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Natural language understanding (NLU) of text is a fundamental challenge in AI, and it has received significant attention throughout the history of NLP research.
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Programs with common sense
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Conceptual dependency: A theory of natural language understanding
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A Framework for Representing Knowledge
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R. C. Schank and R. P. Abelson · 1975
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The concept of a linguistic variable and its application to approximate reasoning—I
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An example for natural language understanding and the AI problems it raises
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Scenes-and-frames semantics
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The Process of Question Answering
W. G. Lehnert · 1977
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Representations of Knowledge in a Program for Solving Physics Problems
G. Novak · 1977
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PRUF—a meaning representation language for natural languages
L. A. Zadeh · 1978
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P. N. Johnson-Laird · 1980
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Lexical-functional grammar: A formal system for grammatical representation
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The presocratic philosophers: A critical history with a selcetion of texts
G. S. Kirk, J. E. Raven, and M. Schofield · 1983
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The role of frame-based representation in reasoning
R. Fikes and T. Kehler · 1985
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The role of hierarchical knowledge representation in decisionmaking and system management
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Anaphora resolution: a multi-strategy approach
J. G. Carbonell and R. D. Brown · 1988
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Interpretation as Abduction
J. R. Hobbs, M. E. Stickel, P. A. Martin, and D. Edwards · 1988
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Society of mind
M. Minsky · 1988
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Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference
J. Pearl · 1988
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Learning representations by back-propagating errors
D. E. Rumelhart, G. E. Hinton, and R. J. Williams · 1988
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Word Association Norms, Mutual Information and Lexicography
K. W. Church and P. Hanks · 1989
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On the approximate realization of continuous mappings by neural networks
K.-I. Funahashi · 1989
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Induction: Processes of inference, learning, and discovery
J. H. Holland, K. J. Holyoak, R. E. Nisbett, and P. R. Thagard · 1989
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The symbol grounding problem
S. Harnad · 1990
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Formalizing common sense: papers , volume 5
J. McCarthy and V. Lifschitz · 1990
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A methodology for using a default and abductive reasoning system
D. Poole · 1990
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Abductive and Default Reasoning: A Computational Core
B. Selman and H. J. Levesque · 1990
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Class-based n-gram models of natural language
P. F. Brown, P. V. Desouza, R. L. Mercer, V. J. D. Pietra, and J. C. Lai · 1992
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Alfarabi, Avicenna, and Averroes on intellect: their cosmologies, theories of the active intellect, and theories of human intellect
H. A. Davidson · 1992
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The Turing Test is not a trick: Turing indistinguishability is a scientific criterion
S. Harnad · 1992
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Human reasoning: The psychology of deduction
J. S. B. Evans, S. E. Newstead, and R. M. Byrne · 1993
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Interpretation as abduction
J. R. Hobbs, M. E. Stickel, D. E. Appelt, and P. Martin · 1993
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Making the abstraction hierarchy concrete
A. M. Bisantz and K. J. Vicente · 1994
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CYC: A large-scale investment in knowledge infrastructure
D. B. Lenat · 1995
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Using decision trees for coreference resolution
J. F. McCarthy · 1995
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WordNet: a lexical database for English
G. Miller · 1995
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Sparse approximate solutions to linear systems
B. K. Natarajan · 1995
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Attention allocation within the abstraction hierarchy
M. E. Janzen and K. J. Vicente · 1997
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The berkeley framenet project
C. F. Baker, C. J. Fillmore, and J. B. Lowe · 1998
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Text categorization with support vector machines: Learning with many relevant features
T. Joachims · 1998
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Part of speech tagging using a network of linear separators
D. Roth and D. Zelenko · 1998
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Collective dynamics of ‘small-world’networks
