Fetching the paper…
Reading the bibliography…
Being more powerful and intrusive into user-device interactions, LLMs are eager for on-device execution to better preserve user privacy.
Behavior Sequence Transformer for E-commerce Recommendation in Alibaba
Qiwei Chen, Huan Zhao, Wei Li, Pipei Huang, and Wenwu Ou. 2019 · 1905
Earlier work this paper cites.
Language Models are Few-Shot Learners
Tom B. Brown, Benjamin Mann, Nick Ryder, et al · 2005
Earlier work this paper cites.
Big Bird: Transformers for Longer Sequences
Manzil Zaheer, Guru Guruganesh, Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, and Amr Ahmed. 2021 · 2007
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.
Fast app launching for mobile devices using predictive user context. In Proceedings of the 10th International Conference on Mobile Systems, Applications, and Services (Low Wood Bay, Lake District, UK) (MobiSys ’12) . Association for Computing Machinery, New York, NY, USA, 113–126
Tingxin Yan, David Chu, Deepak Ganesan, Aman Kansal, and Jie Liu. 2012 · 2012
Earlier work this paper cites.
Practical prediction and prefetch for faster access to applications on mobile phones. In Proceedings of the 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Zurich, Switzerland) (UbiComp ’13) . Association for Computing Machinery, New York, NY, USA, 275–284
Abhinav Parate, Matthias Böhmer, David Chu, Deepak Ganesan, and Benjamin M. Marlin. 2013 · 2013
Earlier work this paper cites.
DR. Swap: Energy-efficient paging for smartphones. In 2014 IEEE/ACM International Symposium on Low Power Electronics and Design (ISLPED) . 81–86
Kan Zhong, Xiao Zhu, Tianzheng Wang, Dan Zhang, Xianlu Luo, Duo Liu, Weichen Liu, and Edwin H.-M. Sha. 2014 · 2014
Earlier work this paper cites.
Predicting The Next App That You Are Going To Use. In Proceedings of the Eighth ACM International Conference on Web Search and Data Mining (Shanghai, China) (WSDM ’15) . Association for Computing Machinery, New York, NY, USA, 285–294
Ricardo Baeza-Yates, Di Jiang, Fabrizio Silvestri, and Beverly Harrison. 2015 · 2015
Earlier work this paper cites.
M A R S MARS : Mobile Application Relaunching Speed-Up through Flash-Aware Page Swapping
Weichao Guo, Kang Chen, Huan Feng, Yongwei Wu, Rui Zhang, and Weimin Zheng. 2016 · 2015
Earlier work this paper cites.
Teaching Machines to Read and Comprehend. In NIPS . 1693–1701
Karl Moritz Hermann, Tomás Kociský, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Earlier work this paper cites.
Character-level Convolutional Networks for Text Classification. In NIPS
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun. 2015 · 2015
Earlier work this paper cites.
Neural Machine Translation by Jointly Learning to Align and Translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2016 · 2016
Earlier work this paper cites.
Song Han, Huizi Mao, and William J. Dally. 2016 · 2016
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.
SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Earlier work this paper cites.
Findings of the 2017 Conference on Machine Translation (WMT17). In Proceedings of the Second Conference on Machine Translation, Volume 2: Shared Task Papers . Association for Computational Linguistics, Copenhagen, Denmark, 169–214
Ond rej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shujian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, Lucia Specia, and Marco Turchi. 2017 · 2017
Earlier work this paper cites.
Application-Aware Swapping for Mobile Systems
Sang-Hoon Kim, Jinkyu Jeong, and Jin-Soo Kim. 2017 · 2017
Earlier work this paper cites.
SmartSwap: High-performance and user experience friendly swapping in mobile systems. In 2017 54th ACM/EDAC/IEEE Design Automation Conference (DAC) . 1–6
Xiao Zhu, Duo Liu, Kan Zhong, Jinting Ren, and Tao Li. 2017 · 2017
Earlier work this paper cites.
