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Transformer-based large language models (LLMs) demonstrate impressive performance across various natural language processing tasks.
The penn treebank: Annotating predicate argument structure
Mitch Marcus, Grace Kim, Mary Ann Marcinkiewicz, Robert MacIntyre, Ann Bies, Mark Ferguson, Karen Katz, and Britta Schasberger · 1994
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Choice of plausible alternatives: An evaluation of commonsense causal reasoning
Melissa Roemmele, Cosmin Bejan, and Andrew Gordon · 2011
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le · 2014
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Clipper: A low-latency online prediction serving system
Daniel Crankshaw, Xin Wang, Guilio Zhou, Michael J Franklin, Joseph E Gonzalez, and Ion Stoica · 2017
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Pointer sentinel mixture models
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher · 2017
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Tensorflow-serving: Flexible, high-performance ml serving
Christopher Olston, Noah Fiedel, Kiril Gorovoy, Jeremiah Harmsen, Li Lao, Fangwei Li, Vinu Rajashekhar, Sukriti Ramesh, and Jordan Soyke · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin · 2017
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin · 2018
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Dragon: Breaking gpu memory capacity limits with direct nvm access
Pak Markthub, Mehmet E. Belviranli, Seyong Lee, Jeffrey S. Vetter, and Satoshi Matsuoka · 2018
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Training millions of personalized dialogue agents
Pierre-Emmanuel Mazare, Samuel Humeau, Martin Raison, and Antoine Bordes · 2018
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Can a suit of armor conduct electricity? a new dataset for open book question answering
Todor Mihaylov, Peter Clark, Tushar Khot, and Ashish Sabharwal · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman · 2018
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Dynamic control flow in large-scale machine learning
Yuan Yu, Martín Abadi, Paul Barham, Eugene Brevdo, Mike Burrows, Andy Davis, Jeff Dean, Sanjay Ghemawat, Tim Harley, Peter Hawkins, et al · 2018
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Personalizing dialogue agents: I have a dog, do you have pets too?
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston · 2018
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Generating long sequences with sparse transformers
Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever · 2019
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Nexus: A gpu cluster engine for accelerating dnn-based video analysis
Haichen Shen, Lequn Chen, Yuchen Jin, Liangyu Zhao, Bingyu Kong, Matthai Philipose, Arvind Krishnamurthy, and Ravi Sundaram · 2019
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Pretraining-based natural language generation for text summarization
Haoyu Zhang, Jingjing Cai, Jianjun Xu, and Ji Wang · 2019
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The CacheLib caching engine: Design and experiences at scale
Benjamin Berg, Daniel S. Berger, Sara McAllister, Isaac Grosof, Sathya Gunasekar, Jimmy Lu, Michael Uhlar, Jim Carrig, Nathan Beckmann, Mor Harchol-Balter, and Gregory R. Ganger · 2020
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Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan bras, Jianfeng Gao, and Choi Yejin · 2020
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Inferline: latency-aware provisioning and scaling for prediction serving pipelines
Daniel Crankshaw, Gur-Eyal Sela, Xiangxi Mo, Corey Zumar, Ion Stoica, Joseph Gonzalez, and Alexey Tumanov · 2020
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Serving dnns like clockwork: Performance predictability from the bottom up
Arpan Gujarati, Reza Karimi, Safya Alzayat, Wei Hao, Antoine Kaufmann, Ymir Vigfusson, and Jonathan Mace · 2020
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Autotm: Automatic tensor movement in heterogeneous memory systems using integer linear programming
Mark Hildebrand, Jawad Khan, Sanjeev Trika, Jason Lowe-Power, and Venkatesh Akella · 2020
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Swapadvisor: Pushing deep learning beyond the gpu memory limit via smart swapping
Chien-Chin Huang, Gu Jin, and Jinyang Li · 2020
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Reformer: The efficient transformer
Nikita Kitaev, Lukasz Kaiser, and Anselm Levskaya · 2020
Cited alongside, same era.
Capuchin: Tensor-based gpu memory management for deep learning
Xuan Peng, Xuanhua Shi, Hulin Dai, Hai Jin, Weiliang Ma, Qian Xiong, Fan Yang, and Xuehai Qian · 2020
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Compressive transformers for long-range sequence modelling
Jack W Rae, Anna Potapenko, Siddhant M Jayakumar, Chloe Hillier, and Timothy P Lillicrap · 2020
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Linformer: Self-attention with linear complexity
Sinong Wang, Belinda Z. Li, Madian Khabsa, Han Fang, and Hao Ma · 2020
Cited alongside, same era.
In-depth analyses of unified virtual memory system for gpu accelerated computing
Tyler Allen and Rong Ge · 2021
Cited alongside, same era.
