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We present a novel approach to learn representations for sentence-level semantic similarity using conversational data.
Semeval-2012 task 6: A pilot on semantic textual similarity
Eneko Agirre, Mona Diab, Daniel Cer, and Aitor Gonzalez-Agirre. 2012 · 2012
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Ukp: Computing semantic textual similarity by combining multiple content similarity measures
Daniel Bär, Chris Biemann, Iryna Gurevych, and Torsten Zesch. 2012 · 2012
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Soft cardinality: A parameterized similarity function for text comparison
Sergio Jimenez, Claudia Becerra, and Alexander Gelbukh. 2012 · 2012
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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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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Skip-thought vectors
Ryan Kiros, Yukun Zhu, Ruslan R Salakhutdinov, Richard Zemel, Raquel Urtasun, Antonio Torralba, and Sanja Fidler. 2015 · 2015
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Jointly optimizing word representations for lexical and sentential tasks with the c-phrase model
Germán Kruszewski, Angeliki Lazaridou, Marco Baroni, et al. 2015 · 2015
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Improved semantic representations from tree-structured long short-term memory networks
Kai Sheng Tai, Richard Socher, and Christopher D Manning. 2015 · 2015
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Conversational contextual cues: The case of personalization and history for response ranking
Rami Al-Rfou, Marc Pickett, Javier Snaider, Yun-hsuan Sung, Brian Strope, and Ray Kurzweil. 2016 · 2016
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Smart reply: Automated response suggestion for email
Anjuli Kannan, Karol Kurach, Sujith Ravi, Tobias Kaufman, Balint Miklos, Greg Corrado, Andrew Tomkins, Laszlo Lukacs, Marina Ganea, Peter Young, and Vivek Ramavajjala. 2016 · 2016
Cited alongside, same era.
An empirical evaluation of doc2vec with practical insights into document embedding generation
Jey Han Lau and Timothy Baldwin. 2016 · 2016
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A simple but tough-to-beat baseline for sentence embeddings
Sanjeev Arora, Yingyu Liang, and Tengyu Ma. 2017 · 2017
Cited alongside, same era.
Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Inigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
Cited alongside, same era.
Simbow at semeval-2017 task 3: Soft-cosine semantic similarity between questions for community question answering
Delphine Charlet and Geraldine Damnati. 2017 · 2017
Cited alongside, same era.
Efficient natural language response suggestion for smart reply
Matthew Henderson, Rami Al-Rfou, Brian Strope, Yun-Hsuan Sung, László Lukács, Ruiqi Guo, Sanjiv Kumar, Balint Miklos, and Ray Kurzweil. 2017 · 2017
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SemEval-2017 task 3: Community question answering
Preslav Nakov, Doris Hoogeveen, Lluís Màrquez, Alessandro Moschitti, Hamdy Mubarak, Timothy Baldwin, and Karin Verspoor. 2017 · 2017
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Unsupervised learning of sentence embeddings using compositional n-gram features
Matteo Pagliardini, Prakhar Gupta, and Martin Jaggi. 2017 · 2017
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Hcti at semeval-2017 task 1: Use convolutional neural network to evaluate semantic textual similarity
Yang Shao. 2017 · 2017
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Ecnu at semeval-2017 task 1: Leverage kernel-based traditional nlp features and neural networks to build a universal model for multilingual and cross-lingual semantic textual similarity
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Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Diana Inkpen, and Si Wei. 2017 · 2017
Cited alongside, same era.
Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Kelp at semeval-2017 task 3: Learning pairwise patterns in community question answering
Simone Filice, Giovanni Da San Martino, and Alessandro Moschitti. 2017 · 2017
Cited alongside, same era.
Junfeng Tian, Zhiheng Zhou, Man Lan, and Yuanbin Wu. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Learning to parse from a semantic objective: It works. is it syntax?
Adina Williams, Andrew Drozdov, and Samuel R Bowman. 2017 · 2017
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Bit at semeval-2017 task 1: Using semantic information space to evaluate semantic textual similarity
Hao Wu, Heyan Huang, Ping Jian, Yuhang Guo, and Chao Su. 2017 · 2017
Later among the works it cites.