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Deploying Large Language Models (LLMs) locally on mobile devices presents a significant challenge due to their extensive memory requirements.
PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 1912
Earlier work this paper cites.
Scaling Laws for Neural Language Models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B. Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
Earlier work this paper cites.
Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2005
Earlier work this paper cites.
Measuring Massive Multitask Language Understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2009
Earlier work this paper cites.
Limitations of Autoregressive Models and Their Alternatives
Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley, and Jason Eisner. 2021 · 2010
Earlier work this paper cites.
Learning Word Vectors for Sentiment Analysis. In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies . Association for Computational Linguistics, Portland, Oregon, USA, 142–150
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
Earlier work this paper cites.
Pointer Sentinel Mixture Models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher. 2016 · 2016
Earlier work this paper cites.
Modnn: Local distributed mobile computing system for deep neural network. In Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017 . IEEE, 1396–1401
Jiachen Mao, Xiang Chen, Kent W Nixon, Christopher Krieger, and Yiran Chen. 2017a · 2017
Earlier work this paper cites.
A survey on mobile edge computing: The communication perspective
Yuyi Mao, Changsheng You, Jun Zhang, Kaibin Huang, and Khaled B Letaief. 2017b · 2017
Earlier work this paper cites.
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning
Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Meghan Cowan, Haichen Shen, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, and Arvind Krishnamurthy. 2018 · 2018
Earlier work this paper cites.
A survey on methods and theories of quantized neural networks
Yunhui Guo. 2018 · 2018
Earlier work this paper cites.
ONNX: Open Neural Network Exchange
Junjie Bai, Fang Lu, Ke Zhang, et al · 2019
Earlier work this paper cites.
Deep learning with edge computing: A review
Jiasi Chen and Xukan Ran. 2019 · 2019
Earlier work this paper cites.
Wireless edge computing with latency and reliability guarantees
Mohammed S Elbamby, Cristina Perfecto, Chen-Feng Liu, Jihong Park, Sumudu Samarakoon, Xianfu Chen, and Mehdi Bennis. 2019 · 2019
Earlier work this paper cites.
Deephome: Distributed inference with heterogeneous devices in the edge. In The 3rd International Workshop on Deep Learning for Mobile Systems and Applications . 13–18
Zhiming Hu, Ahmad Bisher Tarakji, Vishal Raheja, Caleb Phillips, Teng Wang, and Iqbal Mohomed. 2019 · 2019
Earlier work this paper cites.
Tinybert: Distilling bert for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu. 2019 · 2019
Earlier work this paper cites.
Wireless network intelligence at the edge
Jihong Park, Sumudu Samarakoon, Mehdi Bennis, and Mérouane Debbah. 2019 · 2019
Earlier work this paper cites.
Machine learning at facebook: Understanding inference at the edge. In 2019 IEEE international symposium on high performance computer architecture (HPCA) . IEEE, 331–344
Carole-Jean Wu, David Brooks, Kevin Chen, Douglas Chen, Sy Choudhury, Marat Dukhan, Kim Hazelwood, Eldad Isaac, Yangqing Jia, Bill Jia, et al · 2019
Earlier work this paper cites.
Deep learning in mobile and wireless networking: A survey
Chaoyun Zhang, Paul Patras, and Hamed Haddadi. 2019 · 2019
Earlier work this paper cites.
Adaptive Parallel Execution of Deep Neural Networks on Heterogeneous Edge Devices. In Proceedings of the 4th ACM/IEEE Symposium on Edge Computing (Arlington, Virginia) (SEC ’19) . Association for Computing Machinery, New York, NY, USA, 195–208
Li Zhou, Mohammad Hossein Samavatian, Anys Bacha, Saikat Majumdar, and Radu Teodorescu. 2019 · 2019
Earlier work this paper cites.
What is the state of neural network pruning?
Davis Blalock, Jose Javier Gonzalez Ortiz, Jonathan Frankle, and John Guttag. 2020 · 2020
Earlier work this paper cites.
GPT-3: Its Nature, Scope, Limits, and Consequences
Luciano Floridi and Massimo Chiriatti. 2020 · 2020
Earlier work this paper cites.
SwapAdvisor: Pushing Deep Learning Beyond the GPU Memory Limit via Smart Swapping. In Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems (Lausanne, Switzerland) (ASPLOS ’20) . Association for Computing Machinery, New York, NY, USA, 1341–1355
Chien-Chin Huang, Gu Jin, and Jinyang Li. 2020 · 2020
Earlier work this paper cites.
Toward edge-based deep learning in industrial Internet of Things
Fan Liang, Wei Yu, Xing Liu, David Griffith, and Nada Golmie. 2020b · 2020
Cited alongside, same era.
Mixkd: Towards efficient distillation of large-scale language models
Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, and Lawrence Carin. 2020a · 2020
Cited alongside, same era.
Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining . 3505–3506
Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He. 2020 · 2020
Cited alongside, same era.
CoEdge: Cooperative DNN Inference With Adaptive Workload Partitioning Over Heterogeneous Edge Devices
Liekang Zeng, Xu Chen, Zhi Zhou, Lei Yang, and Junshan Zhang. 2021 · 2020
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Understanding and overcoming the challenges of efficient transformer quantization
Distributed Assignment With Load Balancing for DNN Inference at the Edge
Yuzhe Xu, Thaha Mohammed, Mario Di Francesco, and Carlo Fischione. 2022 · 2022
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Zeroquant: Efficient and affordable post-training quantization for large-scale transformers
Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, and Yuxiong He. 2022 · 2022
Later among the works it cites.
