暂无分享,去创建一个
[1] Matthew Henderson,et al. The third Dialog State Tracking Challenge , 2014, 2014 IEEE Spoken Language Technology Workshop (SLT).
[2] Ehud Rivlin,et al. Placing search in context: the concept revisited , 2002, TOIS.
[3] Zhen Wang,et al. Knowledge Graph Embedding by Translating on Hyperplanes , 2014, AAAI.
[4] Chris Dyer,et al. Ontologically Grounded Multi-sense Representation Learning for Semantic Vector Space Models , 2015, NAACL.
[5] Felix Hill,et al. SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity , 2016, EMNLP.
[6] Lyan Verwimp,et al. Character-Word LSTM Language Models , 2017, EACL.
[7] Danqi Chen,et al. A Fast and Accurate Dependency Parser using Neural Networks , 2014, EMNLP.
[8] Steve J. Young,et al. Cognitive User Interfaces , 2010, IEEE Signal Processing Magazine.
[9] Steven Skiena,et al. Polyglot: Distributed Word Representations for Multilingual NLP , 2013, CoNLL.
[10] Mark Dredze,et al. Improving Lexical Embeddings with Semantic Knowledge , 2014, ACL.
[11] Kevin Gimpel,et al. From Paraphrase Database to Compositional Paraphrase Model and Back , 2015, Transactions of the Association for Computational Linguistics.
[12] Manaal Faruqui,et al. Improving Vector Space Word Representations Using Multilingual Correlation , 2014, EACL.
[13] David Vandyke,et al. Continuously Learning Neural Dialogue Management , 2016, ArXiv.
[14] Kevin Gimpel,et al. Tailoring Continuous Word Representations for Dependency Parsing , 2014, ACL.
[15] Roi Reichart,et al. Separated by an Un-common Language: Towards Judgment Language Informed Vector Space Modeling , 2015 .
[16] Tie-Yan Liu,et al. Knowledge-Powered Deep Learning for Word Embedding , 2014, ECML/PKDD.
[17] Roy Schwartz,et al. Symmetric Pattern Based Word Embeddings for Improved Word Similarity Prediction , 2015, CoNLL.
[18] Anna Korhonen,et al. On the Role of Seed Lexicons in Learning Bilingual Word Embeddings , 2016, ACL.
[19] Ryan Cotterell,et al. The SIGMORPHON 2016 Shared Task—Morphological Reinflection , 2016, SIGMORPHON.
[20] Parminder Bhatia,et al. Morphological Priors for Probabilistic Neural Word Embeddings , 2016, EMNLP.
[21] Yu Hu,et al. Learning Semantic Word Embeddings based on Ordinal Knowledge Constraints , 2015, ACL.
[22] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[23] Mathias Creutz,et al. Unsupervised models for morpheme segmentation and morphology learning , 2007, TSLP.
[24] Maxine Eskénazi,et al. Recipe For Building Robust Spoken Dialog State Trackers: Dialog State Tracking Challenge System Description , 2013, SIGDIAL Conference.
[25] Patrick Pantel,et al. From Frequency to Meaning: Vector Space Models of Semantics , 2010, J. Artif. Intell. Res..
[26] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[27] David Vandyke,et al. A Network-based End-to-End Trainable Task-oriented Dialogue System , 2016, EACL.
[28] Geoffrey E. Hinton,et al. Rectified Linear Units Improve Restricted Boltzmann Machines , 2010, ICML.
[29] Christopher D. Manning,et al. Bilingual Word Representations with Monolingual Quality in Mind , 2015, VS@HLT-NAACL.
[30] Chris Callison-Burch,et al. PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification , 2015, ACL.
[31] David Vandyke,et al. Multi-domain Dialog State Tracking using Recurrent Neural Networks , 2015, ACL.
[32] Simone Paolo Ponzetto,et al. BabelNet: The automatic construction, evaluation and application of a wide-coverage multilingual semantic network , 2012, Artif. Intell..
[33] Anna Korhonen,et al. Is "Universal Syntax" Universally Useful for Learning Distributed Word Representations? , 2016, ACL.
[34] Ngoc Thang Vu,et al. Integrating Distributional Lexical Contrast into Word Embeddings for Antonym-Synonym Distinction , 2016, ACL.
[35] Antoine Raux,et al. The Dialog State Tracking Challenge Series: A Review , 2016, Dialogue Discourse.
[36] Jan Snajder,et al. DErivBase: Inducing and Evaluating a Derivational Morphology Resource for German , 2013, ACL.
[37] Matthew Henderson,et al. Robust dialog state tracking using delexicalised recurrent neural networks and unsupervised adaptation , 2014, 2014 IEEE Spoken Language Technology Workshop (SLT).
[38] Steve Young,et al. Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints , 2017 .
[39] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[40] Shashi Narayan,et al. Encoding Prior Knowledge with Eigenword Embeddings , 2015, TACL.
[41] Christo Kirov,et al. A Language-Independent Feature Schema for Inflectional Morphology , 2015, ACL.
[42] Christopher D. Manning,et al. Better Word Representations with Recursive Neural Networks for Morphology , 2013, CoNLL.