D. J. Watts and S. H. Strogatz · 1998
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Deep Read: A Reading Comprehension System
L. Hirschman, M. Light, E. Breck, and J. D. Burger · 1999
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The Turing Test: the first 50 years
R. M. French · 2000
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Beyond the Turing test
J. Hernandez-Orallo · 2000
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Scaling question answering to the Web
C. C. T. Kwok, O. Etzioni, and D. S. Weld · 2001
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The use of classifiers in sequential inference
V. Punyakanok and D. Roth · 2001
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An analysis of the AskMSR question-answering system
E. Brill, S. Dumais, and M. Banko · 2002
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The average distances in random graphs with given expected degrees
F. Chung and L. Lu · 2002
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Automatic labeling of semantic roles
D. Gildea and D. Jurafsky · 2002
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From TreeBank to PropBank
P. Kingsbury and M. Palmer · 2002
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Summarization beyond sentence extraction: A probabilistic approach to sentence compression
K. Knight and D. Marcu · 2002
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Learning Question Classifiers
X. Li and D. Roth · 2002
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Performance issues and error analysis in an open-domain question answering system
D. Moldovan, M. Paşca, S. Harabagiu, and M. Surdeanu · 2003
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VerbOcean: Mining the Web for Fine-Grained Semantic Verb Relations
T. Chklovski and P. Pantel · 2004
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Speech summarization: an approach through word extraction and a method for evaluation
C. Hori and F. Sadaoki · 2004
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Attention: Theory and practice
A. Johnson and R. W. Proctor · 2004
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ConceptNet—a practical commonsense reasoning tool-kit
H. Liu and P. Singh · 2004
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The NomBank project: An interim report
A. Meyers, R. Reeves, C. Macleod, R. Szekely, V. Zielinska, B. Young, and R. Grishman · 2004
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Mapping Dependencies Trees: An Application to Question Answering
V. Punyakanok, D. Roth, and W. Yih · 2004
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A linear programming formulation for global inference in natural language tasks
D. Roth and W. Yih · 2004
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Selected Grand Challenges in Cognitive Science
R. Brachman, D. Gunning, S. Bringsjord, M. Genesereth, L. Hirschman, and L. Ferro · 2005
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The role of semantic roles in disambiguating verb senses
H. T. Dang and M. Palmer · 2005
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The proposition bank: An annotated corpus of semantic roles
M. Palmer, D. Gildea, and P. Kingsbury · 2005
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Solving the symbol grounding problem: a critical review of fifteen years of research
M. Taddeo and L. Floridi · 2005
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Learning to map sentences to logical form: Structured classification with probabilistic categorial grammars
L. S. Zettlemoyer and M. Collins · 2005
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Integrating Linguistic Resources: The American National Corpus Model
N. Ide and K. Suderman · 2006
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Markov Logic Networks
M. Richardson and P. Domingos · 2006
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Open Information Extraction from the Web
M. Banko, M. J. Cafarella, S. Soderland, M. Broadhead, and O. Etzioni · 2007
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Computing semantic relatedness using wikipedia-based explicit semantic analysis
E. Gabrilovich and S. Markovitch · 2007
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Higher-order lexical semantic models for non-factoid answer reranking
D. Fried, P. Jansen, G. Hahn-Powell, M. Surdeanu, and P. Clark · 2015
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Combining vector space embeddings with symbolic logical inference over open-domain text
M. Gardner, P. Talukdar, and T. Mitchell · 2015
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Teaching Machines to Read and Comprehend
K. M. Hermann, T. Kociský, E. Grefenstette, L. Espeholt, W. Kay, M. Suleyman, and P. Blunsom · 2015
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Exploring Markov Logic Networks for Question Answering
T. Khot, N. Balasubramanian, E. Gribkoff, A. Sabharwal, P. Clark, and O. Etzioni · 2015
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Word Embedding Revisited: A New Representation Learning and Explicit Matrix Factorization Perspective
Y. Li, L. Xu, F. Tian, L. Jiang, X. Zhong, and E. Chen · 2015
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Machine Comprehension with Discourse Relations
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Question answering based on semantic roles
M. Kaisser and B. Webber · 2007
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A probabilistic graphical model for joint answer ranking in question answering
J. Ko, E. Nyberg, and L. Si · 2007
Cited alongside, same era.
Classifying What-Type Questions by Head Noun Tagging
F. Li, X. Zhang, J. Yuan, and X. Zhu · 2007
Cited alongside, same era.
