REPL4NLP 2016 : 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
- 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
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. Accepted papers will be presented as posters. Selected papers may also be presented orally at the discretion of the committee.
All submissions must be in PDF format and must follow 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.
Submissions must be made through the Softconf website set up for this workshop: https://www.softconf.com/acl2016/repl4nlp2016/. Style files and other information about paper formatting requirements will be made available on the conference website, http://acl2016.org.
Accepted papers will appear in the workshop proceedings, where no distinction will be made on the basis of length or mode of presentation.
- Phil Blunsom, University of Oxford and Google DeepMind
- Kyunghyun Cho, NYU
- Shay Cohen, University of Edinburgh
- Edward Grefenstette, Google DeepMind
- Karl Moritz Hermann, Google DeepMind
- Laura Rimell, University of Cambridge
- Jason Weston, Facebook
- Scott Wen-tau Yih, Microsoft Research