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Large Language Models (LLMs), such as ChatGPT and GPT-4, have dramatically transformed natural language processing research and shown promising strides towards Artificial General Intelligence (AGI).
SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson · 2012
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RACE: Large-scale ReAding comprehension dataset from examinations
Guokun Lai, Qizhe Xie, Hanxiao Liu, Yiming Yang, and Eduard Hovy · 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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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Nlp chinese corpus: Large scale chinese corpus for nlp, September 2019
Bright Xu · 2019
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Root Mean Square Layer Normalization
Biao Zhang and Rico Sennrich · 2019
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Revisiting pre-trained models for Chinese natural language processing
Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, Shijin Wang, and Guoping Hu · 2020
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Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, and Yuxiong He · 2020
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Glu variants improve transformer, 2020
Noam Shazeer · 2020
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Pre-training with whole word masking for chinese bert
Yiming Cui, Wanxiang Che, Ting Liu, Bing Qin, and Ziqing Yang · 2021
Cited alongside, same era.
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
Cited alongside, same era.
Roformer: Enhanced transformer with rotary position embedding, 2021
Jianlin Su, Yu Lu, Shengfeng Pan, Bo Wen, and Yunfeng Liu · 2021
Cited alongside, same era.
Lert: A linguistically-motivated pre-trained language model
Yiming Cui, Wanxiang Che, Shijin Wang, and Ting Liu · 2022
Cited alongside, same era.
GPTQ: Accurate post-training compression for generative pretrained transformers
Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh · 2022
Extending context window of large language models via positional interpolation
Shouyuan Chen, Sherman Wong, Liangjian Chen, and Yuandong Tian · 2023
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Qlora: Efficient finetuning of quantized llms
Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer · 2023
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llama.cpp
Georgi Gerganov · 2023
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C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models
Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, Junlei Zhang, Jinghan Zhang, Tangjun Su, Junteng Liu, Chuancheng Lv, Yikai Zhang, Jiayi Lei, Yao Fu, Maosong Sun, and Junxian He · 2023
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OpenAssistant Conversations – Democratizing Large Language Model Alignment
Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, Sotiris Anagnostidis, Zhi-Rui Tam, Keith Stevens, Abdullah Barhoum, Nguyen Minh Duc, Oliver Stanley, Richárd Nagyfi, Shahul ES, Sameer Suri, David Glushkov, Arnav Dantuluri, Andrew Maguire, Christoph Schuhmann, Huu Nguyen, and Alexander Mattick · 2023
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Cited alongside, same era.
Introducing chatgpt
OpenAI · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 2022
Cited alongside, same era.
Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al · 2022
Cited alongside, same era.
Self-Instruct: Aligning Language Model with Self Generated Instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi · 2022
Cited alongside, same era.
CINO: A Chinese minority pre-trained language model
Ziqing Yang, Zihang Xu, Yiming Cui, Baoxin Wang, Min Lin, Dayong Wu, and Zhigang Chen · 2022
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, Yuxiao Dong, Jie Tang, and Juanzi Li · 2023
Cited alongside, same era.
Stanford alpaca: An instruction-following llama model
Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B. Hashimoto
Cited in the paper.
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Cmmlu: Measuring massive multitask language understanding in chinese, 2023
Haonan Li, Yixuan Zhang, Fajri Koto, Yifei Yang, Hai Zhao, Yeyun Gong, Nan Duan, and Timothy Baldwin · 2023
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OpenAI · 2023
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Yarn: Efficient context window extension of large language models
Bowen Peng, Jeffrey Quesnelle, Honglu Fan, and Enrico Shippole · 2023
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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
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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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GLM-130b: An open bilingual pre-trained model
Aohan Zeng, Xiao Liu, Zhengxiao Du, Zihan Wang, Hanyu Lai, Ming Ding, Zhuoyi Yang, Yifan Xu, Wendi Zheng, Xiao Xia, Weng Lam Tam, Zixuan Ma, Yufei Xue, Jidong Zhai, Wenguang Chen, Zhiyuan Liu, Peng Zhang, Yuxiao Dong, and Jie Tang · 2023
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