Computational Linguistics: Publications
Books
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[1]
Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse
Chris Heunen‚ Mehrnoosh Sadrzadeh and Edward Grefenstette, editors
Oxford University Press. February, 2013.
Details about Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse | BibTeX data for Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse | Link to Quantum Physics and Linguistics: A Compositional‚ Diagrammatic Discourse
Book chapters
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[1]
Collapsed Variational Bayesian Inference for Hidden Markov Models
Pengyu Wang and Phil Blunsom
In AISTATS. 2013.
Details about Collapsed Variational Bayesian Inference for Hidden Markov Models | BibTeX data for Collapsed Variational Bayesian Inference for Hidden Markov Models
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[2]
Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras
Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh‚ Stephen Pulman and Bob Coecke
In A. Chubb J. Eskandarian and V. Harizanov, editors, Logic and Algebraic Structures in Quantum Computing and Information. Cambridge University Press. 2013.
To appear
Details about Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras | BibTeX data for Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras | Download ?(pdf) of Reasoning about Meaning in Natural Language with Compact Closed Categories and Frobenius Algebras
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[3]
Bayesian Synchronous Grammar Induction
Phil Blunsom‚ Trevor Cohn and Miles Osborne
In D. Koller‚ D. Schuurmans‚ Y. Bengio and L. Bottou, editors, Advances in Neural Information Processing Systems 21. Pages 161–168. 2008.
Details about Bayesian Synchronous Grammar Induction | BibTeX data for Bayesian Synchronous Grammar Induction
Journal papers
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[1]
New Directions in Vector Space Models of Meaning
Edward Grefenstette‚ Karl Moritz Hermann‚ Georgiana Dinu and Phil Blunsom
In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. June, 2014.
Details about New Directions in Vector Space Models of Meaning | BibTeX data for New Directions in Vector Space Models of Meaning | Download (pdf) of New Directions in Vector Space Models of Meaning
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[2]
A Deep Architecture for Semantic Parsing
Edward Grefenstette‚ Phil Blunsom‚ Nando de Freitas and Karl Moritz Hermann
In Proceedings of the ACL 2014 Workshop on Semantic Parsing. June, 2014.
Details about A Deep Architecture for Semantic Parsing | BibTeX data for A Deep Architecture for Semantic Parsing | Link to A Deep Architecture for Semantic Parsing
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[3]
Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning
Edward Grefenstette and Mehrnoosh Sadrzadeh
In Computational Linguistics. 2014.
Details about Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning | BibTeX data for Concrete Models and Empirical Evaluations for the Categorical Compositional Distributional Model of Meaning
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[4]
A Convolutional Neural Network for Modelling Sentences
Nal Kalchbrenner‚ Edward Grefenstette and Phil Blunsom
In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. June, 2014.
Details about A Convolutional Neural Network for Modelling Sentences | BibTeX data for A Convolutional Neural Network for Modelling Sentences | Link to A Convolutional Neural Network for Modelling Sentences
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[5]
A Type−Driven Tensor−Based Semantics for CCG
Jean Maillard‚ Stephen Clark and Edward Grefenstette
In EACL 2014 Type Theory and Natural Language Semantics Workshop. 2014.
Details about A Type−Driven Tensor−Based Semantics for CCG | BibTeX data for A Type−Driven Tensor−Based Semantics for CCG | Link to A Type−Driven Tensor−Based Semantics for CCG
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[6]
Compositional Operators in Distributional Semantics
Dimitri Kartsaklis
In Springer Science Reviews. April, 2014.
Details about Compositional Operators in Distributional Semantics | BibTeX data for Compositional Operators in Distributional Semantics | Download ?(pdf) of Compositional Operators in Distributional Semantics | DOI (10.1007/s40362-014-0017-z)
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[7]
Tree Transduction Tools for cdec
Austin Matthews‚ Paul Baltescu‚ Phil Blunsom‚ Alon Lavie and Chris Dyer
In The Prague Bulletin of Mathematical Linguistics. Vol. 102. No. 1. Pages 27–36. October, 2014.
Details about Tree Transduction Tools for cdec | BibTeX data for Tree Transduction Tools for cdec | Download (pdf) of Tree Transduction Tools for cdec
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[8]
OxLM: A Neural Language Modelling Framework for Machine Translation
Paul Baltescu‚ Phil Blunsom and Hieu Hoang
In The Prague Bulletin of Mathematical Linguistics. Vol. 102. No. 1. Pages 81–92. October, 2014.
