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Diversifying Reply Suggestions using a Matching-Conditional Variational Autoencoder [article]

Budhaditya Deb and Peter Bailey and Milad Shokouhi
2019 arXiv   pre-print
We consider the problem of diversifying automated reply suggestions for a commercial instant-messaging (IM) system (Skype).  ...  To diversify responses, we formulate the model as a generative latent variable model with Conditional Variational Auto-Encoder (M-CVAE).  ...  To this end, we propose the Matching-CVAE (M-CVAE) architecture, which introduces a generative LVM on the Matching-IR model using the neural variational autoencoder (VAE) framework (Kingma and Welling  ... 
arXiv:1903.10630v1 fatcat:lgoqayqpobajjevekrmjxbvuse

Diversifying Reply Suggestions Using a Matching-Conditional Variational Autoencoder

Budhaditya Deb, Peter Bailey, Milad Shokouhi
2019 Proceedings of the 2019 Conference of the North  
We consider the problem of diversifying automated reply suggestions for a commercial instant-messaging (IM) system (Skype).  ...  To diversify responses, we formulate the model as a generative latent variable model with Conditional Variational Auto-Encoder (M-CVAE).  ...  To this end, we propose the Matching-CVAE (M-CVAE) architecture, which introduces a generative LVM on the Matching-IR model using the neural variational autoencoder (VAE) framework (Kingma and Welling  ... 
doi:10.18653/v1/n19-2006 dblp:conf/naacl/DebBS19 fatcat:wfrcwx7j7zbtpohkvi7dynucxi

A Conditional Generative Matching Model for Multi-lingual Reply Suggestion [article]

Budhaditya Deb, Guoqing Zheng, Milad Shokouhi, Ahmed Hassan Awadallah
2021 arXiv   pre-print
While prior works largely focus on monolingual models, we propose Conditional Generative Matching models (CGM), optimized within a Variational Autoencoder framework to address challenges arising from multi-lingual  ...  We study the problem of multilingual automated reply suggestions (RS) model serving many languages simultaneously.  ...  Diversifying reply suggestions using a matching- conditional variational autoencoder. In NAACL- HLT. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019.  ... 
arXiv:2109.07046v1 fatcat:36qxed7xlnbvrfiyz2wz5whiji

Guiding Variational Response Generator to Exploit Persona [article]

Bowen Wu, Mengyuan Li, Zongsheng Wang, Yifu Chen, Derek Wong, Qihang Feng, Junhong Huang, Baoxun Wang
2020 arXiv   pre-print
This paper proposes to adopt the personality-related characteristics of human conversations into variational response generators, by designing a specific conditional variational autoencoder based deep  ...  We sincerely thank the anonymous reviewers for their thorough reviewing and valuable suggestions.  ...  CVAE Conditional Variational AutoEncoder with user information as prior knowledge for modeling persona . Similar to VAE, bagof-words loss is applied in CVAE.  ... 
arXiv:1911.02390v2 fatcat:nklapps6mvd3zfv4jfcqkbsjsq

MojiTalk: Generating Emotional Responses at Scale

Xianda Zhou, William Yang Wang
2018 Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)  
We investigate several conditional variational autoencoders training on these conversations, which allow us to use emojis to control the emotion of the generated text.  ...  Generating emotional language is a key step towards building empathetic natural language processing agents.  ...  Conditional Variational Autoencoder (CVAE) Having similar encoder-decoder structures, SEQ2SEQ can be easily extended to a Conditional Variational Autoencoder (CVAE) (Sohn et al., 2015) .  ... 
doi:10.18653/v1/p18-1104 dblp:conf/acl/WangZ18 fatcat:u6cjgc42vrd5ldz23waw6lov5e

Diversifying Dialogue Generation with Non-Conversational Text [article]

Hui Su, Xiaoyu Shen, Sanqiang Zhao, Xiao Zhou, Pengwei Hu, Randy Zhong, Cheng Niu, Jie Zhou
2020 arXiv   pre-print
In this paper, we propose a new perspective to diversify dialogue generation by leveraging non-conversational text.  ...  We further present a training paradigm to effectively incorporate these text via iterative back translation.  ...  CVAE The conditional variational autoencoder (Serban et al., 2017b; Zhao et al., 2017) which injects diversity by imposing stochastical latent variables.  ... 
arXiv:2005.04346v2 fatcat:iduxvzafffa7vizrd6u3g3ud3a

Jointly Optimizing Diversity and Relevance in Neural Response Generation

Xiang Gao, Sungjin Lee, Yizhe Zhang, Chris Brockett, Michel Galley, Jianfeng Gao, Bill Dolan
2019 Proceedings of the 2019 Conference of the North  
As a result, our approach induces a latent space in which the distance and direction from the predicted response vector roughly match the relevance and diversity, respectively.  ...  In this paper, we propose a SPACEFUSION model to jointly optimize diversity and relevance that essentially fuses the latent space of a sequenceto-sequence model and that of an autoencoder model by leveraging  ...  For instance, Zhao et al. (2017) present an approach to enhancing diversity by mapping diverse responses to a probability distribution using a conditional variational autoencoder (CVAE).  ... 
doi:10.18653/v1/n19-1125 dblp:conf/naacl/GaoLZBGGD19 fatcat:mrrunqfozje3ngxt6bmlcqhndi

