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Alex Wang | Samuel R. Bowman | Benjamin Van Durme | R. Thomas McCoy | Adam Poliak | Ellie Pavlick | Tal Linzen | Patrick Xia | Ian Tenney | Alexis Ross | Najoung Kim | Roma Patel | Alex Wang | Tal Linzen | Ellie Pavlick | Adam Poliak | Ian Tenney | Patrick Xia | Roma Patel | Najoung Kim | Alexis Ross
[1] Sanjiv Kumar,et al. On the Convergence of Adam and Beyond , 2018 .
[2] Carolyn Penstein Rosé,et al. Stress Test Evaluation for Natural Language Inference , 2018, COLING.
[3] Allan Jabri,et al. Learning Visually Grounded Sentence Representations , 2018, NAACL.
[4] Sheng Zhang,et al. Ordinal Common-sense Inference , 2016, TACL.
[5] Yonatan Belinkov,et al. On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference , 2018, NAACL.
[6] Gerard de Melo,et al. Exploring Semantic Properties of Sentence Embeddings , 2018, ACL.
[7] Alex Wang,et al. What do you learn from context? Probing for sentence structure in contextualized word representations , 2019, ICLR.
[8] Anders Søgaard,et al. Linguistic representations in multi-task neural networks for ellipsis resolution , 2018, BlackboxNLP@EMNLP.
[9] Omer Levy,et al. GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding , 2018, BlackboxNLP@EMNLP.
[10] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[11] Edouard Grave,et al. Colorless Green Recurrent Networks Dream Hierarchically , 2018, NAACL.
[12] Richard Socher,et al. Pointer Sentinel Mixture Models , 2016, ICLR.
[13] Carlos Guestrin,et al. Semantically Equivalent Adversarial Rules for Debugging NLP models , 2018, ACL.
[14] Richard Socher,et al. The Natural Language Decathlon: Multitask Learning as Question Answering , 2018, ArXiv.
[15] Dieuwke Hupkes,et al. Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items , 2018, BlackboxNLP@EMNLP.
[16] Samuel R. Bowman,et al. Discourse-Based Objectives for Fast Unsupervised Sentence Representation Learning , 2017, ArXiv.
[17] Samuel R. Bowman,et al. A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference , 2017, NAACL.
[18] Rachel Rudinger,et al. Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation , 2018, BlackboxNLP@EMNLP.
[19] Thorsten Brants,et al. One billion word benchmark for measuring progress in statistical language modeling , 2013, INTERSPEECH.
[20] Micha Elsner,et al. Breaking NLP: Using Morphosyntax, Semantics, Pragmatics and World Knowledge to Fool Sentiment Analysis Systems , 2017 .
[21] Pietro Perona,et al. Microsoft COCO: Common Objects in Context , 2014, ECCV.
[22] Luke S. Zettlemoyer,et al. Deep Contextualized Word Representations , 2018, NAACL.
[23] Richard Socher,et al. Learned in Translation: Contextualized Word Vectors , 2017, NIPS.
[24] Nathan Schneider,et al. Comprehensive Supersense Disambiguation of English Prepositions and Possessives , 2018, ACL.
[25] Yonatan Belinkov,et al. Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks , 2016, ICLR.
[26] Luke S. Zettlemoyer,et al. AllenNLP: A Deep Semantic Natural Language Processing Platform , 2018, ArXiv.
[27] Sanja Fidler,et al. Skip-Thought Vectors , 2015, NIPS.
[28] Allyson Ettinger,et al. Probing for semantic evidence of composition by means of simple classification tasks , 2016, RepEval@ACL.
[29] Florian Mohnert,et al. Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information , 2018, BlackboxNLP@EMNLP.
[30] Mark Steedman,et al. CCGbank: A Corpus of CCG Derivations and Dependency Structures Extracted from the Penn Treebank , 2007, CL.
[31] Kevin Duh,et al. Inference is Everything: Recasting Semantic Resources into a Unified Evaluation Framework , 2017, IJCNLP.
[32] Holger Schwenk,et al. Supervised Learning of Universal Sentence Representations from Natural Language Inference Data , 2017, EMNLP.
[33] Srinivas Bangalore,et al. Supertagging: An Approach to Almost Parsing , 1999, CL.
[34] Rui Yan,et al. Natural Language Inference by Tree-Based Convolution and Heuristic Matching , 2015, ACL.
[35] Noah D. Goodman,et al. Evaluating Compositionality in Sentence Embeddings , 2018, CogSci.
[36] Noah D. Goodman,et al. DisSent: Sentence Representation Learning from Explicit Discourse Relations , 2017, ArXiv.
[37] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[38] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[39] Hailin Jin,et al. Rethinking Skip-thought: A Neighborhood based Approach , 2017, Rep4NLP@ACL.
[40] Guillaume Lample,et al. What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties , 2018, ACL.
[41] Samuel R. Bowman,et al. Neural Network Acceptability Judgments , 2018, Transactions of the Association for Computational Linguistics.
[42] Ali Farhadi,et al. Bidirectional Attention Flow for Machine Comprehension , 2016, ICLR.
[43] Gemma Boleda,et al. Distributional Semantics in Use , 2015, LSDSem@EMNLP.
[44] Emily M. Bender,et al. Towards Linguistically Generalizable NLP Systems: A Workshop and Shared Task , 2017, Proceedings of the First Workshop on Building Linguistically Generalizable NLP Systems.
[45] Ieva Staliūnaite,et al. Breaking Sentiment Analysis of Movie Reviews , 2017 .
[46] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).