CONLL 2019 : The SIGNLL Conference on Computational Natural Language Learning
Call For Papers
Call for Papers - CoNLL 2019
SIGNLL, the Association for Computational Linguistics’ Special Interest Group on Natural Language Learning, invites you to submit your papers to the Conference on Computational Natural Language Learning (CoNLL 2019), which will be held on November 3-4, 2019, in Hong Kong.
Submit your paper!
We invite the submission of papers on all aspects of computational approaches to natural language learning, including, but not limited to:
Language Models, Segmentation
Multimodal and Grounded Language Processing
Computational Models of Language evolution and Change
Computational Simulation and Analysis of Psycholinguistic Findings
Computational Learning Theory and Analysis of Language Learning
Computational Models of First, Second and Bilingual Language Acquisition
Data Resources, Techniques and Tools for Computational Modeling of Human Language Acquisition and Processing
Investigations of Learning Methods (e.g. machine learning, biologically-inspired, active learning, hybrid models) from a Cognitive Perspective
Models of induction and Analogy in Linguistics
Morphological Analysis, POS Tagging and Sequence Labeling
Syntactic and Semantic Parsing
Lexical and Compositional Semantics
Discourse and Coreference
Dialogue and Interactive Systems
Narrative Understanding and Commonsense Reasoning
Spoken Language Processing
Sentiment Analysis and Opinion Mining
Information Retrieval, Question Answering
Natural Language Generation
Other NLP Applications
Multilinguality and Cross-linguality
Machine Learning for NLP
Linguistic Theories and Resources
Paper submission: May 31, 2019
Notification of acceptance: July 27, 2019
Camera-ready due: August 24, 2019
Conference: November 3-4, 2019 (before EMNLP 2019)
Note: All deadlines are calculated at 11:59pm UTC-12h.
- Paper submissions
CoNLL 2019 long paper submissions must describe substantial, original, completed and unpublished work. Wherever appropriate, concrete evaluation and analysis should be included. Each submission will be reviewed by at least three program committee members. Each long paper submission consists of a paper of up to eight (8) pages of content, plus unlimited pages for references. Final versions of long papers will be given one additional page (up to nine pages with unlimited pages for references) so that reviewers comments can be taken into account.
- IMPORTANT: New submission guidelines
CoNLL 2019 adopts ACL’s policies for submission, review, and citation. Submissions that violate any of these policies will be rejected without review. Most importantly, the policies refer to the anonymity period, which starts on April 30, 2019 for CoNLL 2019.
You may not make a non-anonymized version of your paper available online to the general community (for example, via a preprint server) during the anonymity period.
You may not update the non-anonymized version during the anonymity period, and we ask you not to advertise it on social media or take other actions that would further compromise double-blind reviewing during the anonymity period.
The details are described in the ACL 2019 Author Guidelines, which we follow.
- Optional Supplementary Materials: Appendices, Software and Data
Each CoNLL 2019 submission can be accompanied by a single PDF appendix, one .tgz or .zip archive containing software, and one .tgz or .zip archive containing data. CoNLL 2019 encourages the submission of these supplementary materials to improve the reproducibility of results, and to enable authors to provide additional information that does not fit in the paper. For example, preprocessing decisions, model parameters, feature templates, lengthy proofs or derivations, pseudocode, sample system inputs/outputs, and other details that are necessary for the exact replication of the work described in the paper can be put into the appendix. However, the paper submissions need to remain fully self-contained, as these supplementary materials are completely optional, and reviewers are not even asked to review or download them. If the pseudo-code or derivations or model specifications are an important part of the contribution, or if they are important for the reviewers to assess the technical correctness of the work, they should be a part of the main paper, and not appear in the appendix. Supplementary materials need to be fully anonymized to preserve the double-blind reviewing policy.
- Formatting Requirements
Papers must follow the CoNLL 2019 two-column format, using our LaTeX style files or Word template. Please do not modify these style files, or use templates designed for other conferences. Submissions that do not conform to the required styles, including paper size, margin width, and font size restrictions, will be rejected without review.
- Double-Blind Review Instructions
As the reviewing will be blind, submissions and supplementary materials must not include the authors’ names and affiliations. Furthermore, self-references that reveal the author’s identity, e.g., “We previously showed (Smith, 1991) …”, should be avoided. Instead, use citations such as “Smith (1991) previously showed …”. Acknowledgments of funding or assistance must also be omitted. Submissions should not contain pointers to supplemental information on the web; any such material should be submitted as supplementary materials (see above). Submissions that do not conform to these requirements will be rejected without review. Separate author identification information is required as part of the online submission process.
- Multiple Submission Policy
We will not accept for submission papers that have been or will be submitted to other meetings or publications.
We will not accept for publication or presentation papers that overlap significantly in content or results with papers that will be (or have been) published elsewhere. Authors submitting more than one paper to CoNLL 2019 must ensure that the submissions do not overlap significantly ()25%) with each other in content or results.
We accept submissions online via Softconf. The submission deadline is May 31, 2019.
All accepted papers must be presented at the conference in order to appear in the proceedings. At least one author of each accepted paper must register for CoNLL 2019. Accepted papers will be presented orally or as a poster (at the discretion of the program chairs based on the nature rather than the quality of the work). All papers will be published in the conference proceedings. There will be no distinction in the proceedings between papers presented orally or as posters.
The conference will take place immediately before EMNLP 2019 (November 3 – November 7, 2019). CoNLL 2019 website will continue to be updated with information.
Best Paper Award
As in recent CoNLL conferences, a Best Paper Award will be given to the authors of the highest quality paper. The most important aspects in judging the quality of a paper will be: originality, innovativeness, relevance, and impact of the presented research.
Best Paper Award for Research Inspired by Human Language Learning and Processing
We will also continue giving a special award for the Best Paper Award for Research Inspired by Human Language Learning and Processing.
Mohit Bansal (University of North Carolina at Chapel Hill, USA)
Aline Villavicencio (University of Essex, UK and Federal University of Rio Grande do Sul, Brazil)
Jason Baldridge, Google AI Language, USA
Laurent Besacier, Université Grenoble Alpes, France
Chris Biemann, Universität Hamburg, Germany
Asli Celikyilmaz, Microsoft Research, USA
Snigdha Chaturvedi, UCSC, USA
Grzegorz Chrupala, Tilburg University, The Netherlands
Mathieu Constant, Université de Lorraine, France
Ryan Cotterell, University of Cambridge, UK
Dipanjan Das, Google AI Language, USA
Greg Durrett, UT Austin, USA
Manaal Faruqui, Google Assistant, USA
Michel Galley, Microsoft Research, USA
Dilek Hakkani-Tur, Amazon Alexa AI, USA
Mohit Iyyer, UMass Amherst, USA
Yangfeng Ji, University of Virginia, USA
Preethi Jyothi, IIT Bombay, India
Douwe Kiela, Facebook Research, USA
Graham Neubig, CMU, USA
Horacio Saggion, Universitat Pompeu Fabra, Spain
Avirup Sil, IBM Research AI, USA
Amanda Stent, Bloomberg Research, USA
Mark Stevenson, University of Sheffield, UK
Andreas Vachlos, University of Cambridge, UK
Miikka Silfverberg, University of Helsinki, Finland
Rodrigo Wilkens, Université Catholique de Louvain, Belgium
Publicity / sponsorship chair:
Ramakanth Pasunuru, University of North Carolina at Chapel Hill, USA
Pieter Fivez, University of Antwerp, Belgium
Marcely Zanon Boito, Université Grenoble Alpes, France