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To meet the requirements of real-world applications, it is essential to control generations of large language models (LLMs).
Roberta: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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CTRL: A conditional transformer language model for controllable generation
Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, Caiming Xiong, and Richard Socher. 2019 · 1909
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A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and Bill Dolan. 2016 · 2016
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Controlling linguistic style aspects in neural language generation
Jessica Ficler and Yoav Goldberg. 2017 · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann N. Dauphin. 2018 · 2018
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Scibert: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 2019
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Multiple-attribute text rewriting
Guillaume Lample, Sandeep Subramanian, Eric Michael Smith, Ludovic Denoyer, Marc’Aurelio Ranzato, and Y-Lan Boureau. 2019 · 2019
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Plug and play language models: A simple approach to controlled text generation
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu. 2020 · 2020
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Realtoxicityprompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A. Smith. 2020 · 2020
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Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasovic, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
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Cocon: A self-supervised approach for controlled text generation
Alvin Chan, Yew-Soon Ong, Bill Pung, Aston Zhang, and Jie Fu. 2021 · 2021
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Decision transformer: Reinforcement learning via sequence modeling
Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, and Igor Mordatch. 2021 · 2021
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Offline reinforcement learning as one big sequence modeling problem
Michael Janner, Qiyang Li, and Sergey Levine. 2021 · 2021
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A distributional approach to controlled text generation
Muhammad Khalifa, Hady Elsahar, and Marc Dymetman. 2021 · 2021
Cited alongside, same era.
Gedi: Generative discriminator guided sequence generation
Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, Nitish Shirish Keskar, Shafiq R. Joty, Richard Socher, and Nazneen Fatema Rajani. 2021 · 2021
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Controlled text generation as continuous optimization with multiple constraints
Sachin Kumar, Eric Malmi, Aliaksei Severyn, and Yulia Tsvetkov. 2021 · 2021
Cited alongside, same era.
A distributional lens for multi-aspect controllable text generation
Yuxuan Gu, Xiaocheng Feng, Sicheng Ma, Lingyuan Zhang, Heng Gong, and Bing Qin. 2022b · 2022
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Diffusion-lm improves controllable text generation
Xiang Li, John Thickstun, Ishaan Gulrajani, Percy Liang, and Tatsunori B. Hashimoto. 2022 · 2022
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QUARK: controllable text generation with reinforced unlearning
Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, and Yejin Choi. 2022 · 2022
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Controllable natural language generation with contrastive prefixes
Jing Qian, Li Dong, Yelong Shen, Furu Wei, and Weizhu Chen. 2022 · 2022
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Discup: Discriminator cooperative unlikelihood prompt-tuning for controllable text generation
Hanqing Zhang and Dawei Song. 2022 · 2022
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Online decision transformer
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Xiang Lisa Li and Percy Liang. 2021 · 2021
Cited alongside, same era.
Plug-and-blend: A framework for plug-and-play controllable story generation with sketches
Zhiyu Lin and Mark O. Riedl. 2021 · 2021
Cited alongside, same era.
Dexperts: Decoding-time controlled text generation with experts and anti-experts
Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith, and Yejin Choi. 2021 · 2021
Cited alongside, same era.
Scaling language models: Methods, analysis & insights from training gopher
Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, H. Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d’Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J. Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, and Geoffrey Irving. 2021 · 2021
Cited alongside, same era.
Ethical and social risks of harm from language models
Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, Zac Kenton, Sasha Brown, Will Hawkins, Tom Stepleton, Courtney Biles, Abeba Birhane, Julia Haas, Laura Rimell, Lisa Anne Hendricks, William Isaac, Sean Legassick, Geoffrey Irving, and Iason Gabriel. 2021 · 2021
Cited alongside, same era.
FUDGE: controlled text generation with future discriminators
Kevin Yang and Dan Klein. 2021 · 2021
Cited alongside, same era.
Domain-specific language model pretraining for biomedical natural language processing
Yu Gu, Robert Tinn, Hao Cheng, Michael Lucas, Naoto Usuyama, Xiaodong Liu, Tristan Naumann, Jianfeng Gao, and Hoifung Poon. 2022a
Cited in the paper.
Qinqing Zheng, Amy Zhang, and Aditya Grover. 2022 · 2022
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Controllable text generation via probability density estimation in the latent space
Yuxuan Gu, Xiaocheng Feng, Sicheng Ma, Lingyuan Zhang, Heng Gong, Weihong Zhong, and Bing Qin. 2023 · 2023
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An extensible plug-and-play method for multi-aspect controllable text generation
Xuancheng Huang, Zijun Liu, Peng Li, Tao Li, Maosong Sun, and Yang Liu. 2023 · 2023
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Fine-grained human feedback gives better rewards for language model training
Zeqiu Wu, Yushi Hu, Weijia Shi, Nouha Dziri, Alane Suhr, Prithviraj Ammanabrolu, Noah A. Smith, Mari Ostendorf, and Hannaneh Hajishirzi. 2023 · 2023
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Hyper-decision transformer for efficient online policy adaptation
Mengdi Xu, Yuchen Lu, Yikang Shen, Shun Zhang, Ding Zhao, and Chuang Gan. 2023 · 2023
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Tailor: A soft-prompt-based approach to attribute-based controlled text generation
Kexin Yang, Dayiheng Liu, Wenqiang Lei, Baosong Yang, Mingfeng Xue, Boxing Chen, and Jun Xie. 2023a · 2023
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