Details about OxLM: A Neural Language Modelling Framework for Machine Translation | BibTeX data for OxLM: A Neural Language Modelling Framework for Machine Translation | Download (pdf) of OxLM: A Neural Language Modelling Framework for Machine Translation
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[9]
A Fast and Simple Online Synchronous Context Free Grammar Extractor
Paul Baltescu and Phil Blunsom
In The Prague Bulletin of Mathematical Linguistics. Vol. 102. No. 1. Pages 17–26. October, 2014.
Details about A Fast and Simple Online Synchronous Context Free Grammar Extractor | BibTeX data for A Fast and Simple Online Synchronous Context Free Grammar Extractor | Download (pdf) of A Fast and Simple Online Synchronous Context Free Grammar Extractor
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[10]
Recurrent Convolutional Neural Networks for Discourse Compositionality
Nal Kalchbrenner and Phil Blunsom
In Proceedings of the 2013 Workshop on Continuous Vector Space Models and their Compositionality. 2013.
Details about Recurrent Convolutional Neural Networks for Discourse Compositionality | BibTeX data for Recurrent Convolutional Neural Networks for Discourse Compositionality
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[11]
"Not not bad" is not "bad": A distributional account of negation
Karl Moritz Hermann‚ Edward Grefenstette and Phil Blunsom
In Proceedings of the 2013 Workshop on Continuous Vector Space Models and their Compositionality. August, 2013.
Details about "Not not bad" is not "bad": A distributional account of negation | BibTeX data for "Not not bad" is not "bad": A distributional account of negation | Link to "Not not bad" is not "bad": A distributional account of negation
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[12]
Multi−Step Regression Learning for Compositional Distributional Semantics
Edward Grefenstette‚ Georgiana Dinu‚ Yao−Zhong Zhang‚ Mehrnoosh Sadrzadeh and Marco Baroni
In Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013). 2013.
Details about Multi−Step Regression Learning for Compositional Distributional Semantics | BibTeX data for Multi−Step Regression Learning for Compositional Distributional Semantics | Download (pdf) of Multi−Step Regression Learning for Compositional Distributional Semantics
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[13]
Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors
Edward Grefenstette
In Proceedings of the Second Joint Conference on Lexical and Computational Semantics. 2013.
Details about Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors | BibTeX data for Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors | Download (pdf) of Towards a Formal Distributional Semantics: Simulating Logical Calculi with Tensors
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[14]
Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus
Bob Coecke‚ Edward Grefenstette and Mehrnoosh Sadrzadeh
In Annals of Pure and Applied Logic. 2013.
Details about Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus | BibTeX data for Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus | Link to Lambek vs. Lambek: Functorial Vector Space Semantics and String Diagrams for Lambek Calculus
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[15]
Experimenting with Transitive Verbs in a DisCoCat
Edward Grefenstette and Mehrnoosh Sadrzadeh
In Proceedings of the GEMS 2011 Workshop on GEometrical Models of Natural Language Semantics. 2011.
Details about Experimenting with Transitive Verbs in a DisCoCat | BibTeX data for Experimenting with Transitive Verbs in a DisCoCat | Download (pdf) of Experimenting with Transitive Verbs in a DisCoCat
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[16]
Concrete Sentence Spaces for Compositional Distributional Models of Meaning
Edward Grefenstette‚ Mehrnoosh Sadrzadeh‚ Stephen Clark‚ Bob Coecke and Stephen Pulman
In Proceedings of the 9th International Conference on Computational Semantics (IWCS11). Pages 125–134. 2011.
Details about Concrete Sentence Spaces for Compositional Distributional Models of Meaning | BibTeX data for Concrete Sentence Spaces for Compositional Distributional Models of Meaning | Download (pdf) of Concrete Sentence Spaces for Compositional Distributional Models of Meaning
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[17]
A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations
Mehrnoosh Sadrzadeh and Edward Grefenstette
In Lecture Notes in Computer Science. Vol. 7052. Pages 35–47. 2011.
Details about A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations | BibTeX data for A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations | Link to A Compositional Distributional Semantics‚ Two Concrete Constructions‚ and some Experimental Evaluations
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[18]
Experimental Support for a Categorical Compositional Distributional Model of Meaning
Edward Grefenstette and Mehrnoosh Sadrzadeh
In Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing. 2011.
