Connectionists: 1st Workshop on Representation Learning for NLP: Call for Papers

[Kyunghyun Cho]

1st Workshop on Representation Learning for NLP: Call for Papers

The 1st Workshop on Representation Learning for NLP (
https://sites.google.com/site/repl4nlp2016/) invites papers of a
theoretical or experimental nature on all relevant topics. Relevant topics
for the workshop include, but are not limited to, the following areas (in
alphabetical order):


   -

   Analysis of language using eigenvalue, singular value and tensor
   decompositions
   -

   Distributional compositional semantics
   -

   Integration of distributional representations with other models
   -

   Knowledge base embedding
   -

   Language modeling for automatic speech recognition, statistical machine
   translation, and information retrieval
   -

   Language modeling for logical and natural reasoning
   -

   Latent-variable and representation learning for language
   -

   Multi-modal learning for distributional representations
   -

   Neural networks and deep learning in NLP
   -

   The role of syntax in compositional models
   -

   Spectral learning and the method of moments in NLP
   -

   Language embeddings and their applications


Important Dates

   -

   Deadline for submission: 8 May 2016
   -

   Notification of acceptance: 5 June 2016
   -

   Deadline for camera-ready version: 22 June 2016
   -

   Early registration deadline (ACL'16): To be announced.
   -

   Workshop: 11 August 2016

Submissions

We solicit three categories of papers: regular workshop papers, extended
abstracts and cross-submissions. Only regular workshop papers will be
included in the proceedings as archival publications. All submissions
should be in PDF format and made through the Softconf website set up for
this workshop: https://www.softconf.com/acl2016/repl4nlp2016/.

Regular Workshop Paper

Authors should submit a long paper of up to 8 pages, with up to 2
additional pages for references, following the ACL 2016 formatting
requirements (see the ACL 2016 Call For Papers for reference:
http://acl2016.org/index.php?article_id=9). The reported research should be
substantially original. Accepted papers will be presented as posters.
Selected papers may also be presented orally at the discretion of the
committee. Reviewing will be double-blind, and thus no author information
should be included in the papers; self-reference that identifies the
authors should be avoided or anonymized. Accepted papers will appear in the
workshop proceedings, where no distinction will be made on the basis of
mode of presentation.

Extended Abstracts

Preliminary but interesting ideas or results that have not been published
before may be submitted as extended abstracts, with length of 2 to 4 pages
plus references, following the ACL 2016 formatting requirements (see the
ACL 2016 Call For Papers for reference:
http://acl2016.org/index.php?article_id=9). Reviewing will be double-blind,
and thus no author information should be included in the papers;
self-reference that identifies the authors should be avoided or anonymized.
Accepted abstracts will be presented as posters, but will not be included
in the workshop proceedings.

Cross Submissions

In addition to unpublished work, we also solicit papers on related topics
that have appeared in a non-NLP venue (e.g., workshop or conference papers
at NIPS or ICML). These papers will be presented as posters, but do not
count as RepL4NLP workshop papers and will not be included in the
proceedings.  Interested authors need to submit their papers in PDF format
through the same Softconf website at
https://www.softconf.com/acl2016/repl4nlp2016/ with a note on the original
venue. Papers in this category do not need to follow the ACL format and the
selection is solely determined by the organizing committee.

Best Paper Prizes

Thanks to generous support from our sponsors: Google DeepMind, Microsoft
Research, and Facebook, we will be awarding a prize of $300 to the three
best regular workshop paper submissions as selected by our program
committee, to be presented at the workshop.
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