/4-2-of-workers-have-pasted-company-data-into-chatgpt/. (Accessed on 08/06/2023).

Spiceworks Community. 2019. Exchange 2013-2019 Regular Expression to block SSN in external mails. - Collaboration. https://community.spiceworks.com/t/exchange-2013-2019-regular-expression-to-block-ssn-in-external-mails/1012724. (Accessed on 04/02/2024).

Ben Derico. 2024. ChatGPT bug leaked users' conversation histories. https://www.bbc.com/news/technology-65047304. (Accessed on 08/01/2024).

Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. 2006. Calibrating Noise to Sensitivity in Private Data Analysis. In Proceedings of the Third Conference on Theory of Cryptography (New York, NY) (TCC'06). Springer-Verlag, Berlin, Heidelberg, 265--284. https://doi.org/10.1007/11681878_14

Sara Evensen, Chang Ge, and Cagatay Demiralp. 2020. Ruler: Data Programming by Demonstration for Document Labeling. In Findings of the Association for Computational Linguistics: EMNLP 2020. Association for Computational Linguistics, Online, 1996--2005. https://doi.org/10.18653/v1/2020.findings-emnlp.181

Muge Fazlioglu. 2019. Beyond the nature of data: Obstacles to protecting sensitive information in the European Union and the United States. Fordham Urb. LJ 46 (2019), 271.

Kasra Ferdowsifard, Allen Ordookhanians, Hila Peleg, Sorin Lerner, and Nadia Polikarpova. 2020. Small-step live programming by example. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. 614--626.

Yao Fu, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, and Luo Mai. 2024. ServerlessLLM: Low-Latency Serverless Inference for Large Language Models. In 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI 24). USENIX Association, Santa Clara, CA, 135--153. https://www.usenix.org/conference/osdi24/presentation/fu

Sumit Gulwani. 2011. Automating string processing in spreadsheets using input-output examples. ACM Sigplan Notices 46, 1 (2011), 317--330.

Ishu Gupta, Sloni Mittal, Ankit Tiwari, Priya Agarwal, and Ashutosh Kumar Singh. 2022. TIDF-DLPM: Term and Inverse Document Frequency based Data Leakage Prevention Model. arXiv:2203.05367 [cs.CR]

José María Gómez-Hidalgo, José Miguel Martín-Abreu, Javier Nieves, Igor Santos, Felix Brezo, and Pablo G. Bringas. 2010. Data Leak Prevention through Named Entity Recognition. In 2010 IEEE Second International Conference on Social Computing. 1129--1134. https://doi.org/10.1109/SocialCom.2010.167

H2O.AI. 2023. H2O LLM EvalGPT: A Comprehensive Tool for Evaluating Large Language Models. https://h2o.ai/blog/h2o-llm-evalgpt-a-comprehensive-tool-for-evaluating-large-language-models/. (Accessed on 08/14/2023).

Hacker News. 2023. ChatGPT Enterprise. https://news.ycombinator.com/item?id=37297304. (Accessed on 04/02/2024).

Hacker News. 2023. You have to trust OpenAI follows their privacy policy. Otherwise, you shouldn't... https://news.ycombinator.com/item?id=36712936. (Accessed on 04/02/2024).

Hacker News. 2024. Employees are feeding sensitive data to ChatGPT, raising security fears | Hacker News. https://news.ycombinator.com/item?id=35330438. (Accessed on 08/01/2024).

Guntur Budi Herwanto, Gerald Quirchmayr, and A Min Tjoa. 2021. A named entity recognition based approach for privacy requirements engineering. In 2021 IEEE 29th International Requirements Engineering Conference Workshops (REW). IEEE, 406--411.

Naoise Holohan, Spiros Antonatos, Stefano Braghin, and Pól Mac Aonghusa. 2020. The Bounded Laplace Mechanism in Differential Privacy. Journal of Privacy and Confidentiality 10, 1 (2020). https://doi.org/10.29012/jpc.715

ShareGPT (https://sharegpt.com). 2023. ShareGPT dataset. https://huggingface.co/datasets/philschmid/sharegpt-raw. (Accessed on 08/06/2023).