Wikify!: linking documents to encyclopedic knowledge
R. Mihalcea and A. Csomai · 2007
Cited alongside, same era.
Using Semantic Roles to Improve Question Answering
D. Shen and M. Lapata · 2007
Cited alongside, same era.
The Sixth PASCAL Recognizing Textual Entailment Challenge
L. Bentivogli, P. Clark, I. Dagan, and D. Giampiccolo · 2008
Cited alongside, same era.
K. Narasimhan and R. Barzilay · 2015
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Using key concepts in a translation model for retrieval
J. H. Park and W. B. Croft · 2015
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Reasoning about quantities in natural language
S. Roy, T. Vieira, and D. Roth · 2015
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Observed versus latent features for knowledge base and text inference
K. Toutanova and D. Chen · 2015
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A Transition-based Algorithm for AMR Parsing
C. Wang, N. Xue, S. Pradhan, and S. Pradhan · 2015
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From Paraphrase Database to Compositional Paraphrase Model and Back
J. Wieting, M. Bansal, K. Gimpel, K. Livescu, and D. Roth · 2015
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WikiQA: A Challenge Dataset for Open-Domain Question Answering
Y. Yang, W. Yih, and C. Meek · 2015
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Labeling the semantic roles of commas
N. Arivazhagan, C. Christodoulopoulos, and D. Roth · 2016
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A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
D. Chen, J. Bolton, and C. D. Manning · 2016
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My Computer is an Honor Student — but how Intelligent is it? Standardized Tests as a Measure of AI
P. Clark and O. Etzioni · 2016
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Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions
P. Clark, O. Etzioni, T. Khot, A. Sabharwal, O. Tafjord, P. Turney, and D. Khashabi · 2016
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IKE - An Interactive Tool for Knowledge Extraction
B. Dalvi, S. Bhakthavatsalam, and P. Clark · 2016
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What happens next? event prediction using a compositional neural network model
M. Granroth-Wilding and S. Clark · 2016
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What’s in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams
P. Jansen, N. Balasubramanian, M. Surdeanu, and P. Clark · 2016
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A Study of Automatically Acquiring Explanatory Inference Patterns from Corpora of Explanations: Lessons from Elementary Science Exams
P. A. Jansen · 2016
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Question answering via integer programming over semi-structured knowledge
D. Khashabi, T. Khot, A. Sabharwal, P. Clark, O. Etzioni, and D. Roth · 2016
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Semantic parsing to probabilistic programs for situated question answering
J. Krishnamurthy, O. Tafjord, and A. Kembhavi · 2016
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MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
T. Nguyen, M. Rosenberg, X. Song, J. Gao, S. Tiwary, R. Majumder, and L. Deng · 2016
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A Decomposable Attention Model for Natural Language Inference
A. P. Parikh, O. Täckström, D. Das, and J. Uszkoreit · 2016
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SQuAD: 100,000+ Questions for Machine Comprehension of Text
P. Rajpurkar, J. Zhang, K. Lopyrev, and P. Liang · 2016
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Illinois Named Entity Recognizer: Addendum to Ratinov and Roth ’09 reporting improved results, 2016
T. Redman, M. Sammons, and D. Roth · 2016
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Neural semantic role labeling with dependency path embeddings
M. Roth and M. Lapata · 2016
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Bidirectional attention flow for machine comprehension
M. Seo, A. Kembhavi, A. Farhadi, and H. Hajishirzi · 2016
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Convolutional Neural Networks vs. Convolution Kernels: Feature Engineering for Answer Sentence Reranking
K. Tymoshenko, D. Bonadiman, and A. Moschitti · 2016
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Inner Attention based Recurrent Neural Networks for Answer Selection
B. Wang, K. Liu, and J. Zhao · 2016
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Attention-based convolutional neural network for machine comprehension
W. Yin, S. Ebert, and H. Schütze · 2016
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Enhanced LSTM for Natural Language Inference
Q. Chen, X. Zhu, Z. Ling, S. Wei, H. Jiang, and D. Inkpen · 2017
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Verb Physics: Relative Physical Knowledge of Actions and Objects
M. Forbes and Y. Choi · 2017
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Framing QA as Building and Ranking Intersentence Answer Justifications
P. Jansen, R. Sharp, M. Surdeanu, and P. Clark · 2017
