A Survey of the Usages of Deep Learning for Natural Language Processing
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winograd, 1971, Procedures as a representation for data in a computer program for understanding natural language
hennessy, 2017, Computer Architecture A Quantitative Approach
schuman, 2017, A survey of neuromorphic computing and neural networks in hardware, arXiv 1705 06963
bobrow, 1964, Natural language input for a computer problem solving system
nogueira dos santos, 2015, Boosting named entity recognition with neural character embeddings, arXiv 1505 05008
santos, 2006, Harem: An advanced ner evaluation contest for portuguese, Proc LREC, 1986
sang, 2003, Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition, Proc HLT-NAACL, 4, 142
chiu, 2015, Named entity recognition with bidirectional LSTM-CNNs, arXiv 1511 08308
pang, 2016, Text matching as image recognition, Proc 13th AAAI Conf Artif Intell, 2793
bahdanau, 2014, Neural machine translation by jointly learning to align and translate, arXiv 1409 0473
el hihi, 1996, Hierarchical recurrent neural networks for long-term dependencies, Proc NIPS, 493
johnson, 2016, Google’s multilingual neural machine translation system: Enabling zero-shot translation, arXiv 1611 04558
chung, 2014, Empirical evaluation of gated recurrent neural networks on sequence modeling, arXiv 1412 3555
jurafsky, 2017, Speech & language processing
pradhan, 2013, Towards robust linguistic analysis using ontonotes, Proc CoNLL, 143
akbik, 2018, Contextual string embeddings for sequence labeling, Proc COLING, 1638
lafferty, 2001, Conditional random fields: Probabilistic models for segmenting and labeling sequence data, Proc 18th Int Conf Mach Learn, 282
fausett, 1994, Fundamentals of Neural Networks Architectures Algorithms and Applications
mikolov, 2010, Recurrent neural network based language model, Proc 11th Annu Conf Int Speech Commun Assoc, 2, 3
dos santos, 2014, Deep convolutional neural networks for sentiment analysis of short texts, Proc COLING, 69
zeng, 2014, Relation classification via convolutional deep neural network, Proc COLING, 2335
socher, 2011, Dynamic pooling and unfolding recursive autoencoders for paraphrase detection, Proc NIPS, 801
white, 2017, Inference is everything: Recasting semantic resources into a unified evaluation framework, Proc IJCNLP, 1, 996
rahman, 2012, Resolving complex cases of definite pronouns: The winograd schema challenge, Proc Joint EMNLP CoNLL, 777
williams, 2017, A broad-coverage challenge corpus for sentence understanding through inference, arXiv 1704 05426
lin, 2013, Network in network, arXiv 1312 4400
daniluk, 2017, Frustratingly short attention spans in neural language modeling, arXiv 1702 04521
chelba, 2013, One billion word benchmark for measuring progress in statistical language modeling, arXiv 1312 3005
chen, 2008, Evaluation metrics for language models
paulus, 2017, A deep reinforced model for abstractive summarization, arXiv 1705 04304
lu, 2013, A deep architecture for matching short texts, Proc Adv Neural Inf Process Syst, 1367
huang, 2013, Learning deep structured semantic models for Web search using clickthrough data, Proc ACM CIKM, 2333
auer, 2007, DBpedia: A nucleus for a Web of open data, The Semantic Web, 722, 10.1007/978-3-540-76298-0_52
coates, 2013, Deep learning with cots HPC systems, Proc ICML, 1337
goodfellow, 2016, Deep Learning, 1
ciresan, 2011, Flexible, high performance convolutional neural networks for image classification, Proc IJCAI, 22, 1237
bengio, 2003, A neural probabilistic language model, J Mach Learn Res, 3, 1137
brunner, 2018, Natural language multitasking: Analyzing and improving syntactic saliency of hidden representations, arXiv 1801 06024
koehn, 2005, Europarl: A parallel corpus for statistical machine translation, Proc MT Summit, 5, 79
collobert, 2011, Natural language processing (almost) from scratch, J Mach Learn Res, 12, 2493
kumar srivastava, 2015, Highway networks, arXiv 1505 00387
jurafsky, 2000, Speech & language processing
vaswani, 2017, Attention is all you need, Proc NIPS, 6000
nair, 2010, Rectified linear units improve restricted Boltzmann machines, Proc ICML, 807
liu, 2017, Stochastic answer networks for machine reading comprehension, arXiv 1712 03556
devlin, 2018, BERT: Pre-training of deep bidirectional transformers for language understanding, arXiv 1810 04805
