Fetching the paper…
Reading the bibliography…
Text generation rarely considers the control of lexical complexity, which limits its more comprehensive practical application.
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. 2020 · 1901
Earlier work this paper cites.
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
Earlier work this paper cites.
Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, et al. 2019 · 1910
Earlier work this paper cites.
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. 2019 · 1912
Earlier work this paper cites.
Automatic evaluation of machine translation quality using n-gram co-occurrence statistics
George Doddington. 2002 · 2002
Earlier work this paper cites.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Exploring controllable text generation techniques
Shrimai Prabhumoye, Alan W Black, and Ruslan Salakhutdinov. 2020 · 2005
Earlier work this paper cites.
Pointer: Constrained progressive text generation via insertion-based generative pre-training
Yizhe Zhang, Guoyin Wang, Chunyuan Li, Zhe Gan, Chris Brockett, and Bill Dolan. 2020 · 2005
Earlier work this paper cites.
Fine-grained sentiment controlled text generation
Bidisha Samanta, Mohit Agarwal, and Niloy Ganguly. 2020 · 2006
Earlier work this paper cites.
Meteor: An automatic metric for mt evaluation with high levels of correlation with human judgments
Alon Lavie and Abhaya Agarwal. 2007 · 2007
Earlier work this paper cites.
Reranking machine translation hypotheses with structured and web-based language models
Wen Wang, Andreas Stolcke, and Jing Zheng. 2007 · 2007
Earlier work this paper cites.
Kg-bart: Knowledge graph-augmented bart for generative commonsense reasoning
Ye Liu, Yao Wan, Lifang He, Hao Peng, and Philip S Yu. 2020 · 2009
Earlier work this paper cites.
An enhanced knowledge injection model for commonsense generation
Zhihao Fan, Yeyun Gong, Zhongyu Wei, Siyuan Wang, Yameng Huang, Jian Jiao, Xuanjing Huang, Nan Duan, and Ruofei Zhang. 2020 · 2012
Earlier work this paper cites.
Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen. 2020 · 2012
Earlier work this paper cites.
A distributional approach to controlled text generation
Muhammad Khalifa, Hady Elsahar, and Marc Dymetman. 2020 · 2012
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
A diversity-promoting objective function for neural conversation models
Jiwei Li, Michel Galley, Chris Brockett, Jianfeng Gao, and Bill Dolan. 2015 · 2015
Earlier work this paper cites.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2015 · 2015
Earlier work this paper cites.
Lexis, lexical competence and lexical knowledge: a review
Keiby Caro and Nayibe Rosado Mendinueta. 2017 · 2017
Earlier work this paper cites.
Toward controlled generation of text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017 · 2017
Cited alongside, same era.
Ensemble and reranking: Using multiple models in the nict-2 neural machine translation system at wat2017
Kenji Imamura and Eiichiro Sumita. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Simplification using paraphrases and context-based lexical substitution
Reno Kriz, Eleni Miltsakaki, Marianna Apidianaki, and Chris Callison-Burch. 2018 · 2018
Cited alongside, same era.
Fast lexically constrained decoding with dynamic beam allocation for neural machine translation
Matt Post and David Vilar. 2018 · 2018
Cited alongside, same era.
Gradient-guided unsupervised lexically constrained text generation
Lei Sha. 2020 · 2020
Later among the works it cites.
Bridging the structural gap between encoding and decoding for data-to-text generation
Chao Zhao, Marilyn Walker, and Snigdha Chaturvedi. 2020 · 2020
Later among the works it cites.
Efl students’ difficulties with lexical and syntactic features of news headlines and news stories
Reima Al-Jarf. 2021 · 2021
Later among the works it cites.
Lexical density and readability of secondary stage english textbooks in jordan
Mohammad Ahmad Bani Amer. 2021 · 2021
Later among the works it cites.
