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With the rapid development of large language models (LLMs), which possess powerful natural language processing and generation capabilities, LLMs are poised to provide more natural and personalized user experiences.
Song Han, Huizi Mao, and William J Dally · 2015
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Distilling the knowledge in a neural network
Geoffrey Hinton · 2015
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Singular point probability improve lstm network performance for long-term traffic flow prediction
Boyi Liu, Jieren Cheng, Kuanqi Cai, Pengchao Shi, and Xiangyan Tang · 2017
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Attention is all you need
A Vaswani · 2017
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Federated imitation learning: A novel framework for cloud robotic systems with heterogeneous sensor data
Boyi Liu, Lujia Wang, Ming Liu, and Cheng-Zhong Xu · 2019
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Lifelong federated reinforcement learning: a learning architecture for navigation in cloud robotic systems
Boyi Liu, Lujia Wang, Ming Liu, and Cheng-Zhong Xu · 2019
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Language models are few-shot learners
Tom B Brown · 2020
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Experiments of federated learning for covid-19 chest x-ray images
Boyi Liu, Bingjie Yan, Yize Zhou, Yifan Yang, and Yixian Zhang · 2020
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Mdinference: Balancing inference accuracy and latency for mobile applications
Samuel S Ogden and Tian Guo · 2020
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Energy-efficient deep learning inference on edge devices
Francesco Daghero, Daniele Jahier Pagliari, and Massimo Poncino · 2021
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Peer-assisted robotic learning: a data-driven collaborative learning approach for cloud robotic systems
Boyi Liu, Lujia Wang, Xinquan Chen, Lexiong Huang, Dong Han, and Cheng-Zhong Xu · 2021
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Fully integrated data communication framework by using visualization augmented reality for internet of things networks
Kashif Naseer Qureshi, Adi Alhudhaif, Raja Waseem Anwar, Shahid Nazir Bhati, and Gwanggil Jeon · 2021
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Fedcm: A real-time contribution measurement method for participants in federated learning
Bingjie Yan, Boyi Liu, Lujia Wang, Yize Zhou, Zhixuan Liang, Ming Liu, and Cheng-Zhong Xu · 2021
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Open-source multi-access edge computing for 6g: Opportunities and challenges
Liqiang Zhao, Guorong Zhou, Gan Zheng, I Chih-Lin, Xiaohu You, and Lajos Hanzo · 2021
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Hardware approximate techniques for deep neural network accelerators: A survey
Giorgos Armeniakos, Georgios Zervakis, Dimitrios Soudris, and Jörg Henkel · 2022
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Enabling real-time ai inference on mobile devices via gpu-cpu collaborative execution
Hao Li, Joseph K Ng, and Tarek Abdelzaher · 2022
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Elasticros: An elastically collaborative robot operation system for fog and cloud robotics
Boyi Liu, Lujia Wang, and Ming Liu · 2022
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Application of artificial intelligence in wearable devices: Opportunities and challenges
Darius Nahavandi, Roohallah Alizadehsani, Abbas Khosravi, and U Rajendra Acharya · 2022
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Efficient acceleration of deep learning inference on resource-constrained edge devices: A review
Md Maruf Hossain Shuvo, Syed Kamrul Islam, Jianlin Cheng, and Bashir I Morshed · 2022
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Authros: Secure data sharing among robot operating systems based on ethereum
Shenhui Zhang, Wenkai Li, Xiaoqi Li, and Boyi Liu · 2022
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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
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Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges
Zhaohua Zheng, Yize Zhou, Yilong Sun, Zhang Wang, Boyi Liu, and Keqiu Li · 2022
A systematic review of research on speech-recognition chatbots for language learning: Implications for future directions in the era of large language models
Jaeho Jeon, Seongyong Lee, and Seongyune Choi · 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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Llm-slice: Dedicated wireless network slicing for large language models
Boyi Liu, Jingwen Tong, and Jun Zhang · 2024
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Boyi Liu, Jingwen Tong, and Yufan Zhuang · 2024
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Offline textual adversarial attacks against large language models
Huijun Liu, Bin Ji, Jie Yu, Shasha Li, Jun Ma, Miaomiao Li, and Xi Wang · 2024
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Transformers in speech processing: A survey
Siddique Latif, Aun Zaidi, Heriberto Cuayahuitl, Fahad Shamshad, Moazzam Shoukat, and Junaid Qadir · 2023
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Roboec2: A novel cloud robotic system with dynamic network offloading assisted by amazon ec2
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Translation performance from the user’s perspective of large language models and neural machine translation systems
Jungha Son and Boyoung Kim · 2023
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Xr and ai: Ai-enabled virtual, augmented, and mixed reality
Ryo Suzuki, Mar Gonzalez-Franco, Misha Sra, and David Lindlbauer · 2023
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Large language models in medicine
Arun James Thirunavukarasu, Darren Shu Jeng Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, and Daniel Shu Wei Ting · 2023
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Understanding computational dialogue understanding
Wolfgang Wahlster · 2023
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Recommender systems in the era of large language models (llms)
Zihuai Zhao, Wenqi Fan, Jiatong Li, Yunqing Liu, Xiaowei Mei, Yiqi Wang, Zhen Wen, Fei Wang, Xiangyu Zhao, Jiliang Tang, et al · 2023
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Preserving privacy in large language models: A survey on current threats and solutions
Michele Miranda, Elena Sofia Ruzzetti, Andrea Santilli, Fabio Massimo Zanzotto, Sébastien Bratières, and Emanuele Rodolà · 2024
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Large language models in healthcare and medical domain: A review
Zabir Al Nazi and Wei Peng · 2024
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Llamaduo: Llmops pipeline for seamless migration from service llms to small-scale local llms
Chansung Park, Juyong Jiang, Fan Wang, Sayak Paul, and Jing Tang · 2024
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Mobile edge intelligence for large language models: A contemporary survey
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Mobilequant: Mobile-friendly quantization for on-device language models
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On-device language models: A comprehensive review
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Emerging synergies between large language models and machine learning in ecommerce recommendations
Xiaonan Xu, Zheng Xu, Zhipeng Ling, Zhengyu Jin, and ShuQian Du · 2024
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On protecting the data privacy of large language models (llms): A survey
Biwei Yan, Kun Li, Minghui Xu, Yueyan Dong, Yue Zhang, Zhaochun Ren, and Xiuzhen Cheng · 2024
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Elms: Elasticized large language models on mobile devices
Wangsong Yin, Rongjie Yi, Daliang Xu, Gang Huang, Mengwei Xu, and Xuanzhe Liu · 2024
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Recommender systems in the era of large language models (llms)
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A review on edge large language models: Design, execution, and applications
Yue Zheng, Yuhao Chen, Bin Qian, Xiufang Shi, Yuanchao Shu, and Jiming Chen · 2024
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