luong, 2013, Better word representations with recursive neural networks for morphology, Proc CoNLL, 104
liu, 2018, Stochastic answer networks for natural language inference, arXiv 1804 07888
kim, 2016, Character-aware neural language models, Proc AAAI, 2741
zaremba, 2014, Recurrent neural network regularization, arXiv 1409 2329
botha, 2014, Compositional morphology for word representations and language modelling, Proc ICML, 1899
jozefowicz, 2016, Exploring the limits of language modeling, arXiv 1602 02410
ji, 2015, Document context language models, arXiv 1511 03962
shazeer, 2015, Sparse non-negative matrix language modeling for skip-grams, Proc INTERSPEECH, 1428
mikolov, 2013, Efficient estimation of word representations in vector space, arXiv 1301 3781 [cs]
mikolov, 2013, Distributed representations of words and phrases and their compositionality, Proc NIPS, 3111
radford, 2018, Improving language understanding by generative pre-training
adhikari, 2019, DocBERT: BERT for document classification, arXiv 1904 08398
worsham, 2018, Genre identification and the compositional effect of genre in literature, Proc COLING, 1963
sutton, 1998, Reinforcement Learning An Introduction, 1
smolensky, 1986, Information processing in dynamical systems: Foundations of harmony theory
fletcher, 2013, Practical Methods of Optimization
socher, 2013, Parsing with compositional vector grammars, Proc ACL, 1, 455
socher, 2013, Recursive deep models for semantic compositionality over a sentiment treebank, Proc EMNLP, 1631
lin, 2019, A bert-based universal model for both within-and cross-sentence clinical temporal relation extraction, Proc Clin NLP Workshop, 65
nivre, 2003, An efficient algorithm for projective dependency parsing, Proc Int Workshop Parsing Technol, 149
more, 2018, CONLL-UL: Universal morphological lattices for universal dependency parsing, Proc 11th Int Conf Lang Resour Eval, 3847
vinyals, 2015, Grammar as a foreign Language, Proc NIPS, 2773
huang, 2012, Improving word representations via global context and multiple word prototypes, Proc ACL, 1, 873
cettolo, 2016, An Arabic–Hebrew parallel corpus of TED talks, arXiv 1610 00572
cettolo, 2012, WIT3: Web inventory of transcribed and translated talks, Proc Conf Eur Assoc Mach Transl, 261
kawahara, 2006, Case frame compilation from the Web using high-performance computing, Proc LREC, 1344
kawahara, 2002, Construction of a Japanese relevance-tagged corpus, Proc LREC, 2008
hangyo, 2012, Building a diverse document leads corpus annotated with semantic relations, Proc Pacific–Asia Conf Lang Inf Comput, 535
petrov, 2012, Overview of the 2012 shared task on parsing the Web, Proc Notes 1st Workshop Syntactic Anal Non-Canonical Lang, 59, 1
martin, 2018, Event representations for automated story generation with deep neural nets, Proc 32nd AAAI Conf Artif Intell, 868
tucker, 2019, Genrating believable poetry in multiple languages using GPT-2
radford, 2019, Language models are unsupervised multitask learners, OpenAIRE blog, 1, 9
bena, 2019, Introducing aspects of creativity in automatic poetry generation, Proc Int Conf NLP
jain, 2017, Story generation from sequence of independent short descriptions, arXiv 1707 05501
ren, 2017, Neural joke generation
chippada, 2018, Knowledge amalgam: Generating jokes and quotes together, arXiv 1806 04387
drissi, 2018, Hierarchical text generation using an outline, Proc Int Conf NLP, 180
huang, 2018, Hierarchically structured reinforcement learning for topically coherent visual story generation, arXiv 1805 08191
lin, 2017, Adversarial ranking for language generation, Proc Adv Neural Inf Process Syst, 3155
tambwekar, 2018, Controllable neural story plot generation via reinforcement learning, arXiv 1809 10736
zhang, 2017, Adversarial feature matching for text generation, Proc 34th Int Conf Mach Learn, 70, 4006
chen, 2018, Adversarial text generation via feature-mover’s distance, Proc Adv Neural Inf Process Syst, 4666
guo, 2018, Long text generation via adversarial training with leaked information, Proc 32nd AAAI Conf Artif Intell, 5141
doersch, 2016, Tutorial on variational autoencoders, arXiv 1606 05908
kingma, 2013, Auto-encoding variational Bayes, arXiv 1312 6114
holtzman, 2019, The curious case of neural text degeneration, arXiv 1904 09751
wang, 2019, Topic-guided variational autoencoders for text generation, arXiv 1903 07137
hu, 2017, Toward controlled generation of text, Proc 34th Int Conf Mach Learn, 70, 1587