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
Earlier work this paper cites.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization. In Proceedings of the 2nd Workshop on New Frontiers in Summarization . Association for Computational Linguistics, Hong Kong, China, 70–79
Bogdan Gliwa, Iwona Mochol, Maciej Biesek, and Aleksander Wawer. 2019 · 2019
Earlier work this paper cites.
End the Senseless Killing: Improving Memory Management for Mobile Operating Systems. In 2020 USENIX Annual Technical Conference (USENIX ATC 20) . USENIX Association, 873–887
Niel Lebeck, Arvind Krishnamurthy, Henry M. Levy, and Irene Zhang. 2020 · 2020
Earlier work this paper cites.
Transformers: State-of-the-Art Natural Language Processing. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations . Association for Computational Linguistics, Online, 38–45
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi 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 M. Rush. 2020 · 2020
Earlier work this paper cites.
LoRA: Low-Rank Adaptation of Large Language Models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
Earlier work this paper cites.
PEFT: State-of-the-art Parameter-Efficient Fine-Tuning methods
Sourab Mangrulkar, Sylvain Gugger, Lysandre Debut, Younes Belkada, Sayak Paul, and Benjamin Bossan. 2022 · 2022
Earlier work this paper cites.
Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
Sewon Min, Xinxi Lyu, Ari Holtzman, Mikel Artetxe, Mike Lewis, Hannaneh Hajishirzi, and Luke Zettlemoyer. 2022 · 2022
Earlier work this paper cites.
Efficiently Scaling Transformer Inference
Reiner Pope, Sholto Douglas, Aakanksha Chowdhery, Jacob Devlin, James Bradbury, Anselm Levskaya, Jonathan Heek, Kefan Xiao, Shivani Agrawal, and Jeff Dean. 2022 · 2022
Cited alongside, same era.
Orca: A Distributed Serving System for Transformer-Based Generative Models. In 16th USENIX Symposium on Operating Systems Design and Implementation (OSDI 22) . USENIX Association, Carlsbad, CA, 521–538
Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, and Byung-Gon Chun. 2022 · 2022
Cited alongside, same era.
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
Cited alongside, same era.
OpenAI: Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, et al · 2023
EdgeMoE: Fast On-Device Inference of MoE-based Large Language Models
Rongjie Yi, Liwei Guo, Shiyun Wei, Ao Zhou, Shangguang Wang, and Mengwei Xu. 2023 · 2023
Later among the works it cites.
Rethinking Mobile AI Ecosystem in the LLM Era
Jinliang Yuan, Chen Yang, Dongqi Cai, Shihe Wang, Xin Yuan, Zeling Zhang, Xiang Li, Dingge Zhang, Hanzi Mei, Xianqing Jia, Shangguang Wang, and Mengwei Xu. 2023 · 2023
Later among the works it cites.
H 2 O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models
Zhenyu Zhang, Ying Sheng, Tianyi Zhou, Tianlong Chen, Lianmin Zheng, Ruisi Cai, Zhao Song, Yuandong Tian, Christopher Ré, Clark Barrett, Zhangyang Wang, and Beidi Chen. 2023 · 2023
Later among the works it cites.
Atom: Low-bit Quantization for Efficient and Accurate LLM Serving
Yilong Zhao, Chien-Yu Lin, Kan Zhu, Zihao Ye, Lequn Chen, Size Zheng, Luis Ceze, Arvind Krishnamurthy, Tianqi Chen, and Baris Kasikci. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
The Falcon Series of Open Language Models
Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, Alessandro Cappelli, Ruxandra Cojocaru, Mérouane Debbah, Étienne Goffinet, Daniel Hesslow, Julien Launay, Quentin Malartic, Daniele Mazzotta, Badreddine Noune, Baptiste Pannier, and Guilherme Penedo. 2023 · 2023
Cited alongside, same era.
Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality
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 · 2023
Cited alongside, same era.