Details about Experimental Support for a Categorical Compositional Distributional Model of Meaning | BibTeX data for Experimental Support for a Categorical Compositional Distributional Model of Meaning | Download (pdf) of Experimental Support for a Categorical Compositional Distributional Model of Meaning
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[19]
Inducing Tree−Substitution Grammars
Trevor Cohn‚ Phil Blunsom and Sharon Goldwater
In Journal of Machine Learning Research. Pages 3053–3096. 2010.
Details about Inducing Tree−Substitution Grammars | BibTeX data for Inducing Tree−Substitution Grammars
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[20]
Metrics for MT Evaluation: Evaluating Reordering
Alexandra Birch‚ Phil Blunsom and Miles Osborne
In Machine Translation. 2010.
Details about Metrics for MT Evaluation: Evaluating Reordering | BibTeX data for Metrics for MT Evaluation: Evaluating Reordering
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[21]
Monte Carlo techniques for phrase−based translation
Abhishek Arun‚ Chris Dyer‚ Barry Haddow‚ Phil Blunsom‚ Adam Lopez and Philipp Koehn
In Special Issue of Machine Translation Journal. 2010.
Details about Monte Carlo techniques for phrase−based translation | BibTeX data for Monte Carlo techniques for phrase−based translation
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[22]
Inducing Synchronous Grammars with Slice Sampling
Phil Blunsom and Trevor Cohn
In NAACL 2010. June, 2010.
Details about Inducing Synchronous Grammars with Slice Sampling | BibTeX data for Inducing Synchronous Grammars with Slice Sampling | Download (pdf) of Inducing Synchronous Grammars with Slice Sampling
Conference papers
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[1]
Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning
Jianpeng Cheng‚ Dimitri Kartsaklis and Edward Grefenstette
In Learning Semantics workshop‚ NIPS 2014. Montreal‚ Canada. December, 2014.
Details about Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning | BibTeX data for Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning | Download (pdf) of Investigating the Role or Prior Disambiguation in Deep−Learning Compositional Models of Meaning
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[2]
Evaluating Neural Word Representations in Tensor−Based Compositional Settings
Dmitrijs Milajevs‚ Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh and Matthew Purver
In Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP). Doha‚ Qatar. October, 2014. Association for Computational Linguistics.
Details about Evaluating Neural Word Representations in Tensor−Based Compositional Settings | BibTeX data for Evaluating Neural Word Representations in Tensor−Based Compositional Settings | Download ?(pdf) of Evaluating Neural Word Representations in Tensor−Based Compositional Settings | Download (pdf) of Evaluating Neural Word Representations in Tensor−Based Compositional Settings
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[3]
Compositional Morphology for Word Representations and Language Modelling
Jan A. Botha and Phil Blunsom
In Proceedings of the 31st International Conference on Machine Learning (ICML). Beijing‚ China. June, 2014.
*Award for best application paper*
Details about Compositional Morphology for Word Representations and Language Modelling | BibTeX data for Compositional Morphology for Word Representations and Language Modelling | Download (pdf) of Compositional Morphology for Word Representations and Language Modelling
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[4]
Modelling the Lexicon in Unsupervised Part of Speech Induction
Gregory Dubbin and Phil Blunsom
In Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics. Pages 116–125. Gothenburg‚ Sweden. April, 2014. Association for Computational Linguistics.
Details about Modelling the Lexicon in Unsupervised Part of Speech Induction | BibTeX data for Modelling the Lexicon in Unsupervised Part of Speech Induction | Link to Modelling the Lexicon in Unsupervised Part of Speech Induction
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[5]
Linguistic steganography on Twitter: hierarchical language modeling with manual interaction
Alex Wilson‚ Phil Blunsom and Andrew D Ker
In &T/SPIEIS Electronic Imaging. Pages 902803–902803. International Society for Optics and Photonics. 2014.
Details about Linguistic steganography on Twitter: hierarchical language modeling with manual interaction | BibTeX data for Linguistic steganography on Twitter: hierarchical language modeling with manual interaction
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[6]
A Study of Entanglement in a Categorical Framework of Natural Language
Dimitri Kartsaklis and Mehrnoosh Sadrzadeh
In Proceedings of the 11th Workshop on Quantum Physics and Logic (QPL). Kyoto‚ Japan. June, 2014.
Details about A Study of Entanglement in a Categorical Framework of Natural Language | BibTeX data for A Study of Entanglement in a Categorical Framework of Natural Language | Download ?(pdf) of A Study of Entanglement in a Categorical Framework of Natural Language
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[7]
Learning Bilingual Word Representations by Marginalizing Alignments
Tomáš Kočiský‚ Karl Moritz Hermann and Phil Blunsom
In Proceedings of ACL. June, 2014.
