Fetching the paper…
Reading the bibliography…
Pretrained language models (PLMs) have made remarkable progress in text generation tasks via fine-tuning.
Generating long and informative reviews with aspect-aware coarse-to-fine decoding
Junyi Li, Wayne Xin Zhao, Ji-Rong Wen, and Yang Song. 2019 · 1979
Earlier work this paper cites.
A min-max cut algorithm for graph partitioning and data clustering
Chris H. Q. Ding, Xiaofeng He, Hongyuan Zha, Ming Gu, and Horst D. Simon. 2001 · 2001
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.
Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
Earlier work this paper cites.
Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2005
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.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V. Le. 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. 2016 · 2016
Earlier work this paper cites.
Squad: 100, 000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Earlier work this paper cites.
Convolutional sequence to sequence learning
Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, and Yann N. Dauphin. 2017 · 2017
Earlier work this paper cites.
Dailydialog: A manually labelled multi-turn dialogue dataset
Yanran Li, Hui Su, Xiaoyu Shen, Wenjie Li, Ziqiang Cao, and Shuzi Niu. 2017 · 2017
Earlier work this paper cites.
Get to the point: Summarization with pointer-generator networks
Abigail See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
Bilateral multi-perspective matching for natural language sentences
Zhiguo Wang, Wael Hamza, and Radu Florian. 2017 · 2017
Earlier work this paper cites.
Neural domain adaptation for biomedical question answering
Georg Wiese, Dirk Weissenborn, and Mariana L. Neves. 2017 · 2017
Earlier work this paper cites.
Multiwoz - a large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling
Paweł Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Ultes Stefan, Ramadan Osman, and Milica Gašić. 2018 · 2018
Cited alongside, same era.
Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann N. Dauphin. 2018 · 2018
Cited alongside, same era.
Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies
Max Grusky, Mor Naaman, and Yoav Artzi. 2018 · 2018
Cited alongside, same era.
Don’t give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization
Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
Cited alongside, same era.
Personalizing dialogue agents: I have a dog, do you have pets too?
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018 · 2018
Cited alongside, same era.
Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
Later among the works it cites.
Autoprompt: Eliciting knowledge from language models with automatically generated prompts
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2020
Later among the works it cites.
Compression, transduction, and creation: A unified framework for evaluating natural language generation
Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, and Zhiting Hu. 2021 · 2021
Later among the works it cites.
Single-dataset experts for multi-dataset question answering
Dan Friedman, Ben Dodge, and Danqi Chen. 2021 · 2021
Later among the works it cites.
Few-shot knowledge graph-to-text generation with pretrained language models
Junyi Li, Tianyi Tang, Wayne Xin Zhao, Zhicheng Wei, Nicholas Jing Yuan, and Ji-Rong Wen. 2021b · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Huda Alamri, Vincent Cartillier, Abhishek Das, Jue Wang, Stefan Lee, Peter Anderson, Irfan Essa, Devi Parikh, Dhruv Batra, Anoop Cherian, Tim K. Marks, and Chiori Hori. 2019 · 2019
Cited alongside, same era.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Multi-news: A large-scale multi-document summarization dataset and abstractive hierarchical model
Alexander R. Fabbri, Irene Li, Tianwei She, Suyi Li, and Dragomir R. Radev. 2019 · 2019
Cited alongside, same era.
Topical-Chat: Towards Knowledge-Grounded Open-Domain Conversations
Karthik Gopalakrishnan, Behnam Hedayatnia, Qinlang Chen, Anna Gottardi, Sanjeev Kwatra, Anu Venkatesh, Raefer Gabriel, and Dilek Hakkani-Tür. 2019 · 2019
Cited alongside, same era.
Linguistic knowledge and transferability of contextual representations
Nelson F. Liu, Matt Gardner, Yonatan Belinkov, Matthew E. Peters, and Noah A. Smith. 2019 · 2019
Cited alongside, same era.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
Cited alongside, same era.
Few-shot NLG with pre-trained language model
Zhiyu Chen, Harini Eavani, Wenhu Chen, Yinyin Liu, and William Yang Wang. 2020 · 2020
Cited alongside, same era.
Pretrained language model for text generation: A survey
Junyi Li, Tianyi Tang, Wayne Xin Zhao, and Ji-Rong Wen. 2021c · 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.
GLGE: A new general language generation evaluation benchmark
Dayiheng Liu, Yu Yan, Yeyun Gong, Weizhen Qi, Hang Zhang, Jian Jiao, Weizhu Chen, Jie Fu, Linjun Shou, Ming Gong, Pengcheng Wang, Jiusheng Chen, Daxin Jiang, Jiancheng Lv, Ruofei Zhang, Winnie Wu, Ming Zhou, and Nan Duan. 2021a · 2021
Later among the works it cites.
How many data points is a prompt worth?
Teven Le Scao and Alexander M. Rush. 2021 · 2021
Later among the works it cites.
On transferability of prompt tuning for natural language understanding
YuSheng Su, Xiaozhi Wang, Yujia Qin, Chi-Min Chan, Yankai Lin, Zhiyuan Liu, Peng Li, Juanzi Li, Lei Hou, Maosong Sun, and Jie Zhou. 2021 · 2021
Later among the works it cites.
Spot: Better frozen model adaptation through soft prompt transfer
Tu Vu, Brian Lester, Noah Constant, Rami Al-Rfou, and Daniel Cer. 2021 · 2021
Later among the works it cites.
A comprehensive survey on transfer learning
Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, and Qing He. 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.
A survey of pretrained language models based text generation
Junyi Li, Tianyi Tang, Wayne Xin Zhao, Jian-Yun Nie, and Ji-Rong Wen. 2022 · 2022
Closest in time.
Learning to prompt for continual learning
Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, and Tomas Pfister. 2022 · 2022
Closest in time.