Workshop on continuous Vector Space Models and their Compositionality (3rd edition)
Co-located with ACL 2015, Beijing, China
July 31, 2015
Submission deadline: May 14, 2015
https://sites.google.com/site/cvscworkshop2015
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INVITED SPEAKERS
The workshop will showcase presentations from 5 keynote speakers.         ? Kyunghyun Cho
(Université de Montréal)
? Stephen Clark university of Cambridge)
? Yoav Goldberg (Bar Ilan university)
? Ray Mooney university of Texas at Austin)
? Jason Weston (Facebook AI Research)


AIMS AND SCOPE

In recent years, there has been a growing interest in algorithms that learn and use
continuous representations for words, phrases, or documents in many natural language
processing applications. Among many others, influential proposals that illustrate this
trend include latent Dirichlet allocation, neural network based language models and
spectral methods. These approaches are motivated by improving the generalization power of
the discrete standard models, by dealing with the data sparsity issue and by efficiently
handling a wide context.  Despite the success of single word vector space models, they
are limited since they do not capture compositionality. This prevents them from gaining a
deeper understanding of the semantics of longer phrases, sentences and documents.
Regarding this issue, some  pertinent questions arise: should word/phrase/sentence
representations be of the same sort? Could different linguistic levels require different
modelling approaches ? Is compositionality determined by syntax, and if so, how do we
learn/define it? Should word representations be fixed and obtained distributionally, or
should the encoding be variable?  Should word representations be task-specific, or should
they be general?

In this workshop, we invite submissions of papers on continuous vector space models for
natural language processing. Topics of interest include, but are not limited to:
* Neural networks
* Spectral methods
* Distributional semantic models
* Language modeling for automatic speech recognition, statistical machine translation,
and information retrieval
* Automatic annotation of texts
* Phrase and sentence-level distributional representations
* The role of syntax in compositional models
* Formal and distributional semantic models
* Language modeling for logical and natural reasoning
* Integration of distributional representations with other models
* Multi-modal learning for distributional representations
* Knowledge base embedding


SUBMISSION INFORMATION

Authors should submit a full paper of up to 8 pages in electronic, PDF format, with up to
2 additional pages for references. The reported research should be substantially
original. The papers will be presented orally or as posters.
All submissions must be in PDF format and must follow the ACL 2015 formatting
requirements (see the ACL 2015 Call For Papers http://acl2015.org/call_for_papers.html).
Reviewing will be double-blind, and thus no author information should be included in the
papers; self-reference should be avoided as well. Submissions must be made through the
Softconf website set up for this workshop:
https://www.softconf.com/acl2015/CVSC/

Accepted papers will appear in the workshop proceedings, where no distinction will be
made between papers presented orally or as posters.


IMPORTANT DATES

14 May 2015        : Submission deadline
4 June 2015        : Notification of acceptance
21 June 2015          : Camera-ready deadline
31 July 2015           : Workshop


ORGANIZERS

Alexandre Allauzen (LIMSI-CNRS/Université Paris-Sud, France)
Edward Grefenstette (Google DeepMind, UK)
Karl Moritz Hermann (Google DeepMind, UK)
Hugo Larochelle (Université de Sherbrooke, Canada)
Scott Wen-tau Yih microsoft Research, USA)


program COMMITTEE

Marco Baroni, university of Trento
Yoshua Bengio, Université de Montreal
Phil Blunsom, university of Oxford
Antoine Bordes, Facebook
Leon Bottou, Facebook
Stephen Clark, university of Cambridge
Shay Cohen, university of Edinburgh
Georgiana Dinu, University of Trento
Kevin Duh, Nara Institute of Science and Technology
Yoav Goldberg, Bar Ilan University
Andriy Mnih, Google DeepMind
Mehrnoosh Sadrzadeh, University of London
Mark Steedman, University of Edinburgh
Peter Turney, NRC
Jason Weston, Facebook
Guillaume Wisniewski, LIMSI-CNRS