A Survey on In-context Learning
Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Zhiyong Wu, Baobao Chang, Xu Sun, Jingjing Xu, Lei Li, and Zhifang Sui. 2023 · 2023
Cited alongside, same era.
GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers
Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh. 2023 · 2023
Cited alongside, same era.
Prompt Cache: Modular Attention Reuse for Low-Latency Inference
In Gim, Guojun Chen, Seung seob Lee, Nikhil Sarda, Anurag Khandelwal, and Lin Zhong. 2023 · 2023
Cited alongside, same era.
CogAgent: A Visual Language Model for GUI Agents
Wenyi Hong, Weihan Wang, Qingsong Lv, Jiazheng Xu, Wenmeng Yu, Junhui Ji, Yan Wang, Zihan Wang, Yuxuan Zhang, Juanzi Li, Bin Xu, Yuxiao Dong, Ming Ding, and Jie Tang. 2023 · 2023
Cited alongside, same era.
Efficient Memory Management for Large Language Model Serving with PagedAttention. In Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica. 2023 · 2023
Cited alongside, same era.
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee. 2023 · 2023
Cited alongside, same era.
Efficiently Programming Large Language Models using SGLang
Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Jeff Huang, Chuyue Sun, Cody Hao Yu, Shiyi Cao, Christos Kozyrakis, Ion Stoica, Joseph E. Gonzalez, Clark Barrett, and Ying Sheng. 2023 · 2023
Later among the works it cites.
Andriod low-memory killer
2024 · 2024
Closest in time.
Gboard Smart Reply
2024 · 2024
Closest in time.
GPT-based email writer
2024 · 2024
Closest in time.
GPT4-Turbo
2024 · 2024
Closest in time.
Jetson Orin NX
2024 · 2024
Closest in time.
Jetson TX2
2024 · 2024
Closest in time.
Large Language Models On-Device with MediaPipe and TensorFlow Lite
2024 · 2024
Closest in time.
Llama.cpp
2024 · 2024
Closest in time.
LLM-based AI-Assistant
2024 · 2024
Closest in time.
LLM customer service and support
2024 · 2024
Closest in time.
LLM telegram chatbot
2024 · 2024
Closest in time.
LM Deploy
2024 · 2024
Closest in time.
MI14 smartphone
2024 · 2024
Closest in time.
News Summarization with LLM
2024 · 2024
Closest in time.
Snapdragon 8 gen 3 mobile platform product brief
2024 · 2024
Closest in time.
APIServe: Efficient API Support for Large-Language Model Inferencing
Reyna Abhyankar, Zijian He, Vikranth Srivatsa, Hao Zhang, and Yiying Zhang. 2024 · 2024
Closest in time.
LLM in a flash: Efficient Large Language Model Inference with Limited Memory
Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko, Karen Khatamifard, Minsik Cho, Carlo C Del Mundo, Mohammad Rastegari, and Mehrdad Farajtabar. 2024 · 2024
Closest in time.
Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security
Yuanchun Li, Hao Wen, Weijun Wang, Xiangyu Li, Yizhen Yuan, Guohong Liu, Jiacheng Liu, Wenxing Xu, Xiang Wang, Yi Sun, Rui Kong, Yile Wang, Hanfei Geng, Jian Luan, Xuefeng Jin, Zilong Ye, Guanjing Xiong, Fan Zhang, Xiang Li, Mengwei Xu, Zhijun Li, Peng Li, Yang Liu, Ya-Qin Zhang, and Yunxin Liu. 2024 · 2024
Closest in time.
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Shuming Ma, Hongyu Wang, Lingxiao Ma, Lei Wang, Wenhui Wang, Shaohan Huang, Li Dong, Ruiping Wang, Jilong Xue, and Furu Wei. 2024 · 2024
Closest in time.
DroidBot-GPT: GPT-powered UI Automation for Android
Hao Wen, Hongming Wang, Jiaxuan Liu, and Yuanchun Li. 2024 · 2024
Closest in time.