Jeff Huang, Oren Etzioni, Luke Zettlemoyer, Kevin Clark, and Christian Lee. 2012. RevMiner: An Extractive Interface for Navigating Reviews on a Smartphone. In Proceedings of the 25th Annual ACM Symposium on User Interface Software and Technology (Cambridge, Massachusetts, USA) (UIST '12). Association for Computing Machinery, New York, NY, USA, 3--12. https://doi.org/10.1145/2380116.2380120

Alyssa Hughes. 2023. Phi-2: The Surprising Power of Small Language Models.

Bo Hui, Haolin Yuan, Neil Gong, Philippe Burlina, and Yinzhi Cao. 2024. PLeak: Prompt Leaking Attacks against Large Language Model Applications. arXiv preprint arXiv:2405.06823 (2024).

Duy Huynh. 2024. State Of LLM In 2023: A Quick Recap On Latest Advancements.

Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed. 2024. Mixtral of Experts. arXiv:2401.04088 [cs.LG]

Vanian Jonathan and Leswing Kif. 2023. ChatGPT and generative AI are booming, but the costs can be extraordinary. https://www.cnbc.com/2023/03/13/chatgpt-and-generative-ai-are-booming-but-at-a-very-expensive-price.html. (Accessed on 09/06/2023).

Zhigang Kan, Linbo Qiao, Hao Yu, Liwen Peng, Yifu Gao, and Dongsheng Li. 2023. Protecting User Privacy in Remote Conversational Systems: A Privacy-Preserving framework based on text sanitization. arXiv:2306.08223 [cs.CR] https://arxiv.org/abs/2306.08223

Sean Kandel, Andreas Paepcke, Joseph Hellerstein, and Jeffrey Heer. 2011. Wrangler: Interactive Visual Specification of Data Transformation Scripts. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Vancouver, BC, Canada) (CHI '11). Association for Computing Machinery, New York, NY, USA, 3363--3372. https://doi.org/10.1145/1978942.1979444

Clare-Marie Karat, Christine Halverson, Daniel Horn, and John Karat. 1999. Patterns of entry and correction in large vocabulary continuous speech recognition systems. In Proceedings of the SIGCHI conference on Human Factors in Computing Systems. 568--575.

Tom Kocmi and Christian Federmann. 2023. Large Language Models Are State-of-the-Art Evaluators of Translation Quality. In Proceedings of the 24th Annual Conference of the European Association for Machine Translation. European Association for Machine Translation, Tampere, Finland, 193--203. https://aclanthology.org/2023.eamt-1.19

Siqi Kou, Lanxiang Hu, Zhezhi He, Zhijie Deng, and Hao Zhang. 2024. CLLMs: Consistency Large Language Models. arXiv:2403.00835 [cs.CL]

Vu Le and Sumit Gulwani. 2014. Flashextract: A framework for data extraction by examples. In Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation. 542--553.

Wonbeom Lee, Jungi Lee, Junghwan Seo, and Jaewoong Sim. 2024. InfiniGen: Efficient Generative Inference of Large Language Models with Dynamic KV Cache Management. In 18th USENIX Symposium on Operating Systems Design and Implementation (OSDI 24). USENIX Association, Santa Clara, CA, 155--172. https://www.usenix.org/conference/osdi24/presentation/lee

Guo Lin, Wenyue Hua, and Yongfeng Zhang. 2024. EmojiCrypt: Prompt Encryption for Secure Communication with Large Language Models. arXiv:2402.05868 [cs.CL] https://arxiv.org/abs/2402.05868

Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023. Gpteval: Nlg evaluation using gpt-4 with better human alignment. arXiv preprint arXiv:2303.16634 (2023).

Zichang Liu, Jue Wang, Tri Dao, Tianyi Zhou, Binhang Yuan, Zhao Song, Anshumali Shrivastava, Ce Zhang, Yuandong Tian, Christopher Re, et al. 2023. Deja vu: Contextual sparsity for efficient llms at inference time. In International Conference on Machine Learning. PMLR, 22137--22176.

Brady D Lund and Ting Wang. 2023. Chatting about ChatGPT: how may AI and GPT impact academia and libraries? Library Hi Tech News 40, 3 (2023), 26--29.

