Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Stephen Clark

Stephen Clark

lambeq: An Efficient High-Level Python Library for Quantum NLP


Oct 08, 2021
Dimitri Kartsaklis, Ian Fan, Richie Yeung, Anna Pearson, Robin Lorenz, Alexis Toumi, Giovanni de Felice, Konstantinos Meichanetzidis, Stephen Clark, Bob Coecke

Figure 1 for lambeq: An Efficient High-Level Python Library for Quantum NLP
Figure 2 for lambeq: An Efficient High-Level Python Library for Quantum NLP
Figure 3 for lambeq: An Efficient High-Level Python Library for Quantum NLP
Figure 4 for lambeq: An Efficient High-Level Python Library for Quantum NLP

  Access Paper or Ask Questions

Something Old, Something New: Grammar-based CCG Parsing with Transformer Models


Sep 28, 2021
Stephen Clark

Figure 1 for Something Old, Something New: Grammar-based CCG Parsing with Transformer Models
Figure 2 for Something Old, Something New: Grammar-based CCG Parsing with Transformer Models
Figure 3 for Something Old, Something New: Grammar-based CCG Parsing with Transformer Models
Figure 4 for Something Old, Something New: Grammar-based CCG Parsing with Transformer Models
* o Added to the description of the formal properties of CCG o Added more description of how maxent and neural taggers differ o Added a ref to some very recent CCG parsing work o Fixed a bug in one of the figures o Added a note and ref to the conclusions o Added to the acknowledgements 
  Access Paper or Ask Questions

Imitating Interactive Intelligence


Jan 21, 2021
Josh Abramson, Arun Ahuja, Iain Barr, Arthur Brussee, Federico Carnevale, Mary Cassin, Rachita Chhaparia, Stephen Clark, Bogdan Damoc, Andrew Dudzik, Petko Georgiev, Aurelia Guy, Tim Harley, Felix Hill, Alden Hung, Zachary Kenton, Jessica Landon, Timothy Lillicrap, Kory Mathewson, Soňa Mokrá, Alistair Muldal, Adam Santoro, Nikolay Savinov, Vikrant Varma, Greg Wayne, Duncan Williams, Nathaniel Wong, Chen Yan, Rui Zhu

Figure 1 for Imitating Interactive Intelligence
Figure 2 for Imitating Interactive Intelligence
Figure 3 for Imitating Interactive Intelligence
Figure 4 for Imitating Interactive Intelligence

  Access Paper or Ask Questions

Formalising Concepts as Grounded Abstractions


Jan 13, 2021
Stephen Clark, Alexander Lerchner, Tamara von Glehn, Olivier Tieleman, Richard Tanburn, Misha Dashevskiy, Matko Bosnjak

Figure 1 for Formalising Concepts as Grounded Abstractions
Figure 2 for Formalising Concepts as Grounded Abstractions
Figure 3 for Formalising Concepts as Grounded Abstractions
Figure 4 for Formalising Concepts as Grounded Abstractions

  Access Paper or Ask Questions

Grounded Language Learning Fast and Slow


Sep 15, 2020
Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark

Figure 1 for Grounded Language Learning Fast and Slow
Figure 2 for Grounded Language Learning Fast and Slow
Figure 3 for Grounded Language Learning Fast and Slow
Figure 4 for Grounded Language Learning Fast and Slow

  Access Paper or Ask Questions

Probing Emergent Semantics in Predictive Agents via Question Answering


Jun 01, 2020
Abhishek Das, Federico Carnevale, Hamza Merzic, Laura Rimell, Rosalia Schneider, Josh Abramson, Alden Hung, Arun Ahuja, Stephen Clark, Gregory Wayne, Felix Hill

Figure 1 for Probing Emergent Semantics in Predictive Agents via Question Answering
Figure 2 for Probing Emergent Semantics in Predictive Agents via Question Answering
Figure 3 for Probing Emergent Semantics in Predictive Agents via Question Answering
Figure 4 for Probing Emergent Semantics in Predictive Agents via Question Answering
* ICML 2020 
  Access Paper or Ask Questions

