LlamaDuo: LLMOps Pipeline for Seamless Migration from Service LLMs to Small-Scale Local LLMs

Scaling laws for neural language models

Original

Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001

Earlier work this paper cites.

Training question answering models from synthetic data

Original

Raul Puri, Ryan Spring, Mostofa Patwary, Mohammad Shoeybi, and Bryan Catanzaro. 2020 · 2002

Earlier work this paper cites.

Generative data augmentation for commonsense reasoning

Original

Yiben Yang, Chaitanya Malaviya, Jared Fernandez, Swabha Swayamdipta, Ronan Le Bras, Ji-Ping Wang, Chandra Bhagavatula, Yejin Choi, and Doug Downey. 2020 · 2004

Earlier work this paper cites.

Privacy preserving synthetic data release using deep learning

Nazmiye Ceren Abay, Yan Zhou, Murat Kantarcioglu, Bhavani Thuraisingham, and Latanya Sweeney. 2019 · 2018

Earlier work this paper cites.

Training compute-optimal large language models

Original

Jordan Hoffmann, Sebastian Borgeaud, Arthur Mensch, Elena Buchatskaya, Trevor Cai, Eliza Rutherford, Diego de Las Casas, Lisa Anne Hendricks, Johannes Welbl, Aidan Clark, et al. 2022 · 2022

Earlier work this paper cites.

Training language models to follow instructions with human feedback

Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al. 2022 · 2022

Earlier work this paper cites.

Impact of pretraining term frequencies on few-shot reasoning

Original

Yasaman Razeghi, Robert L Logan IV, Matt Gardner, and Sameer Singh. 2022 · 2022

Earlier work this paper cites.

Gpt-4 technical report

Original

Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023

Earlier work this paper cites.

Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality

Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023

Earlier work this paper cites.

Palm: Scaling language modeling with pathways

Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, et al. 2023 · 2023

Earlier work this paper cites.

Auggpt: Leveraging chatgpt for text data augmentation

Original

Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Yihan Cao, Zihao Wu, Lin Zhao, Shaochen Xu, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Lichao Sun, Quanzheng Li, Dinggang Shen, Tianming Liu, and Xiang Li. 2023 · 2023

Earlier work this paper cites.

Gemini: a family of highly capable multimodal models

Original

Gemini Team. 2023 · 2023

Earlier work this paper cites.

Improving small language models on pubmedqa via generative data augmentation

Z Guo, P Wang, Y Wang, and S Yu. 2023 · 2023

Earlier work this paper cites.

A survey on large language models: Applications, challenges, limitations, and practical usage

Muhammad Usman Hadi, Rizwan Qureshi, Abbas Shah, Muhammad Irfan, Anas Zafar, Muhammad Bilal Shaikh, Naveed Akhtar, Jia Wu, Seyedali Mirjalili, et al. 2023 · 2023

Earlier work this paper cites.

Mistral 7b

Original

Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023

Earlier work this paper cites.

Large language models struggle to learn long-tail knowledge

Nikhil Kandpal, Haikang Deng, Adam Roberts, Eric Wallace, and Colin Raffel. 2023 · 2023

Earlier work this paper cites.

The flan collection: Designing data and methods for effective instruction tuning

Shayne Longpre, Le Hou, Tu Vu, Albert Webson, Hyung Won Chung, Yi Tay, Denny Zhou, Quoc V Le, Barret Zoph, Jason Wei, et al. 2023 · 2023

Cited alongside, same era.

Wizardcoder: Empowering code large language models with evol-instruct

Ziyang Luo, Can Xu, Pu Zhao, Qingfeng Sun, Xiubo Geng, Wenxiang Hu, Chongyang Tao, Jing Ma, Qingwei Lin, and Daxin Jiang. 2023 · 2023

Cited alongside, same era.

Crosslingual generalization through multitask finetuning

Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, et al. 2023 · 2023

Cited alongside, same era.

A comprehensive overview of large language models

Original

Humza Naveed, Asad Ullah Khan, Shi Qiu, Muhammad Saqib, Saeed Anwar, Muhammad Usman, Nick Barnes, and Ajmal Mian. 2023 · 2023

Cited alongside, same era.

Direct preference optimization: Your language model is secretly a reward model

Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn. 2023 · 2023

The Claude 3 Model Family: Opus, Sonnet, Haiku

Anthropic. 2024 · 2024

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A survey on mixture of experts

Original

Weilin Cai, Juyong Jiang, Fan Wang, Jing Tang, Sunghun Kim, and Jiayi Huang. 2024 · 2024

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A survey on evaluation of large language models

Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, et al. 2024 · 2024

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Scaling instruction-finetuned language models

Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2024 · 2024

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Qlora: Efficient finetuning of quantized llms

Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, and Luke Zettlemoyer. 2024 · 2024

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Gemma: Open models based on gemini research and technology