Cecily Mauran. 2023. Samsung ChatGPT leak: Samsung bans use of AI chatbots by employees | Mashable. https://mashable.com/article/samsung-chatgpt-leak-leads-to-employee-ban. (Accessed on 08/11/2023).

Patrick E McKnight and Julius Najab. 2010. Mann-Whitney U Test. The Corsini encyclopedia of psychology (2010), 1--1.

Sachin Mehta, Mohammad Hossein Sekhavat, Qingqing Cao, Maxwell Horton, Yanzi Jin, Chenfan Sun, Iman Mirzadeh, Mahyar Najibi, Dmitry Belenko, Peter Zatloukal, and Mohammad Rastegari. 2024. OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework. arXiv:2404.14619 [cs.CL]

Meta. 2024. Introducing Meta Llama 3: The most capable openly available LLM to date. https://ai.meta.com/blog/meta-llama-3/. (Accessed on 07/27/2024).

Meta. 2024. React - The library for web and native user interfaces. http://react.dev/. (Accessed on 07/20/2024).

Chui Michael, Roberts Roger, and Yee Lareina. 2022. Generative AI is here: How tools like ChatGPT could change your business. https://www.mckinsey.com/capabilities/quantumblack/our-insights/generative-ai-is-here-how-tools-like-chatgpt-could-change-your-business (Accessed on 08/19/2023)

Louis G. Michael, James Donohue, James C. Davis, Dongyoon Lee, and Francisco Servant. 2019. Regexes are Hard: Decision-Making, Difficulties, and Risks in Programming Regular Expressions. In 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE). 415--426. https://doi.org/10.1109/ASE.2019.00047

Microsoft. 2024. Presidio: Data Protection and De-identification SDK. https://microsoft.github.io/presidio/. (Accessed on 04/01/2024).

Microsoft Learn. 2024. Mail Flow Rules (Transport Rules) in Exchange Online. https://learn.microsoft.com/en-us/exchange/security-and-compliance/mail- flow- rules/mail-flow- rules.

Arindam Mitra, Luciano Del Corro, Shweti Mahajan, Andres Codas, Clarisse Simoes, Sahaj Agarwal, Xuxi Chen, Anastasia Razdaibiedina, Erik Jones, Kriti Aggarwal, Hamid Palangi, Guoqing Zheng, Corby Rosset, Hamed Khanpour, and Ahmed Awadallah. 2023. Orca 2: Teaching Small Language Models How to Reason. arXiv:2311.11045 [cs] Comment: Added url to model weights fixed typo in Author name.

Vivek C Nair, Gonzalo Munilla-Garrido, and Dawn Song. 2023. Going Incognito in the Metaverse: Achieving Theoretically Optimal Privacy-Usability Tradeoffs in VR. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology (UIST '23). Association for Computing Machinery, New York, NY, USA, 1--16. https://doi.org/10.1145/3586183.3606754

Ben Naismith, Phoebe Mulcaire, and Jill Burstein. 2023. Automated evaluation of written discourse coherence using GPT-4. In Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023). 394--403.

Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, and Katherine Lee. 2023. Extracting Training Data from ChatGPT. https://not-just-memorization.github.io/extracting-training-data-from-chatgpt.html#patching-an-exploit-fixing-the-underlying-vulnerability.

Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tramèr, and Katherine Lee. 2023. Scalable Extraction of Training Data from (Production) Language Models. arXiv:2311.17035 [cs.LG] https://arxiv.org/abs/2311.17035

Jalagam Navaneeth, Menon Ravi, and Krishnaraj Saravanan. 2022. Common techniques to detect PHI and PII data using AWS Services. https://aws.amazon.com/blogs/industries/common-techniques-to-detect-phi-and-pii-data-using-aws-services/. (Accessed on 08/19/2023).

Palo Alto Networks. 2023. How Enterprise DLP Safeguards Against ChatGPT Data Leakage. https://docs.paloaltonetworks.com/enterprise-dlp/enterprise-dlp-admin/configure-enterprise-dlp/enterprise-dlp-and-ai-apps/how-enterprise-dlp- safeguards-against-chatgpt-data-leakage. (Accessed on 08/14/2023).