Learning to Segment Actions from Observation and Narration


May 07, 2020
Daniel Fried, Jean-Baptiste Alayrac, Phil Blunsom, Chris Dyer, Stephen Clark, Aida Nematzadeh

Figure 1 for Learning to Segment Actions from Observation and Narration
Figure 2 for Learning to Segment Actions from Observation and Narration
Figure 3 for Learning to Segment Actions from Observation and Narration
Figure 4 for Learning to Segment Actions from Observation and Narration
* ACL 2020 
  Access Paper or Ask Questions

Emergent Systematic Generalization in a Situated Agent


Oct 28, 2019
Felix Hill, Andrew Lampinen, Rosalia Schneider, Stephen Clark, Matthew Botvinick, James L. McClelland, Adam Santoro

Figure 1 for Emergent Systematic Generalization in a Situated Agent
Figure 2 for Emergent Systematic Generalization in a Situated Agent
Figure 3 for Emergent Systematic Generalization in a Situated Agent
Figure 4 for Emergent Systematic Generalization in a Situated Agent

  Access Paper or Ask Questions

Neural Generative Rhetorical Structure Parsing


Sep 24, 2019
Amandla Mabona, Laura Rimell, Stephen Clark, Andreas Vlachos

Figure 1 for Neural Generative Rhetorical Structure Parsing
Figure 2 for Neural Generative Rhetorical Structure Parsing
Figure 3 for Neural Generative Rhetorical Structure Parsing
Figure 4 for Neural Generative Rhetorical Structure Parsing
* EMNLP 2019 
  Access Paper or Ask Questions

Scalable Syntax-Aware Language Models Using Knowledge Distillation


Jun 14, 2019
Adhiguna Kuncoro, Chris Dyer, Laura Rimell, Stephen Clark, Phil Blunsom

Figure 1 for Scalable Syntax-Aware Language Models Using Knowledge Distillation
Figure 2 for Scalable Syntax-Aware Language Models Using Knowledge Distillation
Figure 3 for Scalable Syntax-Aware Language Models Using Knowledge Distillation
Figure 4 for Scalable Syntax-Aware Language Models Using Knowledge Distillation
* ACL 2019 
  Access Paper or Ask Questions

Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing


Jun 03, 2018
Jean Maillard, Stephen Clark

Figure 1 for Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing
Figure 2 for Latent Tree Learning with Differentiable Parsers: Shift-Reduce Parsing and Chart Parsing
* ACL 2018 workshop on Relevance of Linguistic Structure in Neural Architectures for NLP 
  Access Paper or Ask Questions

Generating syntactically varied realisations from AMR graphs


Apr 20, 2018
Kris Cao, Stephen Clark

Figure 1 for Generating syntactically varied realisations from AMR graphs
Figure 2 for Generating syntactically varied realisations from AMR graphs
Figure 3 for Generating syntactically varied realisations from AMR graphs
Figure 4 for Generating syntactically varied realisations from AMR graphs

  Access Paper or Ask Questions

Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input


Apr 11, 2018
Angeliki Lazaridou, Karl Moritz Hermann, Karl Tuyls, Stephen Clark

Figure 1 for Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
Figure 2 for Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
Figure 3 for Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
Figure 4 for Emergence of Linguistic Communication from Referential Games with Symbolic and Pixel Input
* To appear at ICLR 2018 
  Access Paper or Ask Questions

Emergent Communication through Negotiation


Apr 11, 2018
Kris Cao, Angeliki Lazaridou, Marc Lanctot, Joel Z Leibo, Karl Tuyls, Stephen Clark

Figure 1 for Emergent Communication through Negotiation
Figure 2 for Emergent Communication through Negotiation
Figure 3 for Emergent Communication through Negotiation
Figure 4 for Emergent Communication through Negotiation
* Published as a conference paper at ICLR 2018 
  Access Paper or Ask Questions

Understanding Grounded Language Learning Agents


Oct 26, 2017
Felix Hill, Karl Moritz Hermann, Phil Blunsom, Stephen Clark

Figure 1 for Understanding Grounded Language Learning Agents
Figure 2 for Understanding Grounded Language Learning Agents
Figure 3 for Understanding Grounded Language Learning Agents
Figure 4 for Understanding Grounded Language Learning Agents

