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Current variational dialog models have employed pre-trained language models (PLMs) to parameterize the likelihood and posterior distributions.
A discrete CVAE for response generation on short-text conversation
Jun Gao, Wei Bi, Xiaojiang Liu, Junhui Li, Guodong Zhou, and Shuming Shi. 2019 · 1908
Earlier work this paper cites.
Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
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
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Auto-encoding variational bayes
Diederik P. Kingma and Max Welling. 2014 · 2014
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Deep unordered composition rivals syntactic methods for text classification
Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, and Hal Daumé III. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Variational inference with normalizing flows
Danilo Jimenez Rezende and Shakir Mohamed. 2015 · 2015
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Learning structured output representation using deep conditional generative models
Kihyuk Sohn, Honglak Lee, and Xinchen Yan. 2015 · 2015
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Generating sentences from a continuous space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew Dai, Rafal Jozefowicz, and Samy Bengio. 2016 · 2016
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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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How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
Chia-Wei Liu, Ryan Lowe, Iulian Serban, Mike Noseworthy, Laurent Charlin, and Joelle Pineau. 2016 · 2016
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Ladder variational autoencoders
Casper Kaae Sønderby, Tapani Raiko, Lars Maaløe, Søren Kaae Sønderby, and Ole Winther. 2016 · 2016
Earlier work this paper cites.
Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy. 2016 · 2016
Earlier work this paper cites.
OpenNMT: Open-source toolkit for neural machine translation
Guillaume Klein, Yoon Kim, Yuntian Deng, Jean Senellart, and Alexander Rush. 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
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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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Piecewise latent variables for neural variational text processing
Iulian Vlad Serban, Alexander G. Ororbia, Joelle Pineau, and Aaron Courville. 2017a · 2017
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A hierarchical latent variable encoder-decoder model for generating dialogues
Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron C. Courville, and Yoshua Bengio. 2017b · 2017
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A conditional variational framework for dialog generation
Xiaoyu Shen, Hui Su, Yanran Li, Wenjie Li, Shuzi Niu, Yang Zhao, Akiko Aizawa, and Guoping Long. 2017 · 2017
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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
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Variational attention for sequence-to-sequence models
Hareesh Bahuleyan, Lili Mou, Olga Vechtomova, and Pascal Poupart. 2018 · 2018
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Hierarchical variational memory network for dialogue generation
Hongshen Chen, Zhaochun Ren, Jiliang Tang, Yihong Eric Zhao, and Dawei Yin. 2018 · 2018
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
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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
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Unsupervised discrete sentence representation learning for interpretable neural dialog generation
Tiancheng Zhao, Kyusong Lee, and Maxine Eskenazi. 2018 · 2018
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Generating multiple diverse responses with multi-mapping and posterior mapping selection
Chaotao Chen, Jinhua Peng, Fan Wang, Jun Xu, and Hua Wu. 2019 · 2019
Earlier work this paper cites.
Improving neural conversational models with entropy-based data filtering
Richárd Csáky, Patrik Purgai, and Gábor Recski. 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.
Implicit deep latent variable models for text generation
Le Fang, Chunyuan Li, Jianfeng Gao, Wen Dong, and Changyou Chen. 2019 · 2019
Cited alongside, same era.
Cyclical annealing schedule: A simple approach to mitigating KL vanishing
Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, and Lawrence Carin. 2019 · 2019
Cited alongside, same era.
Large-scale transfer learning for natural language generation
Sergey Golovanov, Rauf Kurbanov, Sergey Nikolenko, Kyryl Truskovskyi, Alexander Tselousov, and Thomas Wolf. 2019 · 2019
Cited alongside, same era.
Variational diffusion models
Diederik Kingma, Tim Salimans, Ben Poole, and Jonathan Ho. 2021 · 2021
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Variational dialogue generation with normalizing flows
Tien-Ching Luo and Jen-Tzung Chien. 2021 · 2021
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Entropy analysis of n-grams and estimation of the number of meaningful language texts. cyber security applications
Anastasia Malashina. 2021 · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal. 2021 · 2021
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Generating relevant and coherent dialogue responses using self-separated conditional variational AutoEncoders
Bin Sun, Shaoxiong Feng, Yiwei Li, Jiamou Liu, and Kan Li. 2021 · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz. 2021 · 2021
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Xiaodong Gu, Kyunghyun Cho, Jung-Woo Ha, and Sunghun Kim. 2019 · 2019
Cited alongside, same era.