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Adversarial Examples for Evaluating Reading Comprehension Systems
P. Jia and P. Liang · 2017
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TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
M. Joshi, E. Choi, D. S. Weld, and L. Zettlemoyer · 2017
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Are You Smarter Than A Sixth Grader? Textbook Question Answering for Multimodal Machine Comprehension
A. Kembhavi, M. Seo, D. Schwenk, J. Choi, A. Farhadi, and H. Hajishirzi · 2017
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Learning what is essential in questions
D. Khashabi, T. Khot, A. Sabharwal, and D. Roth · 2017
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Answering Complex Questions Using Open Information Extraction
T. Khot, A. Sabharwal, and P. Clark · 2017
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RACE: Large-scale ReAding Comprehension Dataset From Examinations
G. Lai, Q. Xie, H. Liu, Y. Yang, and E. H. Hovy · 2017
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Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
A. McCallum, A. Neelakantan, R. Das, and D. Belanger · 2017
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Universal Semantic Parsing
S. Reddy, O. Täckström, S. Petrov, M. Steedman, and M. Lapata · 2017
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Efficiently Answering Technical Questions-A Knowledge Graph Approach
S. Yang, L. Zou, Z. Wang, J. Yan, and J.-R. Wen · 2017
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Ordinal Common-sense Inference
S. Zhang, R. Rudinger, K. Duh, and B. V. Durme · 2017
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Commonsense for Generative Multi-Hop Question Answering Tasks
L. Bauer, Y. Wang, and M. Bansal · 2018
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Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
P. Clark, I. Cowhey, O. Etzioni, T. Khot, A. Sabharwal, C. Schoenick, and O. Tafjord · 2018
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Learning Scalar Adjective Intensity from Paraphrases
A. Cocos, V. Wharton, E. Pavlick, M. Apidianaki, and C. Callison-Burch · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2018
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AllenNLP: A Deep Semantic Natural Language Processing Platform
M. Gardner, J. Grus, M. Neumann, O. Tafjord, P. Dasigi, N. Liu, M. Peters, M. Schmitz, and L. Zettlemoyer · 2018
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Annotation Artifacts in Natural Language Inference Data
S. Gururangan, S. Swayamdipta, O. Levy, R. Schwartz, S. Bowman, and N. A. Smith · 2018
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Reinforced mnemonic reader for machine reading comprehension
M. Hu, Y. Peng, Z. Huang, X. Qiu, F. Wei, and M. Zhou · 2018
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P. A. Jansen, E. Wainwright, S. Marmorstein, and C. T. Morrison · 2018
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How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks
D. Kaushik and Z. C. Lipton · 2018
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Temporal Information Extraction by Predicting Relative Time-lines
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Constructing Narrative Event Evolutionary Graph for Script Event Prediction
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Multi-Hop Knowledge Graph Reasoning with Reward Shaping
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Stochastic answer networks for machine reading comprehension
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Robust handling of polysemy via sparse representations
A. A. Mahabal, D. Roth, and S. Mittal · 2018
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MITRE at SemEval-2018 Task 11: Commonsense Reasoning without Commonsense Knowledge
E. Merkhofer, J. Henderson, D. Bloom, L. Strickhart, and G. Zarrella · 2018
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J. Ni, C. Zhu, W. Chen, and J. McAuley · 2018
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SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge
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Hypothesis Only Baselines in Natural Language Inference
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Know What You Don’t Know: Unanswerable Questions for SQuAD
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Event2Mind: Commonsense Inference on Events, Intents, and Reactions
H. Rashkin, M. Sap, E. Allaway, N. A. Smith, and Y. Choi · 2018
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Reasoning about Actions and State Changes by Injecting Commonsense Knowledge
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Multi-granularity hierarchical attention fusion networks for reading comprehension and question answering
W. Wang, M. Yan, and C. Wu · 2018
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Extracting Commonsense Properties from Embeddings with Limited Human Guidance
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SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference
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