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Large Language Models (LLMs) enable various applications on edge devices such as smartphones, wearables, and embodied robots.
Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Caglar Gulcehre, Bing Xiang, et al · 2016
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Conditional deep learning for energy-efficient and enhanced pattern recognition
Priyadarshini Panda, Abhronil Sengupta, and Kaushik Roy · 2016
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Branchynet: Fast inference via early exiting from deep neural networks
Surat Teerapittayanon, Bradley McDanel, and Hsiang-Tsung Kung · 2016
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Language models are few-shot learners
Tom B Brown · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde De Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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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, et al · 2021
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Emergent abilities of large language models
Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, et al · 2022
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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, et al · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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6g mobile communication technology: Requirements, targets, applications, challenges, advantages, and opportunities
Mohammed Banafaa, Ibraheem Shayea, Jafri Din, Marwan Hadri Azmi, Abdulaziz Alashbi, Yousef Ibrahim Daradkeh, and Abdulraqeb Alhammadi · 2023
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Ee-llm: Large-scale training and inference of early-exit large language models with 3d parallelism
Yanxi Chen, Xuchen Pan, Yaliang Li, Bolin Ding, and Jingren Zhou · 2023
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Fast inference from transformers via speculative decoding
Yaniv Leviathan, Matan Kalman, and Yossi Matias · 2023
Cited alongside, same era.
Pushing large language models to the 6g edge: Vision, challenges, and opportunities
Zheng Lin, Guanqiao Qu, Qiyuan Chen, Xianhao Chen, Zhe Chen, and Kaibin Huang · 2023
Cited alongside, same era.
From words to watts: Benchmarking the energy costs of large language model inference
Siddharth Samsi, Dan Zhao, Joseph McDonald, Baolin Li, Adam Michaleas, Michael Jones, William Bergeron, Jeremy Kepner, Devesh Tiwari, and Vijay Gadepally · 2023
Cited alongside, same era.
Stanford alpaca: An instruction-following llama model, 2023
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B Hashimoto · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
A survey on large language models with multilingualism: Recent advances and new frontiers
Kaiyu Huang, Fengran Mo, Hongliang Li, You Li, Yuanchi Zhang, Weijian Yi, Yulong Mao, Jinchen Liu, Yuzhuang Xu, Jinan Xu, et al · 2024
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Eagle-2: Faster inference of language models with dynamic draft trees
Yuhui Li, Fangyun Wei, Chao Zhang, and Hongyang Zhang · 2024
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Awq: Activation-aware weight quantization for on-device llm compression and acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, and Song Han · 2024
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Small language models: Survey, measurements, and insights
Zhenyan Lu, Xiang Li, Dongqi Cai, Rongjie Yi, Fangming Liu, Xiwen Zhang, Nicholas D Lane, and Mengwei Xu · 2024
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Cited alongside, same era.
Large language models for robotics: A survey
Fanlong Zeng, Wensheng Gan, Yongheng Wang, Ning Liu, and Philip S Yu · 2023
Cited alongside, same era.
A survey on language models for code
Ziyin Zhang, Chaoyu Chen, Bingchang Liu, Cong Liao, Zi Gong, Hang Yu, Jianguo Li, and Rui Wang · 2023
Cited alongside, same era.
Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2023
Cited alongside, same era.
Spatialvlm: Endowing vision-language models with spatial reasoning capabilities
Boyuan Chen, Zhuo Xu, Sean Kirmani, Brain Ichter, Dorsa Sadigh, Leonidas Guibas, and Fei Xia · 2024
Cited alongside, same era.
Navila: Legged robot vision-language-action model for navigation
An-Chieh Cheng, Yandong Ji, Zhaojing Yang, Zaitian Gongye, Xueyan Zou, Jan Kautz, Erdem Bıyık, Hongxu Yin, Sifei Liu, and Xiaolong Wang · 2024
Cited alongside, same era.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
Cited alongside, same era.
Not all layers of llms are necessary during inference
Siqi Fan, Xin Jiang, Xiang Li, Xuying Meng, Peng Han, Shuo Shang, Aixin Sun, Yequan Wang, and Zhongyuan Wang · 2024
Cited alongside, same era.
Bradley McDanel · 2024
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Mobile edge intelligence for large language models: A contemporary survey
Guanqiao Qu, Qiyuan Chen, Wei Wei, Zheng Lin, Xianhao Chen, and Kaibin Huang · 2024
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Mixture-of-depths: Dynamically allocating compute in transformer-based language models
David Raposo, Sam Ritter, Blake Richards, Timothy Lillicrap, Peter Conway Humphreys, and Adam Santoro · 2024
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A survey of neural code intelligence: Paradigms, advances and beyond
Qiushi Sun, Zhirui Chen, Fangzhi Xu, Kanzhi Cheng, Chang Ma, Zhangyue Yin, Jianing Wang, Chengcheng Han, Renyu Zhu, Shuai Yuan, et al · 2024
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Gemma: Open models based on gemini research and technology
Gemma Team, Thomas Mesnard, Cassidy Hardin, Robert Dadashi, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Sanjay Kale, Juliette Love, et al · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, et al · 2024
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Minghao Yan, Saurabh Agarwal, and Shivaram Venkataraman · 2024
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Zhongzhi Yu, Zheng Wang, Yuhan Li, Haoran You, Ruijie Gao, Xiaoya Zhou, Sreenidhi Reedy Bommu, Yang Katie Zhao, and Yingyan Celine Lin · 2024
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Edgeshard: Efficient llm inference via collaborative edge computing
Mingjin Zhang, Jiannong Cao, Xiaoming Shen, and Zeyang Cui · 2024
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