Scatterbrain: Unifying sparse and low-rank attention
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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Extending context window of large language models via positional interpolation
Shouyuan Chen, Sherman Wong, Liangjian Chen, and Yuandong Tian · 2023
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Sparsegpt: Massive language models can be accurately pruned in one-shot
Elias Frantar and Dan Alistarh · 2023
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Olive: Accelerating large language models via hardware-friendly outlier-victim pair quantization
Cong Guo, Jiaming Tang, Weiming Hu, Jingwen Leng, Chen Zhang, Fan Yang, Yunxin Liu, Minyi Guo, and Yuhao Zhu · 2023
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Deepum: Tensor migration and prefetching in unified memory
Jaehoon Jung, Jinpyo Kim, and Jaejin Lee · 2023
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Beidi Chen, Tri Dao, Eric Winsor, Zhao Song, Atri Rudra, and Christopher Ré · 2021
Cited alongside, same era.
Mongoose: A learnable lsh framework for efficient neural network training
Beidi Chen, Zichang Liu, Binghui Peng, Zhaozhuo Xu, Jonathan Lingjie Li, Tri Dao, Zhao Song, Anshumali Shrivastava, and Christopher Re · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Rethinking attention with performers
Krzysztof Marcin Choromanski, Valerii Likhosherstov, David Dohan, Xingyou Song, Andreea Gane, Tamas Sarlos, Peter Hawkins, Jared Quincy Davis, Afroz Mohiuddin, Lukasz Kaiser, David Benjamin Belanger, Lucy J Colwell, and Adrian Weller · 2021
Cited alongside, same era.
Turbotransformers: an efficient gpu serving system for transformer models
Jiarui Fang, Yang Yu, Chengduo Zhao, and Jie Zhou · 2021
Cited alongside, same era.
A framework for few-shot language model evaluation, 2021
Leo Gao, Jonathan Tow, Stella Biderman, Sid Black, Anthony DiPofi, Charles Foster, Laurence Golding, Jeffrey Hsu, Kyle McDonell, Niklas Muennighoff, et al · 2021
Cited alongside, same era.
Elsa: Hardware-software co-design for efficient, lightweight self-attention mechanism in neural networks
Tae Jun Ham, Yejin Lee, Seong Hoon Seo, Soosung Kim, Hyunji Choi, Sung Jun Jung, and Jae W Lee · 2021
Cited alongside, same era.
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Flat: An optimized dataflow for mitigating attention bottlenecks
Sheng-Chun Kao, Suvinay Subramanian, Gaurav Agrawal, Amir Yazdanbakhsh, and Tushar Krishna · 2023
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Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph Gonzalez, Hao Zhang, and Ion Stoica · 2023
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Scissorhands: Exploiting the persistence of importance hypothesis for llm kv cache compression at test time
Zichang Liu, Aditya Desai, Fangshuo Liao, Weitao Wang, Victor Xie, Zhaozhuo Xu, Anastasios Kyrillidis, and Anshumali Shrivastava · 2023
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Codegen: An open large language model for code with multi-turn program synthesis
Erik Nijkamp, Bo Pang, Hiroaki Hayashi, Lifu Tu, Huan Wang, Yingbo Zhou, Silvio Savarese, and Caiming Xiong · 2023
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Efficiently scaling transformer inference
Reiner Pope, Sholto Douglas, Aakanksha Chowdhery, Jacob Devlin, James Bradbury, Jonathan Heek, Kefan Xiao, Shivani Agrawal, and Jeff Dean · 2023
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FlexGen: High-throughput generative inference of large language models with a single gpu
Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Re, Ion Stoica, and Ce Zhang · 2023
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Welder: Scheduling deep learning memory access via tile-graph
Yining Shi, Zhi Yang, Jilong Xue, Lingxiao Ma, Yuqing Xia, Ziming Miao, Yuxiao Guo, Fan Yang, and Lidong Zhou · 2023
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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
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Element-aware summarization with large language models: Expert-aligned evaluation and chain-of-thought method
Yiming Wang, Zhuosheng Zhang, and Rui Wang · 2023
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Smoothquant: Accurate and efficient post-training quantization for large language models
Guangxuan Xiao, Ji Lin, Mickael Seznec, Hao Wu, Julien Demouth, and Song Han · 2023
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Fifo queues are all you need for cache eviction
Juncheng Yang, Yazhuo Zhang, Ziyue Qiu, Yao Yue, and Rashmi Vinayak · 2023
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G10: Enabling an efficient unified gpu memory and storage architecture with smart tensor migrations
Haoyang Zhang, Yirui Eric Zhou, Yu Xue, Yiqi Liu, and Jian Huang · 2023
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Shepherd: Serving dnns in the wild
Hong Zhang, Yupeng Tang, Anurag Khandelwal, and Ion Stoica · 2023
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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, et al · 2023
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The claude 3 model family: Opus, sonnet, haiku
Anthropic · 2024
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Tender: Accelerating large language models via tensor decomposition and runtime requantization
Jungi Lee, Wonbeom Lee, and Jaewoong Sim · 2024
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Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
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Efficient streaming language models with attention sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, and Mike Lewis · 2024
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A paradigm shift in machine translation: Boosting translation performance of large language models
Haoran Xu, Young Jin Kim, Amr Sharaf, and Hany Hassan Awadalla · 2024
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