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SCLeM 2017 : 1st Workshop on Subword and Character LEvel Models in NLP (SCLeM)

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Link: https://sites.google.com/view/sclem2017/
 
When Sep 7, 2017 - Sep 7, 2017
Where Copenhagen, Denmark
Submission Deadline Jun 2, 2017
Notification Due Jun 30, 2017
Final Version Due Jul 21, 2017
Categories    NLP   IR   representation learning   deep learning
 

Call For Papers

CALL FOR PAPERS

First Workshop on Subword and Character LEvel Models in NLP (SCLeM)
To be held at EMNLP 2017 in Copenhagen on September 7, 2017
https://sites.google.com/view/sclem2017


DATES

Submission deadline: June 2, 2017
Notification: June 30, 2017
Camera ready: July 14, 2017


INVITED SPEAKERS

Kyunghyun Cho, NYU
Karen Livescu, TTIC
Tomas Mikolov, Facebook
Noah Smith, Univ of Washington


INVITED TUTORIAL TALK

Neural weighted finite-state machines,
Ryan Cotterell, JHU


OVERVIEW

Traditional NLP starts with a hand-engineered layer of
representation, the level of tokens or words. A
tokenization component first breaks up the text into units
using manually designed rules. Tokens are then processed by
components such as word segmentation, morphological analysis
and multiword recognition. The heterogeneity of these
components makes it hard to create integrated models of both
structure within tokens (e.g., morphology) and structure
across multiple tokens (e.g., multi-word expressions). This
approach can perform poorly (i) for morphologically rich
languages, (ii) for noisy text, (iii) for languages in which
the recognition of words is difficult and (iv) for
adaptation to new domains; and (v) it can impede the
optimization of preprocessing in end-to-end learning.

The workshop provides a forum for discussing recent advances
as well as future directions on sub-word and character-level
natural language processing and representation learning that
address these problems.


PROGRAM

- invited talks
- invited tutorial talk
- panel discussions
- contributed talks and posters


TOPICS OF INTEREST

- tokenization-free models
- character-level machine translation
- character-ngram information retrieval
- transfer learning for character-level models
- models of within-token and cross-token structure
- NL generation (of words not seen in training etc)
- out of vocabulary words
- morphology & segmentation
- relationship b/w morphology & character-level models
- stemming and lemmatization
- inflection generation
- orthographic productivity
- form-meaning representations
- true end-to-end learning
- spelling correction
- efficient and scalable character-level models


SUBMISSIONS OF LONG AND SHORT PAPERS AND EXTENDED ABSTRACTS

Please submit your paper using START:
https://www.softconf.com/emnlp2017/sclem/. Submissions must
be in PDF format, anonymized for review, written in English
and follow the EMNLP 2017 formatting requirements (available
at http://emnlp2017.net/). We strongly advise you use the
LaTeX template files provided by EMNLP 2017.

Long paper submissions consist of up to eight pages of
content. Short paper submissions consist of up to four
pages of content. There is no limit on the number of pages
for references. There is no extra space for appendices.
Accepted papers will be given one additional page for
content.

Authors can also submit extended abstracts of up to eight
pages of content. Add "(EXTENDED ABSTRACT)" to the title of
an extended abstract submission. Extended abstracts will be
presented as talks or posters if selected by the program
committee, but not included in the proceedings. Thus, your
work will retain the status of being unpublished and later
submission at another venue (e.g., a journal) is not
precluded.


ORGANIZING COMMITTEE

Manaal Faruqui, Google
Hinrich Schuetze, LMU Munich
Isabel Trancoso, INESC-ID/IST
Yadollah Yaghoobzadeh, LMU Munich

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