  Access Paper or Ask Questions

Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs


May 25, 2017
Jean Maillard, Stephen Clark, Dani Yogatama

Figure 1 for Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs
Figure 2 for Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs
Figure 3 for Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs
Figure 4 for Jointly Learning Sentence Embeddings and Syntax with Unsupervised Tree-LSTMs

  Access Paper or Ask Questions

Latent Variable Dialogue Models and their Diversity


Feb 20, 2017
Kris Cao, Stephen Clark

Figure 1 for Latent Variable Dialogue Models and their Diversity
Figure 2 for Latent Variable Dialogue Models and their Diversity
Figure 3 for Latent Variable Dialogue Models and their Diversity
Figure 4 for Latent Variable Dialogue Models and their Diversity
* Accepted at EACL 2017 
  Access Paper or Ask Questions

Virtual Embodiment: A Scalable Long-Term Strategy for Artificial Intelligence Research


Oct 24, 2016
Douwe Kiela, Luana Bulat, Anita L. Vero, Stephen Clark


  Access Paper or Ask Questions

Using Sentence Plausibility to Learn the Semantics of Transitive Verbs


Dec 12, 2014
Tamara Polajnar, Laura Rimell, Stephen Clark

Figure 1 for Using Sentence Plausibility to Learn the Semantics of Transitive Verbs
* Full updated paper for NIPS learning semantics workshop, with some minor errata fixed 
  Access Paper or Ask Questions

The Frobenius anatomy of word meanings II: possessive relative pronouns


Jun 18, 2014
Mehrnoosh Sadrzadeh, Stephen Clark, Bob Coecke

* 40 pages, Journal of Logic and Computation, Essays dedicated to Roy Dyckhoff on the occasion of his retirement, S. Graham-Lengrand and D. Galmiche (eds.), 2014 
  Access Paper or Ask Questions

The Frobenius anatomy of word meanings I: subject and object relative pronouns


Apr 21, 2014
Mehrnoosh Sadrzadeh, Stephen Clark, Bob Coecke

* Journal of Logic and Computation, Special Issue: The Incomputable, an Isaac Newton Institute Workshop, 23(6), pp.1293-1317, 2013 
 * 31 pages 
  Access Paper or Ask Questions

Learning Type-Driven Tensor-Based Meaning Representations


Feb 18, 2014
Tamara Polajnar, Luana Fagarasan, Stephen Clark

Figure 1 for Learning Type-Driven Tensor-Based Meaning Representations
Figure 2 for Learning Type-Driven Tensor-Based Meaning Representations
Figure 3 for Learning Type-Driven Tensor-Based Meaning Representations
Figure 4 for Learning Type-Driven Tensor-Based Meaning Representations
* Submitted as part of the open review process for ICLR'14. The paper contains 10 pages, 3 figures, 4 tables 
  Access Paper or Ask Questions

A quantum teleportation inspired algorithm produces sentence meaning from word meaning and grammatical structure


Oct 11, 2013
Stephen Clark, Bob Coecke, Edward Grefenstette, Stephen Pulman, Mehrnoosh Sadrzadeh

* 10 pages, many pictures 
  Access Paper or Ask Questions

Concrete Sentence Spaces for Compositional Distributional Models of Meaning


Dec 31, 2010
Edward Grefenstette, Mehrnoosh Sadrzadeh, Stephen Clark, Bob Coecke, Stephen Pulman

* Proceedings of the 9th International Conference on Computational Semantics (2011) 
 * 10 pages, presented at the International Conference on Computational Semantics 2011 (IWCS'11), to be published in proceedings 
  Access Paper or Ask Questions

Mathematical Foundations for a Compositional Distributional Model of Meaning


Mar 23, 2010
Bob Coecke, Mehrnoosh Sadrzadeh, Stephen Clark

* Lambek Festschirft, special issue of Linguistic Analysis, 2010. 
 * to appear 
  Access Paper or Ask Questions