Learning hierarchical priors in vaes
Alexej Klushyn, Nutan Chen, Richard Kurle, Botond Cseke, and Patrick van der Smagt. 2019 · 2019
Cited alongside, same era.
A surprisingly effective fix for deep latent variable modeling of text
Bohan Li, Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick, and Yiming Yang. 2019 · 2019
Cited alongside, same era.
Analyzing multi-head self-attention: Specialized heads do the heavy lifting, the rest can be pruned
Elena Voita, David Talbot, Fedor Moiseev, Rico Sennrich, and Ivan Titov. 2019 · 2019
Cited alongside, same era.
PLATO: Pre-trained dialogue generation model with discrete latent variable
Siqi Bao, Huang He, Fan Wang, Hua Wu, and Haifeng Wang. 2020 · 2020
Cited alongside, same era.
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, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Cited alongside, same era.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
Assessing dialogue systems with distribution distances
Jiannan Xiang, Yahui Liu, Deng Cai, Huayang Li, Defu Lian, and Lemao Liu. 2021 · 2021
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Pcvae: Generating prior context for dialogue response generation
Zefeng Cai and Zerui Cai. 2022 · 2022
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DialogVED: A pre-trained latent variable encoder-decoder model for dialog response generation
Wei Chen, Yeyun Gong, Song Wang, Bolun Yao, Weizhen Qi, Zhongyu Wei, Xiaowu Hu, Bartuer Zhou, Yi Mao, Weizhu Chen, Biao Cheng, and Nan Duan. 2022 · 2022
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Measuring and improving semantic diversity of dialogue generation
Seungju Han, Beomsu Kim, and Buru Chang. 2022 · 2022
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Autoregressive diffusion models
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, and Tim Salimans. 2022 · 2022
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Fuse it more deeply! a variational transformer with layer-wise latent variable inference for text generation
Jinyi Hu, Xiaoyuan Yi, Wenhao Li, Maosong Sun, and Xing Xie. 2022b · 2022
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Diffusion-lm improves controllable text generation
Xiang Li, John Thickstun, Ishaan Gulrajani, Percy S Liang, and Tatsunori B Hashimoto. 2022 · 2022
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Composable text controls in latent space with odes
Guangyi Liu, Zeyu Feng, Yuan Gao, Zichao Yang, Xiaodan Liang, Junwei Bao, Xiaodong He, Shuguang Cui, Zhen Li, and Zhiting Hu. 2022 · 2022
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Latent diffusion for language generation
Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shekhtman, and Kilian Weinberger. 2022 · 2022
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Learning to drop out: An adversarial approach to training sequence vaes
Djordje Miladinovic, Kumar Shridhar, Kushal Jain, Max Paulus, Joachim M Buhmann, and Carl Allen. 2022 · 2022
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Cross-task generalization via natural language crowdsourcing instructions
Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi. 2022 · 2022
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Self-conditioned embedding diffusion for text generation
Robin Strudel, Corentin Tallec, Florent Altché, Yilun Du, Yaroslav Ganin, Arthur Mensch, Will Grathwohl, Nikolay Savinov, Sander Dieleman, Laurent Sifre, et al. 2022 · 2022
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BERTScore is unfair: On social bias in language model-based metrics for text generation
Tianxiang Sun, Junliang He, Xipeng Qiu, and Xuanjing Huang. 2022 · 2022
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Latent diffusion energy-based model for interpretable text modelling
Peiyu Yu, Sirui Xie, Xiaojian Ma, Baoxiong Jia, Bo Pang, Ruiqi Gao, Yixin Zhu, Song-Chun Zhu, and Ying Nian Wu. 2022 · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2023 · 2023
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Diffuseq: Sequence to sequence text generation with diffusion models
Shansan Gong, Mukai Li, Jiangtao Feng, Zhiyong Wu, and Lingpeng Kong. 2023 · 2023
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Understanding DDPM latent codes through optimal transport
Valentin Khrulkov, Gleb V. Ryzhakov, Andrei Chertkov, and Ivan V. Oseledets. 2023 · 2023
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Towards diverse, relevant and coherent open-domain dialogue generation via hybrid latent variables
Bin Sun, Yitong Li, Fei Mi, Weichao Wang, Yiwei Li, and Kan Li. 2023 · 2023
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MVP: Multi-task supervised pre-training for natural language generation
Tianyi Tang, Junyi Li, Wayne Xin Zhao, and Ji-Rong Wen. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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