Word-order Biases in Deep-agent Emergent Communication
暂无分享,去创建一个
Eugene Kharitonov | Alessandro Lazaric | Rahma Chaabouni | Emmanuel Dupoux | Marco Baroni | A. Lazaric | Marco Baroni | Emmanuel Dupoux | E. Kharitonov | Rahma Chaabouni
[1] Pieter Abbeel,et al. Emergence of Grounded Compositional Language in Multi-Agent Populations , 2017, AAAI.
[2] Julie M. Hupp,et al. Evidence for a domain-general mechanism underlying the suffixation preference in language , 2009 .
[3] Kyunghyun Cho,et al. Emergent Communication in a Multi-Modal, Multi-Step Referential Game , 2017, ICLR.
[4] Ken Hale. Basic word order in two “free word order” languages , 1992 .
[5] Joseph H. Greenberg,et al. Some Universals of Grammar with Particular Reference to the Order of Meaningful Elements , 1990, On Language.
[6] John A. Hawkins,et al. A Performance Theory of Order and Constituency , 1995 .
[7] Anna L. Theakston,et al. Iconicity affects children’s comprehension of complex sentences: The role of semantics, clause order, input and individual differences , 2018, Cognition.
[8] Lior Wolf,et al. Using the Output Embedding to Improve Language Models , 2016, EACL.
[9] Marco Baroni,et al. Generalization without Systematicity: On the Compositional Skills of Sequence-to-Sequence Recurrent Networks , 2017, ICML.
[10] Yu-Jung Heo,et al. Answerer in Questioner's Mind for Goal-Oriented Visual Dialogue , 2018, ArXiv.
[11] George Kingsley Zipf,et al. Human behavior and the principle of least effort , 1949 .
[12] Sanjiv Kumar,et al. On the Convergence of Adam and Beyond , 2018 .
[13] Maryia Fedzechkinaa,et al. Miniature artificial language learning as a complement to typological data , 2015 .
[14] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[15] Holger Diessel,et al. Iconicity of sequence: A corpus-based analysis of the positioning of temporal adverbial clauses in English , 2008 .
[16] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[17] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[18] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[19] Nando de Freitas,et al. Compositional Obverter Communication Learning From Raw Visual Input , 2018, ICLR.
[20] Marianne Mithun,et al. Is basic word order universal , 1987 .
[21] Jason Lee,et al. Emergent Translation in Multi-Agent Communication , 2017, ICLR.
[22] Solomon Kullback,et al. Information Theory and Statistics , 1960 .
[23] Meng Zhang,et al. Neural Network Methods for Natural Language Processing , 2017, Computational Linguistics.
[24] S. Kirby,et al. Iterated learning and the evolution of language , 2014, Current Opinion in Neurobiology.
[25] Solomon Marcus,et al. SYNTACTIC ICONICITY, WITHIN AND BEYOND ITS ACCEPTED PRINCIPLES , 2010 .
[26] John Haiman,et al. THE ICONICITY OF GRAMMAR: ISOMORPHISM AND MOTIVATION , 1980 .
[27] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[28] Rong Jin,et al. Learning with Multiple Labels , 2002, NIPS.
[29] Marco Baroni,et al. How agents see things: On visual representations in an emergent language game , 2018, EMNLP.
[30] Emil Gustavsson,et al. Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence , 2016, ArXiv.
[31] E. Gibson. Linguistic complexity: locality of syntactic dependencies , 1998, Cognition.
[32] Richard Futrell,et al. Large-scale evidence of dependency length minimization in 37 languages , 2015, Proceedings of the National Academy of Sciences.
[33] Comrie Bernard. Language Universals and Linguistic Typology , 1982 .
[34] Elizabeth Closs Traugott,et al. A History of English Syntax , 1971 .
[35] Alexander Peysakhovich,et al. Multi-Agent Cooperation and the Emergence of (Natural) Language , 2016, ICLR.
[36] René Dirven,et al. Cognitive English Grammar , 2007 .
[37] Michael C. Frank,et al. The learnability of constructed languages reflects typological patterns , 2011, CogSci.
[38] Stephen Clark,et al. Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input , 2018, ICLR.
[39] F. Newmeyer. Iconicity and generative grammar , 1992 .
[40] Ivan Titov,et al. Emergence of Language with Multi-agent Games: Learning to Communicate with Sequences of Symbols , 2017, NIPS.
[41] José M. F. Moura,et al. Natural Language Does Not Emerge ‘Naturally’ in Multi-Agent Dialog , 2017, EMNLP.
[42] Guigang Zhang,et al. Deep Learning , 2016, Int. J. Semantic Comput..
[43] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[44] Elissa L. Newport,et al. Balancing Effort and Information Transmission During Language Acquisition: Evidence From Word Order and Case Marking , 2017, Cogn. Sci..
[45] Yann Dauphin,et al. Deal or No Deal? End-to-End Learning of Negotiation Dialogues , 2017, EMNLP.
[46] Ting Qian,et al. Cue Effectiveness in Communicatively Efficient Discourse Production , 2012, Cogn. Sci..