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Recent research, such as BitNet, is paving the way for a new era of 1-bit Large Language Models (LLMs).
1.1 computing’s energy problem (and what we can do about it)
Mark Horowitz · 2014
Earlier work this paper cites.
Pointer sentinel mixture models, 2016
Stephen Merity, Caiming Xiong, James Bradbury, and Richard Socher · 2016
Earlier work this paper cites.
The LAMBADA dataset: Word prediction requiring a broad discourse context
Denis Paperno, Germán Kruszewski, Angeliki Lazaridou, Quan Ngoc Pham, Raffaella Bernardi, Sandro Pezzelle, Marco Baroni, Gemma Boleda, and Raquel Fernández · 2016
Earlier work this paper cites.
Crowdsourcing multiple choice science questions
Johannes Welbl, Nelson F. Liu, and Matt Gardner · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
PIQA: reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, and Yejin Choi · 2019
Earlier work this paper cites.
Boolq: Exploring the surprising difficulty of natural yes/no questions
Christopher Clark, Kenton Lee, Ming-Wei Chang, Tom Kwiatkowski, Michael Collins, and Kristina Toutanova · 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 Xu Chen, HyoukJoong Lee, Jiquan Ngiam, Quoc V. Le, Yonghui Wu, and Zhifeng Chen · 2019
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu · 2019
Earlier work this paper cites.
Quick and (not so) dirty: Unsupervised selection of justification sentences for multi-hop question answering
Vikas Yadav, Steven Bethard, and Mihai Surdeanu · 2019
Cited alongside, same era.
HellaSwag: can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
Cited alongside, same era.
Root mean square layer normalization
Biao Zhang and Rico Sennrich · 2019
Cited alongside, same era.
WinoGrande: an adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi · 2020
Cited alongside, same era.
GLU variants improve transformer
Noam Shazeer · 2020
Cited alongside, same era.
PokeBNN: A binary pursuit of lightweight accuracy
Yichi Zhang, Zhiru Zhang, and Lukasz Lew · 2022
Efficient memory management for large language model serving with pagedattention
Woosuk Kwon, Zhuohan Li, Siyuan Zhuang, Ying Sheng, Lianmin Zheng, Cody Hao Yu, Joseph E. Gonzalez, Hao Zhang, and Ion Stoica · 2023
Later among the works it cites.
AWQ: activation-aware weight quantization for LLM compression and acceleration
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Xingyu Dang, and Song Han · 2023
Later among the works it cites.
LLaMA: open and efficient foundation language models
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
Later among the works it cites.
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, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, and et al · 2023
Later among the works it cites.
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Cited alongside, same era.
QuIP: 2-bit quantization of large language models with guarantees
Jerry Chee, Yaohui Cai, Volodymyr Kuleshov, and Christopher De Sa · 2023
Cited alongside, same era.
Redpajama: an open dataset for training large language models, 2023
Together Computer · 2023
Cited alongside, same era.
OPTQ: accurate quantization for generative pre-trained transformers
Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh · 2023
Cited alongside, same era.
Stablelm 3b 4e1t
Jonathan Tow, Marco Bellagente, Dakota Mahan, and Carlos Riquelme
Cited in the paper.
Ladder: Efficient tensor compilation on customized data format
Lei Wang, Lingxiao Ma, Shijie Cao, Ningxin Zheng, Quanlu Zhang, Jilong Xue, Ziming Miao, Ting Cao, , and Yuqing Yang · 2023
Later among the works it cites.
Bitnet: Scaling 1-bit transformers for large language models
Hongyu Wang, Shuming Ma, Li Dong, Shaohan Huang, Huaijie Wang, Lingxiao Ma, Fan Yang, Ruiping Wang, Yi Wu, and Furu Wei · 2023
Later among the works it cites.
SmoothQuant: accurate and efficient post-training quantization for large language models
Guangxuan Xiao, Ji Lin, Mickaël Seznec, Hao Wu, Julien Demouth, and Song Han · 2023
Later among the works it cites.
Roformer: Enhanced transformer with rotary position embedding
Jianlin Su, Murtadha H. M. Ahmed, Yu Lu, Shengfeng Pan, Wen Bo, and Yunfeng Liu · 2024
Closest in time.
Quip#: Even better LLM quantization with hadamard incoherence and lattice codebooks
Albert Tseng, Jerry Chee, Qingyao Sun, Volodymyr Kuleshov, and Christopher De Sa · 2024
Closest in time.