OPT: Open Pre-trained Transformer Language Models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, Todor Mihaylov, Myle Ott, Sam Shleifer, Kurt Shuster, Daniel Simig, Punit Singh Koura, Anjali Sridhar, Tianlu Wang, and Luke Zettlemoyer. 2022 · 2022
Later among the works it cites.
A survey of deep learning on mobile devices: Applications, optimizations, challenges, and research opportunities
Tianming Zhao, Yucheng Xie, Yan Wang, Jerry Cheng, Xiaonan Guo, Bin Hu, and Yingying Chen. 2022 · 2022
Later among the works it cites.
GitHub Copilot · Your AI pair programmer
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Yelysei Bondarenko, Markus Nagel, and Tijmen Blankevoort. 2021 · 2021
Cited alongside, same era.
Training Verifiers to Solve Math Word Problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021 · 2021
Cited alongside, same era.
Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors
Claudionor N Coelho, Aki Kuusela, Shan Li, Hao Zhuang, Jennifer Ngadiuba, Thea Klaeboe Aarrestad, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, and Sioni Summers. 2021 · 2021
Cited alongside, same era.
Sparsity in deep learning: Pruning and growth for efficient inference and training in neural networks
Torsten Hoefler, Dan Alistarh, Tal Ben-Nun, Nikoli Dryden, and Alexandra Peste. 2021 · 2021
Cited alongside, same era.
Pruning and quantization for deep neural network acceleration: A survey
Tailin Liang, John Glossner, Lei Wang, Shaobo Shi, and Xiaotong Zhang. 2021 · 2021
Cited alongside, same era.
Low latency deep learning inference model for distributed intelligent IoT edge clusters
Soumyalatha Naveen, Manjunath R Kounte, and Mohammed Riyaz Ahmed. 2021 · 2021
Cited alongside, same era.
{ \{ INFaaS } \} : Automated model-less inference serving. In 2021 USENIX Annual Technical Conference (USENIX ATC 21) . 397–411
Francisco Romero, Qian Li, Neeraja J Yadwadkar, and Christos Kozyrakis. 2021 · 2021
Cited alongside, same era.
Revisiting Neural Scaling Laws in Language and Vision
Ibrahim Alabdulmohsin, Behnam Neyshabur, and Xiaohua Zhai. 2022 · 2022
Cited alongside, same era.
[n. d.] · 2023
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Knowledge Distillation of Large Language Models
Yuxian Gu, Li Dong, Furu Wei, and Minlie Huang. 2023 · 2023
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Gurobi Optimizer Reference Manual
Gurobi Optimization, LLC. 2023 · 2023
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Cybercrime and Privacy Threats of Large Language Models
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A Mathematical Interpretation of Autoregressive Generative Pre-Trained Transformer and Self-Supervised Learning
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BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
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Nguyen, Edward Tan, Emi Baylor, Ezinwanne Ozoani, Fatima Mirza, Frankline Ononiwu, Habib Rezanejad, Hessie Jones, Indrani Bhattacharya, Irene Solaiman, Irina Sedenko, Isar Nejadgholi, Jesse Passmore, Josh Seltzer, Julio Bonis Sanz, Livia Dutra, Mairon Samagaio, Maraim Elbadri, Margot Mieskes, Marissa Gerchick, Martha Akinlolu, Michael McKenna, Mike Qiu, Muhammed Ghauri, Mykola Burynok, Nafis Abrar, Nazneen Rajani, Nour Elkott, Nour Fahmy, Olanrewaju Samuel, Ran An, Rasmus Kromann, Ryan Hao, Samira Alizadeh, Sarmad Shubber, Silas Wang, Sourav Roy, Sylvain Viguier, Thanh Le, Tobi Oyebade, Trieu Le, Yoyo Yang, Zach Nguyen, Abhinav Ramesh Kashyap, Alfredo Palasciano, Alison Callahan, Anima Shukla, Antonio Miranda-Escalada, Ayush Singh, Benjamin Beilharz, Bo Wang, Caio Brito, Chenxi Zhou, Chirag Jain, Chuxin Xu, Clémentine Fourrier, Daniel León Periñán, Daniel Molano, Dian Yu, Enrique Manjavacas, Fabio Barth, Florian Fuhrimann, Gabriel Altay, Giyaseddin Bayrak, Gully Burns, Helena U. Vrabec, Imane Bello, Ishani Dash, Jihyun Kang, John Giorgi, Jonas Golde, Jose David Posada, Karthik Rangasai Sivaraman, Lokesh Bulchandani, Lu Liu, Luisa Shinzato, Madeleine Hahn de Bykhovetz, Maiko Takeuchi, Marc Pàmies, Maria A Castillo, Marianna Nezhurina, Mario Sänger, Matthias Samwald, Michael Cullan, Michael Weinberg, Michiel De Wolf, Mina Mihaljcic, Minna Liu, Moritz Freidank, Myungsun Kang, Natasha Seelam, Nathan Dahlberg, Nicholas Michio Broad, Nikolaus Muellner, Pascale Fung, Patrick Haller, Ramya Chandrasekhar, Renata Eisenberg, Robert Martin, Rodrigo Canalli, Rosaline Su, Ruisi Su, Samuel Cahyawijaya, Samuele Garda, Shlok S Deshmukh, Shubhanshu Mishra, Sid Kiblawi, Simon Ott, Sinee Sang-aroonsiri, Srishti Kumar, Stefan Schweter, Sushil Bharati, Tanmay Laud, Théo Gigant, Tomoya Kainuma, Wojciech Kusa, Yanis Labrak, Yash Shailesh Bajaj, Yash Venkatraman, Yifan Xu, Yingxin Xu, Yu Xu, Zhe Tan, Zhongli Xie, Zifan Ye, Mathilde Bras, Younes Belkada, and Thomas Wolf. 2023 · 2023
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