Details about Learning Bilingual Word Representations by Marginalizing Alignments | BibTeX data for Learning Bilingual Word Representations by Marginalizing Alignments | Link to Learning Bilingual Word Representations by Marginalizing Alignments
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[8]
Resolving Lexical Ambiguity in Tensor Regression Models of Meaning
Dimitri Kartsaklis‚ Nal Kalchbrenner and Mehrnoosh Sadrzadeh
In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Vol. 2: Short Papers). Pages 212–217. Baltimore‚ USA. June, 2014. Association for Computational Linguistics.
Details about Resolving Lexical Ambiguity in Tensor Regression Models of Meaning | BibTeX data for Resolving Lexical Ambiguity in Tensor Regression Models of Meaning | Download ?(pdf) of Resolving Lexical Ambiguity in Tensor Regression Models of Meaning
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[9]
Semantic Frame Identification with Distributed Word Representations
Karl Moritz Hermann‚ Dipanjan Das‚ Jason Weston and Kuzman Ganchev
In Proceedings of ACL. June, 2014.
Details about Semantic Frame Identification with Distributed Word Representations | BibTeX data for Semantic Frame Identification with Distributed Word Representations | Link to Semantic Frame Identification with Distributed Word Representations
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[10]
Multilingual Models for Compositional Distributional Semantics
Karl Moritz Hermann and Phil Blunsom
In Proceedings of ACL. June, 2014.
Details about Multilingual Models for Compositional Distributional Semantics | BibTeX data for Multilingual Models for Compositional Distributional Semantics | Link to Multilingual Models for Compositional Distributional Semantics
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[11]
Multilingual Distributed Representations without Word Alignment
Karl Moritz Hermann and Phil Blunsom
In Proceedings of ICLR. April, 2014.
Details about Multilingual Distributed Representations without Word Alignment | BibTeX data for Multilingual Distributed Representations without Word Alignment | Link to Multilingual Distributed Representations without Word Alignment
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[12]
Parsing Graphs with Hyperedge Replacement Grammars
David Chiang‚ Jacob Andreas‚ Daniel Bauer‚ Karl Moritz Hermann‚ Bevan Jones and Kevin Knight
In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Pages 924–932. Sofia‚ Bulgaria. August, 2013. Association for Computational Linguistics.
Details about Parsing Graphs with Hyperedge Replacement Grammars | BibTeX data for Parsing Graphs with Hyperedge Replacement Grammars | Link to Parsing Graphs with Hyperedge Replacement Grammars
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[13]
Prior Disambiguation of Word Tensors for Constructing Sentence Vectors
Dimitri Kartsaklis and Mehrnoosh Sadrzadeh
In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP). Seattle‚ USA. October, 2013.
Details about Prior Disambiguation of Word Tensors for Constructing Sentence Vectors | BibTeX data for Prior Disambiguation of Word Tensors for Constructing Sentence Vectors | Download ?(pdf) of Prior Disambiguation of Word Tensors for Constructing Sentence Vectors
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[14]
Adaptor Grammars for Learning Non−Concatenative Morphology
Jan A. Botha and Phil Blunsom
In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Pages 345−356. Seattle‚ Washington‚ USA. October, 2013. Association for Computational Linguistics.
Details about Adaptor Grammars for Learning Non−Concatenative Morphology | BibTeX data for Adaptor Grammars for Learning Non−Concatenative Morphology | Download (pdf) of Adaptor Grammars for Learning Non−Concatenative Morphology
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[15]
Collapsed Variational Bayesian Inference for PCFGs
Pengyu Wang and Phil Blunsom
In Proceedings of the Seventeenth Conference on Computational Natural Language Learning. Pages 173–182. Sofia‚ Bulgaria. August, 2013. Association for Computational Linguistics.
Details about Collapsed Variational Bayesian Inference for PCFGs | BibTeX data for Collapsed Variational Bayesian Inference for PCFGs | Link to Collapsed Variational Bayesian Inference for PCFGs
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[16]
Recurrent Continuous Translation Models
Nal Kalchbrenner and Phil Blunsom
Seattle. October, 2013. Association for Computational Linguistics.
Details about Recurrent Continuous Translation Models | BibTeX data for Recurrent Continuous Translation Models
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[17]
A Systematic Bayesian Treatment of the IBM Alignment Models
Yarin Gal and Phil Blunsom
In Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics. 2013.