Nightfall. 2023. ChatGPT DLP Filtering: How to Use ChatGPT without Exposing Customer Data. https://www.nightfall.ai/blog/chatgpt-dlp-filtering-how-to-use-chatgpt-without-exposing-customer-data. (Accessed on 08/06/2023).

Helen Nissenbaum. 2004. Privacy as contextual integrity. Wash. L. Rev. 79 (2004), 119.

Helen Nissenbaum. 2020. Protecting privacy in an information age: The problem of privacy in public. In The ethics of information technologies. Routledge, 141--178.

Office for Civil Rights. 2021. Health Information Privacy. https://www.hhs.gov/hipaa/index.html.

OpenAI. 2023. Enterprise privacy at OpenAI. https://openai.com/enterprise-privacy. (Accessed on 09/06/2023).

OpenAI API Reference. 2022. Streaming. https://platform.openai.com/docs/api-reference/streaming. (Accessed on 07/20/2024).

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022. Training language models to follow instructions with human feedback. Advances in neural information processing systems 35 (2022), 27730--27744.

PrivateAI. 2023. Introducing PrivateGPT: A Private AI solution. https://www.private-ai.com/2023/05/01/introducing-privategpt/. (Accessed on 08/06/2023).

Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn. 2024. Direct preference optimization: Your language model is secretly a reward model. Advances in Neural Information Processing Systems 36 (2024).

Reddit users. 2023. Is there any self hosting LLM option that offers GPT3 level of performance?: r/datascience. https://www.reddit.com/r/datascience/comments/11b5xb2/is_there_any_self_hosting_llm_option_that_offers/. (Accessed on 08/14/2023).

Jie Ruan, Wenqing Wang, and Xiaojun Wan. 2024. Defining and Detecting Vulnerability in Human Evaluation Guidelines: A Preliminary Study Towards Reliable NLG Evaluation. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), Kevin Duh, Helena Gomez, and Steven Bethard (Eds.). Association for Computational Linguistics, Mexico City, Mexico, 7965--7989. https://aclanthology.org/2024.naacl-long.441

Yuri Shapira, Bracha Shapira, and Asaf Shabtai. 2013. Content-based data leakage detection using extended fingerprinting. arXiv preprint arXiv:1302.2028 (2013).

Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, and Ce Zhang. 2023. FlexGen: high-throughput generative inference of large language models with a single GPU. In Proceedings of the 40th International Conference on Machine Learning (, Honolulu, Hawaii, USA,) (ICML'23). JMLR.org, Article 1288, 23 pages.

Xiaokui Shu, Danfeng Yao, and Elisa Bertino. 2015. Privacy-preserving detection of sensitive data exposure. IEEE transactions on information forensics and security 10, 5 (2015), 1092--1103.

Mukul Singh, José Cambronero Sánchez, Sumit Gulwani, Vu Le, Carina Negreanu, Mohammad Raza, and Gust Verbruggen. 2023. Cornet: Learning Table Formatting Rules By Example. Proc. VLDB Endow. 16, 10 (aug 2023), 2632--2644. https://doi.org/10.14778/3603581.3603600

Yixin Song, Zeyu Mi, Haotong Xie, and Haibo Chen. 2023. PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU. arXiv:2312.12456 [cs.LG]

Benjamin Spector and Chris Re. 2023. Accelerating LLM Inference with Staged Speculative Decoding. arXiv:2308.04623 [cs.AI] https://arxiv.org/abs/2308.04623

Robin Staab, Mark Vero, Mislav Balunović, and Martin Vechev. 2023. Beyond Memorization: Violating Privacy Via Inference with Large Language Models. arXiv:2310.07298 [cs.AI]

State of California - Department of Justice - Office of the Attorney General. 2018. California Consumer Privacy Act (CCPA). https://oag.ca.gov/privacy/ccpa.

TIIUAE. 2023. Falcon LLM. https://falconllm.tii.ae/falcon.html?ref=blog.duy-huynh.com.

Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom. 2023. Llama 2: Open Foundation and Fine-Tuned Chat Models. arXiv:2307.09288 [cs.CL]

Rahul Tripathi, Balaji Dhamodharaswamy, Srinivasan Jagannathan, and Abhishek Nandi. 2019. Detecting Sensitive Content in Spoken Language. In 2019 IEEE International Conference on Data Science and Advanced Analytics (DSAA). 374--381. https://doi.org/10.1109/DSAA.2019.00052

James Vincent. 2023. Apple restricts employees from using ChatGPT over fear of data leaks - The Verge. https://www.theverge.com/2023/5/19/23729619/apple-bans-chatgpt-openai-fears-data-leak. (Accessed on 08/11/2023).

Chenglong Wang, Yu Feng, Rastislav Bodik, Alvin Cheung, and Isil Dillig. 2019. Visualization by Example. Proc. ACM Program. Lang. 4, POPL, Article 49 (dec 2019), 28 pages. https://doi.org/10.1145/3371117

Jiaan Wang, Yunlong Liang, Fandong Meng, Zengkui Sun, Haoxiang Shi, Zhixu Li, Jinan Xu, Jianfeng Qu, and Jie Zhou. 2023. Is ChatGPT a Good NLG Evaluator? A Preliminary Study. In Proceedings of the 4th New Frontiers in Summarization Workshop, Yue Dong, Wen Xiao, Lu Wang, Fei Liu, and Giuseppe Carenini (Eds.). Association for Computational Linguistics, Singapore, 1--11. https://doi.org/10.18653/v1/2023.newsum-1.1

Peipei Wang, Chris Brown, Jamie A Jennings, and Kathryn T Stolee. 2022. Demystifying regular expression bugs: A comprehensive study on regular expression bug causes, fixes, and testing. Empirical Software Engineering 27, 1 (2022), 21.

Yufei Wang, Wanjun Zhong, Liangyou Li, Fei Mi, Xingshan Zeng, Wenyong Huang, Lifeng Shang, Xin Jiang, and Qun Liu. 2023. Aligning Large Language Models with Human: A Survey. arXiv:2307.12966 [cs.CL] https://arxiv.org/abs/2307.12966

Robert F Woolson. 2005. Wilcoxon signed-rank test. Encyclopedia of Biostatistics 8 (2005).

Zeqiu Wu, Yushi Hu, Weijia Shi, Nouha Dziri, Alane Suhr, Prithviraj Ammanabrolu, Noah A Smith, Mari Ostendorf, and Hannaneh Hajishirzi. 2024. Fine-grained human feedback gives better rewards for language model training. Advances in Neural Information Processing Systems 36 (2024).

Daliang Xu, Wangsong Yin, Xin Jin, Ying Zhang, Shiyun Wei, Mengwei Xu, and Xuanzhe Liu. 2023. LLMCad: Fast and Scalable On-device Large Language Model Inference. arXiv:2309.04255 [cs.NI]

Rongjie Yi, Liwei Guo, Shiyun Wei, Ao Zhou, Shangguang Wang, and Mengwei Xu. 2023. EdgeMoE: Fast On-Device Inference of MoE-based Large Language Models. arXiv:2308.14352 [cs.LG] https://arxiv.org/abs/2308.14352

Wangsong Yin, Mengwei Xu, Yuanchun Li, and Xuanzhe Liu. 2024. LLM as a System Service on Mobile Devices. arXiv preprint arXiv:2403.11805 (2024).

Yifei Yuan, Rajeev Alur, and Boon Thau Loo. 2014. NetEgg: Programming network policies by examples. In Proceedings of the 13th ACM Workshop on Hot Topics in Networks. 1--7.

Mingjin Zhang, Jiannong Cao, Xiaoming Shen, and Zeyang Cui. 2024. EdgeShard: Efficient LLM Inference via Collaborative Edge Computing. arXiv:2405.14371 [cs.DC] https://arxiv.org/abs/2405.14371

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al. 2024. Judging llm-as-a-judge with mt-bench and chatbot arena. Advances in Neural Information Processing Systems 36 (2024).

Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Jeff Huang, Chuyue Sun, Cody Hao Yu, Shiyi Cao, Christos Kozyrakis, Ion Stoica, Joseph E Gonzalez, et al. 2023. Efficiently programming large language models using sglang. arXiv preprint arXiv:2312.07104 (2023).