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In recent years, neural networks have shown impressive performance gains on long-standing AI problems, and in particular, answering queries from natural language text.
Q-learning
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Panupong Pasupat and Percy Liang · 2015
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Towards ai-complete question answering: A set of prerequisite toy tasks
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Db-ir integration using tight-coupling in the odysseus dbms
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Understanding Neural Networks through Representation Erasure
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SQuAD: 100,000+ Questions for Machine Comprehension of Text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin · 2016
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End-to-end Differentiable Proving
Tim Rocktäschel and Sebastian Riedel · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Lilon Jones, Aidan Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Dissecting Contextual Word Embeddings: Architecture and Representation
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BERT and PALs: Projected attention layers for efficient adaptation in multi-task learning
Asa Cooper Stickland and Iain Murray · 2019
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What do you learn from context? Probing for sentence structure in contextualized word representations
Ian Tenney, Patrick Xia, Berlin Chen, Alex Wang, Adam Poliak, R. Thomas McCoy, Najoung Kim, Benjamin Van Durme, Samuel R Bowman, Dipanjan Das, and Ellie Pavlick · 2019
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Language Models are Few-Shot Learners
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Improving Language Understanding by Generative Pre-Training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Know what you don’t know: Unanswerable questions for SQuAD
Pranav Rajpurkar, Robin Jia, and Percy Liang · 2018
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Interpretation of natural language rules in conversational machine reading
Marzieh Saeidi, Max Bartolo, Patrick Lewis, Sameer Singh, Tim Rocktäschel, Mike Sheldon, Guillaume Bouchard, and Sebastian Riedel · 2018
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The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant · 2018
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FEVER: a large-scale dataset for Fact Extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal · 2018
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Constructing datasets for multi-hop reading comprehension across documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel · 2018
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Transformers as Soft Reasoners over Language
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REALM : Retrieval-Augmented Language Model Pre-Training
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Kilt: a benchmark for knowledge intensive language tasks
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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Linformer: Self-Attention with Linear Complexity
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Huggingface’s transformers: State-of-the-art natural language processing, 2020
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