Details about A Systematic Bayesian Treatment of the IBM Alignment Models | BibTeX data for A Systematic Bayesian Treatment of the IBM Alignment Models | Link to A Systematic Bayesian Treatment of the IBM Alignment Models
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[18]
Separating Disambiguation from Composition in Distributional Semantics
Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh and Stephen Pulman
In Proceedings of 17th Conference on Natural Language Learning (CoNLL). Pages 114−123. Sofia‚ Bulgaria. August, 2013.
Details about Separating Disambiguation from Composition in Distributional Semantics | BibTeX data for Separating Disambiguation from Composition in Distributional Semantics | Download ?(pdf) of Separating Disambiguation from Composition in Distributional Semantics
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[19]
The Role of Syntax in Vector Space Models of Compositional Semantics
Karl Moritz Hermann and Phil Blunsom
In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Pages 894–904. Sofia‚ Bulgaria. August, 2013. Association for Computational Linguistics.
Details about The Role of Syntax in Vector Space Models of Compositional Semantics | BibTeX data for The Role of Syntax in Vector Space Models of Compositional Semantics | Download (pdf) of The Role of Syntax in Vector Space Models of Compositional Semantics
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[20]
Semantics−Based Machine Translation with Hyperedge Replacement Grammars
Bevan Jones‚ Jacob Andreas‚ Daniel Bauer‚ Karl Moritz Hermann and Kevin Knight
In Proceedings of COLING 2012. Pages 1359–1376. December, 2012.
First four are joint first author in randomized order
Details about Semantics−Based Machine Translation with Hyperedge Replacement Grammars | BibTeX data for Semantics−Based Machine Translation with Hyperedge Replacement Grammars | Link to Semantics−Based Machine Translation with Hyperedge Replacement Grammars
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[21]
The pascal challenge on grammar induction
Douwe Gelling‚ Trevor Cohn‚ Phil Blunsom and Joao Graça
In Proceedings of the NAACL−HLT Workshop on the Induction of Linguistic Structure. Pages 64–80. Association for Computational Linguistics. June, 2012.
Details about The pascal challenge on grammar induction | BibTeX data for The pascal challenge on grammar induction
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[22]
A Bayesian Model for Learning SCFGs with Discontiguous Rules
Abby Levenberg‚ Chris Dyer and Phil Blunsom
In Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning. Pages 223–232. Association for Computational Linguistics. July, 2012.
Details about A Bayesian Model for Learning SCFGs with Discontiguous Rules | BibTeX data for A Bayesian Model for Learning SCFGs with Discontiguous Rules
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[23]
Unsupervised part of speech inference with particle filters
Gregory Dubbin and Phil Blunsom
In Proceedings of the NAACL−HLT Workshop on the Induction of Linguistic Structure. Pages 47–54. Association for Computational Linguistics. 2012.
Details about Unsupervised part of speech inference with particle filters | BibTeX data for Unsupervised part of speech inference with particle filters
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[24]
Unsupervised Bayesian Part of Speech Inference with Particle Gibbs
Gregory Dubbin and Phil Blunsom
In N. Cristianini P. Flach T. De Bie, editor, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD). Bristol‚ UK. September, 2012. Springer.
Details about Unsupervised Bayesian Part of Speech Inference with Particle Gibbs | BibTeX data for Unsupervised Bayesian Part of Speech Inference with Particle Gibbs
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[25]
Hierarchical Bayesian Language Modelling for the Linguistically Informed
Jan A. Botha
In Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop (EACL−SRW). Pages 64–73. 2012.
Best student paper prize
Details about Hierarchical Bayesian Language Modelling for the Linguistically Informed | BibTeX data for Hierarchical Bayesian Language Modelling for the Linguistically Informed | Download (pdf) of Hierarchical Bayesian Language Modelling for the Linguistically Informed
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[26]
Bayesian Language Modelling of German Compounds
Jan A. Botha‚ Chris Dyer and Phil Blunsom
In Proceedings of the 24th International Conference on Computational Linguistics (COLING). Pages 341–356. Mumbai‚ India. December, 2012. The COLING 2012 Organizing Committee.
Details about Bayesian Language Modelling of German Compounds | BibTeX data for Bayesian Language Modelling of German Compounds | Download (pdf) of Bayesian Language Modelling of German Compounds
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[27]
Learning Semantics and Selectional Preference of Adjective−Noun Pairs
Karl Moritz Hermann‚ Chris Dyer‚ Phil Blunsom and Stephen Pulman
In *SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task‚ and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012). Pages 70–74. Montréal‚ Canada. 2012. Association for Computational Linguistics.
