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Large Language Models (LLMs) demonstrate substantial potential across a diverse array of domains via request serving.
Generating text with recurrent neural networks
Ilya Sutskever, James Martens, and Geoffrey E Hinton · 2011
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Earlier work this paper cites.
Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
Earlier work this paper cites.
Generating long sequences with sparse transformers, 2019
Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever · 2019
Earlier work this paper cites.
Gpipe: Efficient training of giant neural networks using pipeline parallelism
Yanping Huang, Youlong Cheng, Ankur Bapna, Orhan Firat, Dehao Chen, Mia Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V Le, Yonghui Wu, et al · 2019
Earlier work this paper cites.
Pipedream: Generalized pipeline parallelism for dnn training
Deepak Narayanan, Aaron Harlap, Amar Phanishayee, Vivek Seshadri, Nikhil R Devanur, Gregory R Ganger, Phillip B Gibbons, and Matei Zaharia · 2019
Earlier work this paper cites.
Fast transformer decoding: One write-head is all you need
Noam Shazeer · 2019
Earlier work this paper cites.
Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan · 2020
Earlier work this paper cites.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
Earlier work this paper cites.
Megatron-lm: Training multi-billion parameter language models using model parallelism, 2020
Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper, and Bryan Catanzaro · 2020
Earlier work this paper cites.
https://princeton-nlp.github.io/flash-decoding/ , 2021
Flashdecoding · 2021
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Evaluating large language models trained on code, 2021
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Josh Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba · 2021
Earlier work this paper cites.
Sequence parallelism: Long sequence training from system perspective
Shenggui Li, Fuzhao Xue, Chaitanya Baranwal, Yongbin Li, and Yang You · 2021
Earlier work this paper cites.
Efficient large-scale language model training on GPU clusters
Deepak Narayanan, Mohammad Shoeybi, Jared Casper, Patrick LeGresley, Mostofa Patwary, Vijay Korthikanti, Dmitri Vainbrand, Prethvi Kashinkunti, Julie Bernauer, Bryan Catanzaro, Amar Phanishayee, and Matei Zaharia · 2021
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Self-attention does not need o ( n 2 ) o(n^{2}) memory
Markus N Rabe and Charles Staats · 2021
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Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale
Reza Yazdani Aminabadi, Samyam Rajbhandari, Ammar Ahmad Awan, Cheng Li, Du Li, Elton Zheng, Olatunji Ruwase, Shaden Smith, Minjia Zhang, Jeff Rasley, et al · 2022
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Flashattention: Fast and memory-efficient exact attention with io-awareness
Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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https://openai.com/blog/chatgpt, 2022
OpenAI · 2022
Earlier work this paper cites.
Bloom: A 176b-parameter open-access multilingual language model
BigScience Workshop, Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, et al · 2022
Earlier work this paper cites.
Orca: A distributed serving system for { \{ Transformer-Based } \} generative models
Gyeong-In Yu, Joo Seong Jeong, Geon-Woo Kim, Soojeong Kim, and Byung-Gon Chun · 2022
Earlier work this paper cites.
https://github.com/microsoft/DeepSpeed/tree/master/blogs/deepspeed-fastgen , 2023
Deepspeed-fastgen: High-throughput text generation for llms via mii and deepspeed-inference · 2023
Cited alongside, same era.
Sarathi: Efficient llm inference by piggybacking decodes with chunked prefills, 2023
Amey Agrawal, Ashish Panwar, Jayashree Mohan, Nipun Kwatra, Bhargav S. Gulavani, and Ramachandran Ramjee · 2023
Cited alongside, same era.
L-eval: Instituting standardized evaluation for long context language models
Chenxin An, Shansan Gong, Ming Zhong, Mukai Li, Jun Zhang, Lingpeng Kong, and Xipeng Qiu · 2023
Cited alongside, same era.
L-eval: Instituting standardized evaluation for long context language models, 2023
Chenxin An, Shansan Gong, Ming Zhong, Xingjian Zhao, Mukai Li, Jun Zhang, Lingpeng Kong, and Xipeng Qiu · 2023
Cited alongside, same era.
Rohan Anil, Andrew M Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, et al · 2023
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
Later among the works it cites.
Yiming Wang, Zhuosheng Zhang, and Rui Wang · 2023
Later among the works it cites.
Leveraging large language models to power chatbots for collecting user self-reported data
Jing Wei, Sungdong Kim, Hyunhoon Jung, and Young-Ho Kim · 2023
Later among the works it cites.
Efficient streaming language models with attention sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen, Song Han, and Mike Lewis · 2023
Later among the works it cites.
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Cited alongside, same era.