[43] Daniel Jurafsky,et al. Knowledge-Free Induction of Inflectional Morphologies , 2001, NAACL.
[44] Kris Cao,et al. A Joint Model for Word Embedding and Word Morphology , 2016, Rep4NLP@ACL.
[45] Phil Blunsom,et al. Compositional Morphology for Word Representations and Language Modelling , 2014, ICML.
[46] Felix Hill,et al. SimLex-999: Evaluating Semantic Models With (Genuine) Similarity Estimation , 2014, CL.
[47] Roy Schwartz,et al. Symmetric Patterns and Coordinations: Fast and Enhanced Representations of Verbs and Adjectives , 2016, HLT-NAACL.
[48] Tie-Yan Liu,et al. Co-learning of Word Representations and Morpheme Representations , 2014, COLING.
[49] Ryan Cotterell,et al. Morphological Smoothing and Extrapolation of Word Embeddings , 2016, ACL.
[50] Omer Levy,et al. Dependency-Based Word Embeddings , 2014, ACL.
[51] Yulia Tsvetkov,et al. Morphological Inflection Generation Using Character Sequence to Sequence Learning , 2015, NAACL.
[52] James Richard Curran,et al. From distributional to semantic similarity , 2004 .
[53] Ryan Cotterell,et al. Morphological Word-Embeddings , 2019, NAACL.
[54] Philipp Cimiano,et al. Representing Multilingual Data as Linked Data: the Case of BabelNet 2.0 , 2014, LREC.
[55] Marco Marelli,et al. Compositional-ly Derived Representations of Morphologically Complex Words in Distributional Semantics , 2013, ACL.
[56] Fei Liu,et al. Dialog state tracking, a machine reading approach using Memory Network , 2016, EACL.
[57] Filip Jurcícek,et al. Incremental LSTM-based dialog state tracker , 2015, 2015 IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU).
[58] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..
[59] Kevin Gimpel,et al. Charagram: Embedding Words and Sentences via Character n-grams , 2016, EMNLP.
[60] Matthew Henderson,et al. Word-Based Dialog State Tracking with Recurrent Neural Networks , 2014, SIGDIAL Conference.
[61] Ryan Cotterell,et al. Neural Multi-Source Morphological Reinflection , 2016, EACL.
[62] Matthew Henderson,et al. The Second Dialog State Tracking Challenge , 2014, SIGDIAL Conference.
[63] Christopher D. Manning,et al. Bilingual Word Embeddings for Phrase-Based Machine Translation , 2013, EMNLP.
[64] Alexander M. Rush,et al. Character-Aware Neural Language Models , 2015, AAAI.
[65] Chris Callison-Burch,et al. PPDB: The Paraphrase Database , 2013, NAACL.
[66] Yoav Goldberg,et al. Morphological Inflection Generation with Hard Monotonic Attention , 2016, ACL.
[67] Yoshua Bengio,et al. Word Representations: A Simple and General Method for Semi-Supervised Learning , 2010, ACL.
[68] Elia Bruni,et al. Multimodal Distributional Semantics , 2014, J. Artif. Intell. Res..
[69] Cícero Nogueira dos Santos,et al. Learning Character-level Representations for Part-of-Speech Tagging , 2014, ICML.
[70] Georgiana Dinu,et al. Improving zero-shot learning by mitigating the hubness problem , 2014, ICLR.
[71] Philipp Koehn,et al. Enriching Morphologically Poor Languages for Statistical Machine Translation , 2008, ACL.
[72] Julien Perez,et al. Gated End-to-End Memory Networks , 2016, EACL.
[73] Ryan Cotterell,et al. Joint Semantic Synthesis and Morphological Analysis of the Derived Word , 2017, TACL.
[74] Yannick Versley,et al. Statistical Parsing of Morphologically Rich Languages (SPMRL) What, How and Whither , 2010, SPMRL@NAACL-HLT.
[75] Stephen Clark,et al. Specializing Word Embeddings for Similarity or Relatedness , 2015, EMNLP.
[76] David Vandyke,et al. On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems , 2016, ACL.
[77] Anders Søgaard,et al. Any-language frame-semantic parsing , 2015, EMNLP.
[78] Ido Dagan,et al. context2vec: Learning Generic Context Embedding with Bidirectional LSTM , 2016, CoNLL.
[79] Miroslav Vodolán,et al. Hybrid Dialog State Tracker with ASR Features , 2017, EACL.
[80] Zellig S. Harris,et al. Distributional Structure , 1954 .
[81] David Vandyke,et al. Counter-fitting Word Vectors to Linguistic Constraints , 2016, NAACL.
[82] Radu Soricut,et al. Unsupervised Morphology Induction Using Word Embeddings , 2015, NAACL.
[83] Koray Kavukcuoglu,et al. Learning word embeddings efficiently with noise-contrastive estimation , 2013, NIPS.
[84] Gang Wang,et al. RC-NET: A General Framework for Incorporating Knowledge into Word Representations , 2014, CIKM.
[85] Tsung-Hsien Wen,et al. Neural Belief Tracker: Data-Driven Dialogue State Tracking , 2016, ACL.