Details about Learning Semantics and Selectional Preference of Adjective−Noun Pairs | BibTeX data for Learning Semantics and Selectional Preference of Adjective−Noun Pairs | Download ?(pdf) of Learning Semantics and Selectional Preference of Adjective−Noun Pairs | Link to Learning Semantics and Selectional Preference of Adjective−Noun Pairs
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[28]
An Unsupervised Ranking Model for Noun−Noun Compositionality
Karl Moritz Hermann‚ Phil Blunsom and Stephen Pulman
In *SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task‚ and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012). Pages 132–141. Montréal‚ Canada. 2012. Association for Computational Linguistics.
Details about An Unsupervised Ranking Model for Noun−Noun Compositionality | BibTeX data for An Unsupervised Ranking Model for Noun−Noun Compositionality | Download ?(pdf) of An Unsupervised Ranking Model for Noun−Noun Compositionality | Link to An Unsupervised Ranking Model for Noun−Noun Compositionality
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[29]
A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments
Dimitri Kartsaklis‚ Mehrnoosh Sadrzadeh and Stephen Pulman
In Proceedings of 24th International Conference on Computational Linguistics (COLING): Posters. Pages 549−558. Mumbai‚ India. December, 2012.
Details about A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments | BibTeX data for A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments | Download ?(pdf) of A Unified Sentence Space for Categorical Distributional−Compositional Semantics: Theory and Experiments
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[30]
A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction
Phil Blunsom and Trevor Cohn
In Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies. Pages 865–874. Portland‚ Oregon‚ USA. June, 2011. Association for Computational Linguistics.
Details about A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction | BibTeX data for A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction | Link to A Hierarchical Pitman−Yor Process HMM for Unsupervised Part of Speech Induction
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[31]
Semantic Relatedness from Automatically Generated Semantic Networks
Pia−Ramona Wojtinnek and Stephen Pulman
In Johan Bos and Stephen Pulman, editors, Proceedings of the 9th International Conference on Computational Semantics (IWCS11). Pages 390−394. Oxford‚ UK. 2011. ACL SIGSEM. ACL.
Details about Semantic Relatedness from Automatically Generated Semantic Networks | BibTeX data for Semantic Relatedness from Automatically Generated Semantic Networks | Download (pdf) of Semantic Relatedness from Automatically Generated Semantic Networks
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[32]
BLOCKED INFERENCE IN BAYESIAN TREE SUBSTITUTION GRAMMARS
Trevor Cohn and Phil Blunsom
In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. Uppsala‚ Sweden. 2010.
Details about BLOCKED INFERENCE IN BAYESIAN TREE SUBSTITUTION GRAMMARS | BibTeX data for BLOCKED INFERENCE IN BAYESIAN TREE SUBSTITUTION GRAMMARS
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[33]
cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models
Chris Dyer‚ Adam Lopez‚ Juri Ganitkevitch‚ Johnathan Weese‚ Ferhan Ture‚ Phil Blunsom‚ Hendra Setiawan‚ Vladimir Eidelman and Philip Resnik
In Proceedings of the ACL 2010 System Demonstrations. Pages 7–12. 2010.
Details about cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models | BibTeX data for cdec: A Decoder‚ Alignment‚ and Learning framework for finite−state and context−free translation models
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[34]
Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing
Phil Blunsom and Trevor Cohn
In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing. Pages 1204–1213. Cambridge‚ MA. October, 2010. Association for Computational Linguistics.
Details about Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing | BibTeX data for Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing | Link to Unsupervised Induction of Tree Substitution Grammars for Dependency Parsing
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[35]
Conceptual Knowledge Acquisition Using Automatically Generated Large−Scale Semantic Networks
Pia−Ramona Wojtinnek‚ Brian Harrington‚ Sebastian Rudolph and Stephen Pulman
In Proceedings of the 18th International Conference on Conceptual Structures. 2010.
Details about Conceptual Knowledge Acquisition Using Automatically Generated Large−Scale Semantic Networks | BibTeX data for Conceptual Knowledge Acquisition Using Automatically Generated Large−Scale Semantic Networks
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[36]
A Note on the Implementation of Hierarchical Dirichlet Processes
Phil Blunsom‚ Trevor Cohn‚ Sharon Goldwater and Mark Johnson
In Proceedings of the ACL−IJCNLP 2009 Conference Short Papers. Pages 337–340. Suntec‚ Singapore. August, 2009. Association for Computational Linguistics.