Longbench: A bilingual, multitask benchmark for long context understanding
Yushi Bai, Xin Lv, Jiajie Zhang, Hongchang Lyu, Jiankai Tang, Zhidian Huang, Zhengxiao Du, Xiao Liu, Aohan Zeng, Lei Hou, et al · 2023
Cited alongside, same era.
Striped attention: Faster ring attention for causal transformers
William Brandon, Aniruddha Nrusimha, Kevin Qian, Zachary Ankner, Tian Jin, Zhiye Song, and Jonathan Ragan-Kelley · 2023
Cited alongside, same era.
A survey on evaluation of large language models, 2023
Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, and Xing Xie · 2023
Cited alongside, same era.
Agentcoder: Multi-agent-based code generation with iterative testing and optimisation
Dong Huang, Qingwen Bu, Jie M Zhang, Michael Luck, and Heming Cui · 2023
Cited alongside, same era.
Mistral 7b, 2023
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023
Cited alongside, same era.
Chatgpt and large language model (llm) chatbots: The current state of acceptability and a proposal for guidelines on utilization in academic medicine
Jin K Kim, Michael Chua, Mandy Rickard, and Armando Lorenzo · 2023
Cited alongside, same era.
Efficient memory management for large language model serving with pagedattention
W Kwon, Z Li, S Zhuang, et al · 2023
Cited alongside, same era.
H 2 o: Heavy-hitter oracle for efficient generative inference of large language models, 2023
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
Later among the works it cites.
Large language models for information retrieval: A survey
Yutao Zhu, Huaying Yuan, Shuting Wang, Jiongnan Liu, Wenhan Liu, Chenlong Deng, Zhicheng Dou, and Ji-Rong Wen · 2023
Later among the works it cites.
Longhealth: A question answering benchmark with long clinical documents
Lisa Adams, Felix Busch, Tianyu Han, Jean-Baptiste Excoffier, Matthieu Ortala, Alexander Löser, Hugo JWL Aerts, Jakob Nikolas Kather, Daniel Truhn, and Keno Bressem · 2024
Closest in time.
Llama 3 model card
AI@Meta · 2024
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https://www.anthropic.com/news/claude-3-family, 2024
Anthropic · 2024
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Longrope: Extending llm context window beyond 2 million tokens
Yiran Ding, Li Lyna Zhang, Chengruidong Zhang, Yuanyuan Xu, Ning Shang, Jiahang Xu, Fan Yang, and Mao Yang · 2024
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Serverlessllm: Locality-enhanced serverless inference for large language models, 2024
Yao Fu, Leyang Xue, Yeqi Huang, Andrei-Octavian Brabete, Dmitrii Ustiugov, Yuvraj Patel, and Luo Mai · 2024
Closest in time.
Our next-generation model: Gemini 1.5. https://blog.google/technology/ai/google-gemini-next-generationmodel-february-2024/, 2024
Google · 2024
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Parrot: Efficient serving of llm-based applications with semantic variable, 2024
Chaofan Lin, Zhenhua Han, Chengruidong Zhang, Yuqing Yang, Fan Yang, Chen Chen, and Lili Qiu · 2024
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Fairness in serving large language models, 2024
Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, and Ion Stoica · 2024
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Llumnix: Dynamic scheduling for large language model serving, 2024
Biao Sun, Ziming Huang, Hanyu Zhao, Wencong Xiao, Xinyi Zhang, Yong Li, and Wei Lin · 2024
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Self-retrieval: Building an information retrieval system with one large language model
Qiaoyu Tang, Jiawei Chen, Bowen Yu, Yaojie Lu, Cheng Fu, Haiyang Yu, Hongyu Lin, Fei Huang, Ben He, Xianpei Han, et al · 2024
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Towards efficient and reliable llm serving: A real-world workload study, 2024
Yuxin Wang, Yuhan Chen, Zeyu Li, Zhenheng Tang, Rui Guo, Xin Wang, Qiang Wang, Amelie Chi Zhou, and Xiaowen Chu · 2024
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Lv-eval: A balanced long-context benchmark with 5 length levels up to 256k
Tao Yuan, Xuefei Ning, Dong Zhou, Zhijie Yang, Shiyao Li, Minghui Zhuang, Zheyue Tan, Zhuyu Yao, Dahua Lin, Boxun Li, et al · 2024
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Benchmarking large language models for news summarization
Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen McKeown, and Tatsunori B Hashimoto · 2024
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Distserve: Disaggregating prefill and decoding for goodput-optimized large language model serving, 2024
Yinmin Zhong, Shengyu Liu, Junda Chen, Jianbo Hu, Yibo Zhu, Xuanzhe Liu, Xin Jin, and Hao Zhang · 2024
Closest in time.