Jointly Optimizing Diversity and Relevance in Neural Response Generation [article]

Xiang Gao, Sungjin Lee, Yizhe Zhang, Chris Brockett, Michel Galley, Jianfeng Gao, Bill Dolan
2019 arXiv   pre-print
As a result, our approach induces a latent space in which the distance and direction from the predicted response vector roughly match the relevance and diversity, respectively.  ...  In this paper, we propose a SpaceFusion model to jointly optimize diversity and relevance that essentially fuses the latent space of a sequence-to-sequence model and that of an autoencoder model by leveraging  ...  For instance, Zhao et al. (2017) present an approach to enhancing diversity by mapping diverse responses to a probability distribution using a conditional variational autoencoder (CVAE).  ... 
arXiv:1902.11205v3 fatcat:g6p5rvlq7fdsrlcuuxwu743oyu

Conditional Text Generation for Harmonious Human-Machine Interaction [article]

Bin Guo, Hao Wang, Yasan Ding, Wei Wu, Shaoyang Hao, Yueqi Sun, Zhiwen Yu
2020 arXiv   pre-print
Conditional Text Generation (CTG) has thus become a research hotspot. As a promising research field, we find that many efforts have been paid to exploring it.  ...  Therefore, we aim to give a comprehensive review of the new research trends of CTG.  ...  CONCLUSION We have made a systematic review of the research trends of conditional text generation (c-TextGen).  ... 
arXiv:1909.03409v2 fatcat:s2zfmwxtubgwjks4luoby6vdoq

Natural Language Generation with Neural Variational Models [article]

Hareesh Bahuleyan
2018 arXiv   pre-print
Specifically, we implement two sequence-to-sequence neural variational models - variational autoencoders (VAE) and variational encoder-decoders (VED).  ...  In order to circumvent this issue, we propose the variational attention mechanism where the attention context vector is modeled as a random variable that can be sampled from a distribution.  ...  Acknowledgements This thesis would not have been possible without the constant support that I received from a number of people.  ... 
arXiv:1808.09012v1 fatcat:2s5l5k5cr5bg3oqzvpbb5yt3zi

Deep Latent-Variable Models for Text Generation [article]

Xiaoyu Shen
2022 arXiv   pre-print
The end-to-end approach conflates all sub-modules, which used to be designed by complex handcrafted rules, into a holistic encode-decode architecture.  ...  As a result, it is difficult to trust the output from them in real-life applications.  ...  Conditional Variational Autoencoder.  ... 
arXiv:2203.02055v1 fatcat:sq3upxl7xvfnhigoc7apszomwu

Recent Advances in Neural Text Generation: A Task-Agnostic Survey [article]

Chen Tang, Frank Guerin, Yucheng Li, Chenghua Lin
2022 arXiv   pre-print
This paper presents a task-agnostic survey of recent advances in neural text generation.  ...  ., 2014) can search best-match text as the reply to a userissued utterance.  ...  The aforementioned Variational Autoencoder (VAE), for instance, is modified to a Variational Recurrent Autoencoder (VRAE) for text generation (Fabius et al., 2015; Chien and Wang, 2019) .  ... 
arXiv:2203.03047v1 fatcat:iupgvcw2hbge5ioy6quiotnra4

Challenges in Building Intelligent Open-domain Dialog Systems [article]

Minlie Huang, Xiaoyan Zhu, Jianfeng Gao
2020 arXiv   pre-print
Consistency requires the system to demonstrate a consistent personality to win users trust and gain their long-term confidence.  ...  Semantics requires a dialog system to not only understand the content of the dialog but also identify user's social needs during the conversation.  ...  In [195] , a conditional variational autoencoder is proposed to generate more emotional responses conditioned on an input post and some pre-specified emojis. Huber et al.  ... 
arXiv:1905.05709v3 fatcat:vdibhr4sobgufgcab2cyfyg7wy

Data Manipulation: Towards Effective Instance Learning for Neural Dialogue Generation via Learning to Augment and Reweight [article]

Hengyi Cai, Hongshen Chen, Yonghao Song, Cheng Zhang, Xiaofang Zhao, Dawei Yin
2020 arXiv   pre-print
As such, a reliable training corpus is the crux of building a robust and well-behaved dialogue model.  ...  In this paper, we propose a data manipulation framework to proactively reshape the data distribution towards reliable samples by augmenting and highlighting effective learning samples as well as reducing  ...  Acknowledgments We would like to thank all the reviewers for their insightful and valuable comments and suggestions.  ... 
arXiv:2004.02594v5 fatcat:yxg4fizbgndubh6y62q4sigagy

Cryptocurrency trading: a comprehensive survey

Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, David Martinez-Rego, Fan Wu, Lingbo Li
2022 Financial Innovation  
and extreme condition, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).  ...  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e.g., cryptocurrency trading systems, bubble  ...  Cryptocurrency exchanges can be market makers (usually using the bid-ask spread as a commission for services) or a matching platform (simply charging fees).  ... 
doi:10.1186/s40854-021-00321-6 fatcat:d3d2pkxy5fgcfa4s6gi4h2snua
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