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We propose LLMA, an LLM accelerator to losslessly speed up Large Language Model (LLM) inference with references.
Ms marco: A human generated machine reading comprehension dataset, 2018
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, Mir Rosenberg, Xia Song, Alina Stoica, Saurabh Tiwary, and Tong Wang · 2018
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Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers, 2020
Wenhui Wang, Furu Wei, Li Dong, Hangbo Bao, Nan Yang, and Ming Zhou · 2020
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Transformers: State-of-the-art natural language processing
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
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Bert-of-theseus: Compressing bert by progressive module replacing
Canwen Xu, Wangchunshu Zhou, Tao Ge, Furu Wei, and Ming Zhou · 2020
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Instantaneous grammatical error correction with shallow aggressive decoding
Xin Sun, Tao Ge, Furu Wei, and Houfeng Wang · 2021
Earlier work this paper cites.
Rarr: Researching and revising what language models say, using language models, 2022
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Y. Zhao, Ni Lao, Hongrae Lee, Da-Cheng Juan, and Kelvin Guu · 2022
Cited alongside, same era.
Lossless acceleration for seq2seq generation with aggressive decoding
Tao Ge, Heming Xia, Xin Sun, Si-Qing Chen, and Furu Wei · 2022
Cited alongside, same era.
Accelerate: Training and inference at scale made simple, efficient and adaptable
Sylvain Gugger, Lysandre Debut, Thomas Wolf, Philipp Schmid, Zachary Mueller, and Sourab Mangrulkar · 2022
Cited alongside, same era.
Text embeddings by weakly-supervised contrastive pre-training, 2022
Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, and Furu Wei · 2022
Cited alongside, same era.
Accelerating large language model decoding with speculative sampling, 2023
Charlie Chen, Sebastian Borgeaud, Geoffrey Irving, Jean-Baptiste Lespiau, Laurent Sifre, and John Jumper · 2023
The case for 4-bit precision: k-bit inference scaling laws, 2023
Tim Dettmers and Luke Zettlemoyer · 2023
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Sparsegpt: Massive language models can be accurately pruned in one-shot, 2023
Elias Frantar and Dan Alistarh · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Llama: Open and efficient foundation language models, 2023
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample · 2023
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Cited alongside, same era.
Speculative decoding: Lossless speedup of autoregressive translation
Heming Xia, Tao Ge, Si-Qing Chen, Furu Wei, and Zhifang Sui
Cited in the paper.
Lossless speedup of autoregressive translation with generalized aggressive decoding, 2022b
Heming Xia, Tao Ge, Furu Wei, and Zhifang Sui
Cited in the paper.