serban, 2017, A hierarchical latent variable encoder-decoder model for generating dialogues, Proc 31st AAAI Conf Artif Intell, 3295
hershcovich, 2018, Universal dependency parsing with a general transition-based DAG parser, arXiv 1808 09354
zeman, 2018, CoNLL 2018 shared task: Multilingual parsing from raw text to universal dependencies, Proc CoNLL Shared Task Multilingual Parsing Raw Text Universal Dependencies, 1
qi, 2019, Universal dependency parsing from scratch, arXiv 1901 10457
ji, 2018, AntNLP at CoNLL 2018 shared task: A graph-based parser for universal dependency parsing, Proc CoNLL Shared Task Multilingual Parsing Raw Text Universal Dependencies, 248
hu, 2014, Convolutional neural network architectures for matching natural language sentences, Proc NIPS, 2042
krantz, 2018, Abstractive summarization using attentive neural techniques, Proc Int Conf NLP, 1
ranzato, 2015, Sequence level training with recurrent neural networks, arXiv 1511 06732
yang, 2019, End-to-End open-domain question answering with BERTserini, arXiv 1902 01718
raposo, 2017, Discovering objects and their relations from entangled scene representations, arXiv 1702 05068
zhang, 2019, Pretraining-based natural language generation for text summarization, arXiv 1902 09243
gehring, 2017, Convolutional sequence to sequence learning, arXiv 1705 03122
santoro, 0, A simple neural network module for relational reasoning, Proc NIPS, 2017, 4974
agirre, 2012, SemEval-2012 task 6: A pilot on semantic textual similarity, Proc Joint Conf Lexical Comput Semantics, 1, 385
wang, 2007, What is the jeopardy model? A quasi-synchronous grammar for QA, Proc Joint EMNLP CoNLL, 22
le, 2014, Distributed representations of sentences and documents, Proc ICML, 1188
liddy, 2001, Natural language processing, Encyclopedia of Library and Information Science
go, 2009, Twitter sentiment classification using distant supervision, 1
kalchbrenner, 2013, Recurrent continuous translation models, Proc EMNLP, 1700
schwenk, 2012, Continuous space translation models for phrase-based statistical machine translation, Proc COLING, 1071
wu, 2016, Google’s neural machine translation system: Bridging the gap between human and machine translation, arXiv 1609 08144
sutskever, 2014, Sequence to sequence learning with neural networks, Proc NIPS, 3104
stenetorp, 2013, Transition-based dependency parsing using recursive neural networks, Proc Deep Learn Workshop Conf Neural Inf Process Syst (NIPS)
wang, 2018, A neural transition-based approach for semantic dependency graph parsing, Proc 32nd AAAI Conf Artif Intell, 5561
sennrich, 2016, Linguistic input features improve neural machine translation, arXiv 1606 02892
ahmed, 2017, Weighted transformer network for machine translation, arXiv 1711 02132
richard medina, 2018, Parallel attention mechanisms in neural machine translation, arXiv 1810 12427
papineni, 2002, BLEU: A method for automatic evaluation of machine translation, Proc ACL, 311
hochreiter, 2001, Gradient flow in recurrent nets: The difficulty of learning long-term dependencies, A Field Guide to Dynamical Recurrent Neural Networks
cettolo, 2014, Report on the 11th IWSLT evaluation campaign, IWSLT 2014, Proc Int Workshop Spoken Lang Transl, 2
lample, 2019, Cross-lingual language model pretraining, arXiv 1901 07291
xu chen, 2018, The best of both worlds: Combining recent advances in neural machine translation, arXiv 1804 09849
lecun, 1995, Convolutional networks for images, speech, and time series, The Handbook of Brain Theory and Neural Networks, 3361
krizhevsky, 2014, One weird trick for parallelizing convolutional neural networks, arXiv 1404 5997
sheng tai, 2015, Improved semantic representations from tree-structured long short-term memory networks, arXiv 1503 00075
tan, 2018, Deep semantic role labeling with self-attention, Proc 32nd AAAI Conf Artif Intell, 4929
kuang, 2018, Modeling coherence for neural machine translation with dynamic and topic caches, Proc COLING, 596
luong, 2014, Addressing the rare word problem in neural machine translation, arXiv 1410 8206
sennrich, 2015, Neural machine translation of rare words with subword units, arXiv 1508 07909
mager, 2018, Lost in translation: Analysis of information loss during machine translation between polysynthetic and fusional languages, arXiv 1807 00286
ott, 2018, Analyzing uncertainty in neural machine translation, arXiv 1803 00047