Privacy-preserved LLM Cascade via CoT-enhanced Policy Learning

Rethinking classification and localization for cascade r-cnn

Original

Ang Li, Xue Yang, and Chongyang Zhang. 2019 · 1907

Earlier work this paper cites.

Rapid object detection using a boosted cascade of simple features

Paul Viola and Michael Jones. 2001 · 2001

Earlier work this paper cites.

A semisupervised cascade classification algorithm

Stamatis Karlos, Nikos Fazakis, Sotiris Kotsiantis, and Kyriakos Sgarbas. 2016 · 2016

Earlier work this paper cites.

Automatic differentiation in pytorch

Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer. 2017 · 2017

Earlier work this paper cites.

Proximal policy optimization algorithms

Original

John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017

Earlier work this paper cites.

Decoupled weight decay regularization

Ilya Loshchilov and Frank Hutter. 2018 · 2018

Earlier work this paper cites.

Language models are unsupervised multitask learners

Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019

Earlier work this paper cites.

Transformers: State-of-the-art natural language processing

Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020

Earlier work this paper cites.

Training verifiers to solve math word problems, 2021

Original

Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al. 2021 · 2021

Earlier work this paper cites.

Do prompt-based models really understand the meaning of their prompts?

Original

Albert Webson and Ellie Pavlick. 2021 · 2021

Earlier work this paper cites.

Emailsum: Abstractive email thread summarization

Shiyue Zhang, Asli Celikyilmaz, Jianfeng Gao, and Mohit Bansal. 2021 · 2021

Earlier work this paper cites.

Gpt-4 technical report

Original

Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023

Earlier work this paper cites.

Tryage: Real-time, intelligent routing of user prompts to large language model

Original

Surya Narayanan Hari and Matt Thomson. 2023 · 2023

Earlier work this paper cites.

Cascaded machine learning model based dos attacks detection and classification in noc

Shengkai Hu, Haoyu Wang, and Basel Halak. 2023 · 2023

Earlier work this paper cites.

Preserving privacy through dememorization: An unlearning technique for mitigating memorization risks in language models

Aly Kassem, Omar Mahmoud, and Sherif Saad. 2023 · 2023

Earlier work this paper cites.

Orchestrallm: Efficient orchestration of language models for dialogue state tracking

Original

Chia-Hsuan Lee, Hao Cheng, and Mari Ostendorf. 2023 · 2023

Earlier work this paper cites.

Reflection-tuning: Data recycling improves llm instruction-tuning

Original

Ming Li, Lichang Chen, Jiuhai Chen, Shwai He, Heng Huang, Jiuxiang Gu, and Tianyi Zhou. 2023 · 2023

Earlier work this paper cites.

Automix: Automatically mixing language models

Original

Aman Madaan, Pranjal Aggarwal, Ankit Anand, Srividya Pranavi Potharaju, Swaroop Mishra, Pei Zhou, Aditya Gupta, Dheeraj Rajagopal, Karthik Kappaganthu, Yiming Yang, et al. 2023 · 2023

Earlier work this paper cites.

Large language model routing with benchmark datasets

Original

Tal Shnitzer, Anthony Ou, Mírian Silva, Kate Soule, Yuekai Sun, Justin Solomon, Neil Thompson, and Mikhail Yurochkin. 2023 · 2023

Cited alongside, same era.

Llama: Open and efficient foundation language models

Original

Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023 · 2023

Cited alongside, same era.

Tabi: An efficient multi-level inference system for large language models

Yiding Wang, Kai Chen, Haisheng Tan, and Kun Guo. 2023 · 2023

Cited alongside, same era.

Llmcad: Fast and scalable on-device large language model inference

Original

Daliang Xu, Wangsong Yin, Xin Jin, Ying Zhang, Shiyun Wei, Mengwei Xu, and Xuanzhe Liu. 2023 · 2023

Cited alongside, same era.

Mars: A benchmark for multi-llm algorithmic routing system

Qitian Jason Hu, Jacob Bieker, Xiuyu Li, Nan Jiang, Benjamin Keigwin, Gaurav Ranganath, Kurt Keutzer, and Shriyash Kaustubh Upadhyay. 2024a · 2024

Closest in time.

Preventing health data from leaking in a machine learning system: Implementing code analysis with llm and model privacy evaluation testing

Balder Janryd and Tim Johansson. 2024 · 2024

Closest in time.

When does confidence-based cascade deferral suffice?

Wittawat Jitkrittum, Neha Gupta, Aditya K Menon, Harikrishna Narasimhan, Ankit Rawat, and Sanjiv Kumar. 2024 · 2024

Closest in time.

Propile: Probing privacy leakage in large language models

Siwon Kim, Sangdoo Yun, Hwaran Lee, Martin Gubri, Sungroh Yoon, and Seong Joon Oh. 2024 · 2024

Closest in time.

Complying with hipaa and hitech

Susan Lincke. 2024 · 2024

Closest in time.

Llamoco: Instruction tuning of large language models for optimization code generation