PAS: Data-Efficient Plug-and-Play Prompt Augmentation System

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 · 1901

Earlier work this paper cites.

Enabling a Plug-and-play integration of smart environments. In 2006 2nd International Conference on Information & Communication Technologies , Vol. 1. IEEE, 820–825

Bessam Abdulrazak and A Helal. 2006 · 2006

Earlier work this paper cites.

Plug-and-play priors for model based reconstruction. In 2013 IEEE global conference on signal and information processing . IEEE, 945–948

Singanallur V Venkatakrishnan, Charles A Bouman, and Brendt Wohlberg. 2013 · 2013

Earlier work this paper cites.

Generalizing AI: Challenges and opportunities for plug and play AI solutions

Ismaeel Al Ridhawi, Safa Otoum, Moayad Aloqaily, and Azzedine Boukerche. 2020 · 2020

Earlier work this paper cites.

DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION. In International Conference on Learning Representations

Pengcheng He, Xiaodong Liu, Jianfeng Gao, and Weizhu Chen. 2020 · 2020

Earlier work this paper cites.

Plug-and-play image restoration with deep denoiser prior

Kai Zhang, Yawei Li, Wangmeng Zuo, Lei Zhang, Luc Van Gool, and Radu Timofte. 2021 · 2021

Earlier work this paper cites.

A survey on in-context learning

Original

Qingxiu Dong, Lei Li, Damai Dai, Ce Zheng, Zhiyong Wu, Baobao Chang, Xu Sun, Jingjing Xu, and Zhifang Sui. 2022 · 2022

Earlier work this paper cites.

Large language models are zero-shot reasoners

Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 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

Earlier work this paper cites.

Chain-of-thought prompting elicits reasoning in large language models

Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022

Earlier work this paper cites.

Automatic chain of thought prompting in large language models

Original

Zhuosheng Zhang, Aston Zhang, Mu Li, and Alex Smola. 2022 · 2022

Earlier work this paper cites.

Large language models are human-level prompt engineers

Original

Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2022a · 2022

Earlier work this paper cites.

Large language models are human-level prompt engineers

Original

Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba. 2022b · 2022

Earlier work this paper cites.

Qwen Technical Report

Original

Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, Binyuan Hui, Luo Ji, Mei Li, Junyang Lin, Runji Lin, Dayiheng Liu, Gao Liu, Chengqiang Lu, Keming Lu, Jianxin Ma, Rui Men, Xingzhang Ren, Xuancheng Ren, Chuanqi Tan, Sinan Tan, Jianhong Tu, Peng Wang, Shijie Wang, Wei Wang, Shengguang Wu, Benfeng Xu, Jin Xu, An Yang, Hao Yang, Jian Yang, Shusheng Yang, Yang Yao, Bowen Yu, Hongyi Yuan, Zheng Yuan, Jianwei Zhang, Xingxuan Zhang, Yichang Zhang, Zhenru Zhang, Chang Zhou, Jingren Zhou, Xiaohuan Zhou, and Tianhang Zhu. 2023 · 2023

Earlier work this paper cites.

Alpagasus: Training a better alpaca with fewer data

Original

Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, et al · 2023

Earlier work this paper cites.

Lingua manga: A generic large language model centric system for data curation

Original

Zui Chen, Lei Cao, and Sam Madden. 2023a · 2023

Earlier work this paper cites.

Black-box prompt optimization: Aligning large language models without model training

Original

Jiale Cheng, Xiao Liu, Kehan Zheng, Pei Ke, Hongning Wang, Yuxiao Dong, Jie Tang, and Minlie Huang. 2023 · 2023

Cited alongside, same era.

Mods: Model-oriented data selection for instruction tuning

Original

Qianlong Du, Chengqing Zong, and Jiajun Zhang. 2023 · 2023

Cited alongside, same era.

How large language models will disrupt data management

Raul Castro Fernandez, Aaron J Elmore, Michael J Franklin, Sanjay Krishnan, and Chenhao Tan. 2023 · 2023

Cited alongside, same era.

Promptbreeder: Self-referential self-improvement via prompt evolution

Original

Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, Simon Osindero, and Tim Rocktäschel. 2023 · 2023

Cited alongside, same era.

Prompt engineering with ChatGPT: a guide for academic writers

Louie Giray. 2023 · 2023

Plan-and-solve prompting: Improving zero-shot chain-of-thought reasoning by large language models

Original

Lei Wang, Wanyu Xu, Yihuai Lan, Zhiqiang Hu, Yunshi Lan, Roy Ka-Wei Lee, and Ee-Peng Lim. 2023 · 2023

Later among the works it cites.

Rethinking the Instruction Quality: LIFT is What You Need

Original

Yang Xu, Yongqiang Yao, Yufan Huang, Mengnan Qi, Maoquan Wang, Bin Gu, and Neel Sundaresan. 2023 · 2023

Later among the works it cites.

Baichuan 2: Open large-scale language models

Original

Aiyuan Yang, Bin Xiao, Bingning Wang, Borong Zhang, Ce Bian, Chao Yin, Chenxu Lv, Da Pan, Dian Wang, Dong Yan, et al · 2023

Later among the works it cites.

Large language models as optimizers

Original

Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V Le, Denny Zhou, and Xinyun Chen. 2023a · 2023

Later among the works it cites.