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Open-domain neural dialogue models have achieved high performance in response ranking and evaluation tasks.
Language models are few-shot learners
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
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The probabilistic relevance framework: BM25 and beyond
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Multi-referenced training for dialogue response generation
Tianyu Zhao and Tatsuya Kawahara. 2020 · 2009
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Automatic keyword extraction from individual documents
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Generate your counterfactuals: Towards controlled counterfactual generation for text
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Explaining nlp models via minimal contrastive editing (mice)
Alexis Ross, Ana Marasović, and Matthew E Peters. 2020 · 2012
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Bootstrapping dialog systems with word embeddings
Gabriel Forgues, Joelle Pineau, Jean-Marie Larchevêque, and Réal Tremblay. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan Salakhutdinov, Richard S. Zemel, Antonio Torralba, Raquel Urtasun, and Sanja Fidler. 2015 · 2015
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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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Building end-to-end dialogue systems using generative hierarchical neural network models
Iulian Serban, Alessandro Sordoni, Yoshua Bengio, Aaron Courville, and Joelle Pineau. 2016 · 2016
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Analysis of the impact of negative sampling on link prediction in knowledge graphs
Bhushan Kotnis and Vivi Nastase. 2017 · 2017
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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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Towards an automatic Turing test: Learning to evaluate dialogue responses
Ryan Lowe, Michael Noseworthy, Iulian Vlad Serban, Nicolas Angelard-Gontier, Yoshua Bengio, and Joelle Pineau. 2017 · 2017
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The effect of negative sampling strategy on capturing semantic similarity in document embeddings
Marzieh Saeidi, Ritwik Kulkarni, Theodosia Togia, and Michele Sama. 2017 · 2017
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A hierarchical latent variable encoder-decoder model for generating dialogues
Iulian Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron Courville, and Yoshua Bengio. 2017 · 2017
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Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang. 2018 · 2018
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HotFlip: White-box adversarial examples for text classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 2018 · 2018
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Vse++: Improving visual-semantic embeddings with hard negatives
Fartash Faghri, David J Fleet, Jamie Ryan Kiros, and Sanja Fidler. 2018 · 2018
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Vse-ens: Visual-semantic embeddings with efficient negative sampling
Guibing Guo, Songlin Zhai, Fajie Yuan, Yuan Liu, and Xingwei Wang. 2018 · 2018
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Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
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Content analysis: An introduction to its methodology
Klaus Krippendorff. 2018 · 2018
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Ruber: An unsupervised method for automatic evaluation of open-domain dialog systems
Chongyang Tao, Lili Mou, Dongyan Zhao, and Rui Yan. 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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Multi-turn response selection for chatbots with deep attention matching network
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou. 2020 · 2020
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The curious case of neural text degeneration
Ari Holtzman, Jan Buys, Maxwell Forbes, and Yejin Choi. 2020 · 2020
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Reducing sentiment bias in language models via counterfactual evaluation
Po-Sen Huang, Huan Zhang, Ray Jiang, Robert Stanforth, Johannes Welbl, Jack Rae, Vishal Maini, Dani Yogatama, and Pushmeet Kohli. 2020 · 2020
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Poly-encoders: architectures and pre-training strategies for fast and accurate multi-sentence scoring
Samuel Humeau, Kurt Shuster, Marie-Anne Lachaux, and Jason Weston. 2020 · 2020
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Is bert really robust? a strong baseline for natural language attack on text classification and entailment
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Xiangyang Zhou, Lu Li, Daxiang Dong, Yi Liu, Ying Chen, Wayne Xin Zhao, Dianhai Yu, and Hua Wu. 2018 · 2018
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Retrieval-guided dialogue response generation via a matching-to-generation framework
Deng Cai, Yan Wang, Wei Bi, Zhaopeng Tu, Xiaojiang Liu, and Shuming Shi. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Counterfactual fairness in text classification through robustness
Sahaj Garg, Vincent Perot, Nicole Limtiaco, Ankur Taly, Ed H. Chi, and Alex Beutel. 2019 · 2019
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Better automatic evaluation of open-domain dialogue systems with contextualized embeddings
Sarik Ghazarian, Johnny Wei, Aram Galstyan, and Nanyun Peng. 2019 · 2019
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Investigating evaluation of open-domain dialogue systems with human generated multiple references
Prakhar Gupta, Shikib Mehri, Tiancheng Zhao, Amy Pavel, Maxine Eskenazi, and Jeffrey Bigham. 2019 · 2019
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Improving taxonomy of errors in chat-oriented dialogue systems
Ryuichiro Higashinaka, Masahiro Araki, Hiroshi Tsukahara, and Masahiro Mizukami. 2019 · 2019
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Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2020 · 2020
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Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oguz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2020
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Learning the difference that makes a difference with counterfactually-augmented data
Divyansh Kaushik, Eduard Hovy, and Zachary C Lipton. 2020 · 2020
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Evaluating the factual consistency of abstractive text summarization
Wojciech Kryscinski, Bryan McCann, Caiming Xiong, and Richard Socher. 2020 · 2020
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The world is not binary: Learning to rank with grayscale data for dialogue response selection
Zibo Lin, Deng Cai, Yan Wang, Xiaojiang Liu, Haitao Zheng, and Shuming Shi. 2020 · 2020
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USR: An unsupervised and reference free evaluation metric for dialog generation
Shikib Mehri and Maxine Eskenazi. 2020 · 2020
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Improving dialog evaluation with a multi-reference adversarial dataset and large scale pretraining
Ananya B Sai, Akash Kumar Mohankumar, Siddhartha Arora, and Mitesh M Khapra. 2020 · 2020
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Evaluating dialogue generation systems via response selection
Shiki Sato, Reina Akama, Hiroki Ouchi, Jun Suzuki, and Kentaro Inui. 2020 · 2020
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Adversarial semantic collisions
Congzheng Song, Alexander Rush, and Vitaly Shmatikov. 2020 · 2020
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Robustness to spurious correlations via human annotations
Megha Srivastava, Tatsunori Hashimoto, and Percy Liang. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
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Designing precise and robust dialogue response evaluators
Tianyu Zhao, Divesh Lala, and Tatsuya Kawahara. 2020 · 2020
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Controlling dialogue generation with semantic exemplars
Prakhar Gupta, Jeffrey Bigham, Yulia Tsvetkov, and Amy Pavel. 2021 · 2021
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Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics
Artidoro Pagnoni, Vidhisha Balachandran, and Yulia Tsvetkov. 2021 · 2021
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Recipes for building an open-domain chatbot
Stephen Roller, Emily Dinan, Naman Goyal, Da Ju, Mary Williamson, Yinhan Liu, Jing Xu, Myle Ott, Eric Michael Smith, Y-Lan Boureau, and Jason Weston. 2021 · 2021
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Do response selection models really know what’s next? utterance manipulation strategies for multi-turn response selection
Taesun Whang, Dongyub Lee, Dongsuk Oh, Chanhee Lee, Kijong Han, Dong-hun Lee, and Saebyeok Lee. 2021 · 2021
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Polyjuice: Automated, general-purpose counterfactual generation
Tongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, and Daniel S Weld. 2021 · 2021
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Can you put it all together: Evaluating conversational agents’ ability to blend skills
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Adversarial examples for evaluating reading comprehension systems
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Speaker-Aware BERT for Multi-Turn Response Selection in Retrieval-Based Chatbots , page 2041–2044. Association for Computing Machinery, New York, NY, USA
Jia-Chen Gu, Tianda Li, Quan Liu, Zhen-Hua Ling, Zhiming Su, Si Wei, and Xiaodan Zhu. 2020 · 2044
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