Simple or complex? learning to predict readability of bengali texts
Susmoy Chakraborty, Mir Tafseer Nayeem, and Wasi Uddin Ahmad. 2021 · 2021
Later among the works it cites.
Parallel refinements for lexically constrained text generation with bart
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Yizhe Zhang, Michel Galley, Jianfeng Gao, Zhe Gan, Xiujun Li, Chris Brockett, and Bill Dolan. 2018 · 2018
Cited alongside, same era.
Sentiment-controllable chinese poetry generation
Huimin Chen, Xiaoyuan Yi, Maosong Sun, Wenhao Li, Cheng Yang, and Zhipeng Guo. 2019 · 2019
Cited alongside, same era.
Improved lexically constrained decoding for translation and monolingual rewriting
J Edward Hu, Huda Khayrallah, Ryan Culkin, Patrick Xia, Tongfei Chen, Matt Post, and Benjamin Van Durme. 2019 · 2019
Cited alongside, same era.
Sentence-level readability assessment for l2 chinese learning
Dawei Lu, Xinying Qiu, and Yi Cai. 2019 · 2019
Cited alongside, same era.
Cgmh: Constrained sentence generation by metropolis-hastings sampling
Ning Miao, Hao Zhou, Lili Mou, Rui Yan, and Lei Li. 2019 · 2019
Cited alongside, same era.
Controllable text simplification with lexical constraint loss
Daiki Nishihara, Tomoyuki Kajiwara, and Yuki Arase. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Cited alongside, same era.
Xingwei He. 2021 · 2021
Later among the works it cites.
Show me how to revise: Improving lexically constrained sentence generation with xlnet
Xingwei He and Victor OK Li. 2021 · 2021
Later among the works it cites.
Lexical thresholds and alleged threats to validity: A storm in a teacup?
Batia Laufer. 2021 · 2021
Later among the works it cites.
Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang. 2021 · 2021
Later among the works it cites.
Constrained text generation with global guidance–case study on commongen
Yixian Liu, Liwen Zhang, Wenjuan Han, Yue Zhang, and Kewei Tu. 2021 · 2021
Later among the works it cites.
Structural adapters in pretrained language models for amr-to-text generation
Leonardo FR Ribeiro, Yue Zhang, and Iryna Gurevych. 2021 · 2021
Later among the works it cites.
A sentiment and style controllable approach for chinese poetry generation
Yizhan Shao, Tong Shao, Minghao Wang, Peng Wang, and Jie Gao. 2021 · 2021
Later among the works it cites.
Songmass: Automatic song writing with pre-training and alignment constraint
Zhonghao Sheng, Kaitao Song, Xu Tan, Yi Ren, Wei Ye, Shikun Zhang, and Tao Qin. 2021 · 2021
Later among the works it cites.
Plan-then-generate: Controlled data-to-text generation via planning
Yixuan Su, David Vandyke, Sihui Wang, Yimai Fang, and Nigel Collier. 2021 · 2021
Later among the works it cites.
Fudge: Controlled text generation with future discriminators
Kevin Yang and Dan Klein. 2021 · 2021
Later among the works it cites.
Controllable generation from pre-trained language models via inverse prompting
Xu Zou, Da Yin, Qingyang Zhong, Hongxia Yang, Zhilin Yang, and Jie Tang. 2021 · 2021
Later among the works it cites.
Summareranker: A multi-task mixture-of-experts re-ranking framework for abstractive summarization
Mathieu Ravaut, Shafiq Joty, and Nancy F Chen. 2022 · 2022
Closest in time.
Assessing sentence readability for german language learners with broad linguistic modeling or readability formulas: When do linguistic insights make a difference?
Zarah Weiss and Detmar Meurers. 2022 · 2022
Closest in time.
A survey of controllable text generation using transformer-based pre-trained language models
Hanqing Zhang, Haolin Song, Shaoyu Li, Ming Zhou, and Dawei Song. 2022 · 2022
Closest in time.