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Variational Auto-Encoder (VAE) has become the de-facto learning paradigm in achieving representation learning and generation for natural language at the same time.
Cyclical annealing schedule: A simple approach to mitigating kl vanishing
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Effective estimation of deep generative language models
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Variational pretraining for semi-supervised text classification
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Implicit deep latent variable models for text generation
Le Fang, Chunyuan Li, Jianfeng Gao, Wen Dong, and Changyou Chen. 2019 · 1908
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A surprisingly effective fix for deep latent variable modeling of text
Bohan Li, Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick, and Yiming Yang. 2019 · 1909
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Pre-train and plug-in: Flexible conditional text generation with variational auto-encoders
Yu Duan, Canwen Xu, Jiaxin Pei, Jialong Han, and Chenliang Li. 2019 · 1911
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Neural networks and physical systems with emergent collective computational abilities
John J Hopfield. 1982 · 1982
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Optimus: Organizing sentences via pre-trained modeling of a latent space
Chunyuan Li, Xiang Gao, Yuan Li, Baolin Peng, Xiujun Li, Yizhe Zhang, and Jianfeng Gao. 2020 · 2004
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Apo-vae: Text generation in hyperbolic space
Shuyang Dai, Zhe Gan, Yu Cheng, Chenyang Tao, Lawrence Carin, and Jingjing Liu. 2020 · 2005
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Adapterfusion: Non-destructive task composition for transfer learning
Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, Kyunghyun Cho, and Iryna Gurevych. 2020 · 2005
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Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton. 2008 · 2008
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Conditional generative adversarial nets
Mehdi Mirza and Simon Osindero. 2014 · 2014
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Generating sentences from a continuous space
Samuel R Bowman, Luke Vilnis, Oriol Vinyals, Andrew M Dai, Rafal Jozefowicz, and Samy Bengio. 2015 · 2015
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Toward controlled generation of text
Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017 · 2017
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A hybrid convolutional variational autoencoder for text generation
Stanislau Semeniuta, Aliaksei Severyn, and Erhardt Barth. 2017 · 2017
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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
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
T-cvae: Transformer-based conditioned variational autoencoder for story completion
Tianming Wang and Xiaojun Wan. 2019 · 2019
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Topic-guided variational auto-encoder for text generation
Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, and Lawrence Carin. 2019 · 2019
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Educating text autoencoders: Latent representation guidance via denoising
Tianxiao Shen, Jonas Mueller, Regina Barzilay, and Tommi Jaakkola. 2020 · 2020
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On variational learning of controllable representations for text without supervision
Peng Xu, Jackie Chi Kit Cheung, and Yanshuai Cao. 2020 · 2020
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Transformer-based conditional variational autoencoder for controllable story generation
Le Fang, Tao Zeng, Chaochun Liu, Liefeng Bo, Wen Dong, and Changyou Chen. 2021 · 2021
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Training tips for the transformer model
Martin Popel and Ondřej Bojar. 2018 · 2018
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Towards text generation with adversarially learned neural outlines
Sandeep Subramanian, Sai Rajeswar Mudumba, Alessandro Sordoni, Adam Trischler, Aaron C Courville, and Chris Pal. 2018 · 2018
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Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel Bowman. 2018 · 2018
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Dirichlet variational autoencoder for text modeling
Yijun Xiao, Tiancheng Zhao, and William Yang Wang. 2018 · 2018
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Adversarially regularized autoencoders
Junbo Zhao, Yoon Kim, Kelly Zhang, Alexander Rush, and Yann LeCun. 2018 · 2018
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
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Understanding posterior collapse in generative latent variable models
James Lucas, George Tucker, Roger Grosse, and Mohammad Norouzi. 2019 · 2019
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Junxian He, Chunting Zhou, Xuezhe Ma, Taylor Berg-Kirkpatrick, and Graham Neubig. 2021 · 2021
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Lora: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021 · 2021
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The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant. 2021 · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang. 2021 · 2021
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Finetuning pretrained transformers into variational autoencoders
Seongmin Park and Jihwa Lee. 2021 · 2021
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Revisiting parameter-efficient tuning: Are we really there yet?
Guanzheng Chen, Fangyu Liu, Zaiqiao Meng, and Shangsong Liang. 2022 · 2022
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Delta tuning: A comprehensive study of parameter efficient methods for pre-trained language models
Ning Ding, Yujia Qin, Guang Yang, Fuchao Wei, Zonghan Yang, Yusheng Su, Shengding Hu, Yulin Chen, Chi-Min Chan, Weize Chen, et al. 2022 · 2022
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Controlled text generation using dictionary prior in variational autoencoders
Xianghong Fang, Jian Li, Lifeng Shang, Xin Jiang, Qun Liu, and Dit-Yan Yeung. 2022 · 2022
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