Details about A Note on the Implementation of Hierarchical Dirichlet Processes | BibTeX data for A Note on the Implementation of Hierarchical Dirichlet Processes | Link to A Note on the Implementation of Hierarchical Dirichlet Processes
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[37]
A Bayesian Model of Syntax−Directed Tree to String Grammar Induction
Trevor Cohn and Phil Blunsom
In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing. Pages 352–361. Singapore. August, 2009. Association for Computational Linguistics.
Details about A Bayesian Model of Syntax−Directed Tree to String Grammar Induction | BibTeX data for A Bayesian Model of Syntax−Directed Tree to String Grammar Induction | Link to A Bayesian Model of Syntax−Directed Tree to String Grammar Induction
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[38]
A Gibbs Sampler for Phrasal Synchronous Grammar Induction
Phil Blunsom‚ Trevor Cohn‚ Chris Dyer and Miles Osborne
In Proc. of the Joint conference of the 47th Annual Meeting of the Association for Computational Linguistics and the 4th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL/IJCNLP−09). Pages 782–790. Singapore. August, 2009.
Details about A Gibbs Sampler for Phrasal Synchronous Grammar Induction | BibTeX data for A Gibbs Sampler for Phrasal Synchronous Grammar Induction
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[39]
Inducing compact but accurate tree−substitution grammars
Trevor Cohn‚ Sharon Goldwater and Phil Blunsom
In NAACL '09: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics. Pages 548–556. Morristown‚ NJ‚ USA. 2009. Association for Computational Linguistics.
Details about Inducing compact but accurate tree−substitution grammars | BibTeX data for Inducing compact but accurate tree−substitution grammars
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[40]
Monte Carlo inference and maximization for phrase−based translation
Abhishek Arun‚ Chris Dyer‚ Barry Haddow‚ Phil Blunsom‚ Adam Lopez and Philipp Koehn
In CoNLL '09: Proceedings of the Thirteenth Conference on Computational Natural Language Learning. Pages 102–110. Morristown‚ NJ‚ USA. 2009. Association for Computational Linguistics.
Details about Monte Carlo inference and maximization for phrase−based translation | BibTeX data for Monte Carlo inference and maximization for phrase−based translation
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[41]
A Discriminative Latent Variable Model for Statistical Machine Translation
Phil Blunsom‚ Trevor Cohn and Miles Osborne
In Proc. of the 46th Annual Conference of the Association for Computational Linguistics: Human Language Technologies (ACL−08:HLT). Pages 200–208. Columbus‚ Ohio. June, 2008.
Details about A Discriminative Latent Variable Model for Statistical Machine Translation | BibTeX data for A Discriminative Latent Variable Model for Statistical Machine Translation | Link to A Discriminative Latent Variable Model for Statistical Machine Translation
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[42]
Probabilistic Inference for Machine Translation
Phil Blunsom and Miles Osborne
In Proceedings of the 2008 Conference on Empirical Methods in Natural Language Processing. Pages 215–223. Honolulu‚ Hawaii. October, 2008.
Details about Probabilistic Inference for Machine Translation | BibTeX data for Probabilistic Inference for Machine Translation
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[43]
Formal and Computational Semantics: a Case Study
Stephen Pulman
In Jeroen Geertzen‚ Elias Thijsse‚ Harry Bunt and Amanda Schiffrin, editors, Proceedings of the Seventh International Workshop on Computational Semantics: IWCS−7‚ Tilburg‚ The Netherlands‚ 2007. Pages 181–196. 2007.
Details about Formal and Computational Semantics: a Case Study | BibTeX data for Formal and Computational Semantics: a Case Study | Download ?(pdf) of Formal and Computational Semantics: a Case Study
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[44]
Discriminative Word Alignment with Conditional Random Fields
Phil Blunsom and Trevor Cohn
In Proc. of the 44th Annual Meeting of the ACL and 21st International Conference on Computational Linguistics (COLING/ACL−2006). Pages 65–72. Sydney‚ Australia. July, 2006.
Details about Discriminative Word Alignment with Conditional Random Fields | BibTeX data for Discriminative Word Alignment with Conditional Random Fields | Link to Discriminative Word Alignment with Conditional Random Fields
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[45]
Multilingual Deep Lexical Acquisition for HPSGs via Supertagging
Phil Blunsom and Timothy Baldwin
In Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing. Pages 164–171. Sydney‚ Australia. July, 2006.
