LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better
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John Hale | Stephen Clark | Chris Dyer | Phil Blunsom | Dani Yogatama | Adhiguna Kuncoro | Dani Yogatama | Chris Dyer | John Hale | S. Clark | P. Blunsom | A. Kuncoro | Phil Blunsom
[1] Edouard Grave,et al. Colorless Green Recurrent Networks Dream Hierarchically , 2018, NAACL.
[2] P. Johnson-Laird. Mental models , 1989 .
[3] Alexander S. Yeh,et al. More accurate tests for the statistical significance of result differences , 2000, COLING.
[4] Frederick Jelinek,et al. Structured language modeling , 2000, Comput. Speech Lang..
[5] Percy Liang,et al. Adversarial Examples for Evaluating Reading Comprehension Systems , 2017, EMNLP.
[6] Noah A. Smith,et al. What Do Recurrent Neural Network Grammars Learn About Syntax? , 2016, EACL.
[7] Eugene Charniak,et al. Parsing as Language Modeling , 2016, EMNLP.
[8] James Henderson,et al. Discriminative Training of a Neural Network Statistical Parser , 2004, ACL.
[9] Bob Carpenter,et al. Probabilistic Parsing using Left Corner Language Models , 1997, IWPT.
[10] WILLIAM MARSLEN-WILSON,et al. Linguistic Structure and Speech Shadowing at Very Short Latencies , 1973, Nature.
[11] Dan Klein,et al. Improving Neural Parsing by Disentangling Model Combination and Reranking Effects , 2017, ACL.
[12] William Schuler,et al. Broad-Coverage Parsing Using Human-Like Memory Constraints , 2010, CL.
[13] Beatrice Santorini,et al. Building a Large Annotated Corpus of English: The Penn Treebank , 1993, CL.
[14] Eugene Charniak,et al. Statistical Techniques for Natural Language Parsing , 1997, AI Mag..
[15] Julie C. Sedivy,et al. Subject Terms: Linguistics Language Eyes & eyesight Cognition & reasoning , 1995 .
[16] John Hale,et al. Automaton Theories of Human Sentence Comprehension , 2014 .
[17] Rico Sennrich,et al. How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs , 2016, EACL.
[18] Stanislas Dehaene,et al. Neurophysiological dynamics of phrase-structure building during sentence processing , 2017, Proceedings of the National Academy of Sciences.
[19] Chris Dyer,et al. On the State of the Art of Evaluation in Neural Language Models , 2017, ICLR.
[20] Philip Resnik,et al. Left-Corner Parsing and Psychological Plausibility , 1992, COLING.
[21] Wang Ling,et al. Memory Architectures in Recurrent Neural Network Language Models , 2018, ICLR.
[22] Kevin Duh,et al. DyNet: The Dynamic Neural Network Toolkit , 2017, ArXiv.
[23] Ahmad Emami,et al. A Neural Syntactic Language Model , 2005, Machine Learning.
[24] James Henderson. Inducing History Representations for Broad Coverage Statistical Parsing , 2003, HLT-NAACL.
[25] Mark Steedman,et al. Unbounded Dependency Recovery for Parser Evaluation , 2009, EMNLP.
[26] Christopher D. Manning,et al. Get To The Point: Summarization with Pointer-Generator Networks , 2017, ACL.
[27] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[28] Mark Johnson,et al. Memory requirements and local ambiguities of parsing strategies , 1991 .
[29] Yonghui Wu,et al. Exploring the Limits of Language Modeling , 2016, ArXiv.
[30] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[31] Noah A. Smith,et al. Recurrent Neural Network Grammars , 2016, NAACL.
[32] Emmanuel Dupoux,et al. Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies , 2016, TACL.
[33] Eugene Charniak,et al. Top-Down Nearly-Context-Sensitive Parsing , 2010, EMNLP.
[34] Stephen Pulman,et al. Grammars, parsers, and memory limitations , 1986 .
[35] Emmanuel Dupoux,et al. Comparing Character-level Neural Language Models Using a Lexical Decision Task , 2017, EACL.