Details about Multilingual Deep Lexical Acquisition for HPSGs via Supertagging | BibTeX data for Multilingual Deep Lexical Acquisition for HPSGs via Supertagging
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[46]
Question classification with log−linear models
Phil Blunsom‚ Krystle Kocik and James R. Curran
In SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval. Pages 615–616. New York‚ NY‚ USA. 2006. ACM.
Details about Question classification with log−linear models | BibTeX data for Question classification with log−linear models | DOI (http://doi.acm.org/10.1145/1148170.1148282)
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[47]
Semantic Role Labelling with Tree Conditional Random Fields
Trevor Cohn and Philip Blunsom
In Proc. of the 9th Conference on Natural Language Learning (CoNLL−2005). Pages 169–172. Ann Arbor‚ Michigan. June, 2005.
Details about Semantic Role Labelling with Tree Conditional Random Fields | BibTeX data for Semantic Role Labelling with Tree Conditional Random Fields | Link to Semantic Role Labelling with Tree Conditional Random Fields
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[48]
Maximum Entropy Markov models for semantic role labelling
Phil Blunsom
In Proc. of the Australasian Language Technology Workshop 2004. Pages 109–116. Sydney‚ Australia. 2005.
Details about Maximum Entropy Markov models for semantic role labelling | BibTeX data for Maximum Entropy Markov models for semantic role labelling
Technical reports
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[1]
Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network
Misha Denil‚ Alban Demiraj‚ Nal Kalchbrenner‚ Phil Blunsom and Nando de Freitas
No. arXiv:1406.3830. University of Oxford. 2014.
Details about Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network | BibTeX data for Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network | Link to Modelling‚ Visualising and Summarising Documents with a Single Convolutional Neural Network
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[2]
A Primer on Graph Processing with Bolinas
Jacob Andreas‚ Daniel Bauer‚ David Chiang‚ Karl Moritz Hermann‚ Bevan Jones and Kevin Knight
August, 2013.
Details about A Primer on Graph Processing with Bolinas | BibTeX data for A Primer on Graph Processing with Bolinas | Download (pdf) of A Primer on Graph Processing with Bolinas
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[3]
Shallow Processing and Automatic Summarising: a First Study
Stephen Pulman‚ Philip Gladwin and Karen Spärck Jones
Computer Laboratory‚ University of Cambridge. 1991.
Details about Shallow Processing and Automatic Summarising: a First Study | BibTeX data for Shallow Processing and Automatic Summarising: a First Study
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[4]
The SRI Core Language Engine project: the grammar
Stephen Pulman and G. D. Ritchie
Centre for Cognitive Science‚ Edinburgh‚ and Institute for Language‚ Logic and Information‚ Amsterdam. 1987.
in E. Klein and J. van Benthem (eds.) Categories‚ Polymorphism and Unification
Details about The SRI Core Language Engine project: the grammar | BibTeX data for The SRI Core Language Engine project: the grammar
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[5]
Indexed Grammars and Intersecting Dependencies
Stephen Pulman and G. D. Ritchie
No. 23. University of East Anglia. 1985.
Details about Indexed Grammars and Intersecting Dependencies | BibTeX data for Indexed Grammars and Intersecting Dependencies | Download ?(pdf) of Indexed Grammars and Intersecting Dependencies
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[6]
Grammatical Description and Sentence Processing
Stephen Pulman
University of East Anglia. 1979.
Details about Grammatical Description and Sentence Processing | BibTeX data for Grammatical Description and Sentence Processing
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[7]
Shape Classifiers and Natural Categories
Stephen Pulman
Essex University. 1978.
Details about Shape Classifiers and Natural Categories | BibTeX data for Shape Classifiers and Natural Categories
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[8]
Can‚ Could‚ and Possible For
Stephen Pulman
Essex University. 1976.
Details about Can‚ Could‚ and Possible For | BibTeX data for Can‚ Could‚ and Possible For
Theses
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[1]
Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics
Edward Grefenstette
PhD Thesis June, 2013.
Details about Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics | BibTeX data for Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics | Link to Category−Theoretic Quantitative Compositional Distributional Models of Natural Language Semantics
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[2]
Analysing Document Similarity Measures
Edward Grefenstette
Master's Thesis University of Oxford. September, 2009.
Details about Analysing Document Similarity Measures | BibTeX data for Analysing Document Similarity Measures | Download (pdf) of Analysing Document Similarity Measures