EMNLP-IJCNLP 2019 : Conference on Empirical Methods in Natural Language Processing & International Joint Conference on Natural Language Processing 2019

  in Conferences   Posted on January 27, 2019

Conference Information

Submission Deadline Tuesday 21 May 2019 Proceedings indexed by :
Conference Dates Dec 5, 2019 - Dec 7, 2019
Conference Address Hong Kong, Hong Kong
Conference & Submission Link https://www.emnlp-ijcnlp2019.org/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Call for Papers

News

November 16, 2018. The website has been launched.

Welcome!

SIGDAT, the Association for Computational Linguistics (ACL) special interest group on linguistic data and corpus-based approaches to NLP, and the AFNLP, the Asian Federation of Natural Language Processing, invite you to participate in the Conference on Empirical Methods in Natural Language Processing (EMNLP) & International Joint Conference on Natural Language Processing (IJCNLP) 2019 in Hong Kong. EMNLP-IJCNLP 2019 will be held at the Asia World Expo in Hong Kong from November 3rd through November 7th, 2019.

Important Dates

Submissions due (long & short) Tuesday May 21, 2019

Author response period starts Tuesday July 9, 2019

Author responses due Monday July 15, 2019

Notification of acceptance Monday August 12, 2019

Camera-ready papers due Friday August 30, 2019

Workshops & tutorials Sunday – Monday November 3–4, 2019

Main conference Tuesday – Thursday November 5–7, 2019

Note: All deadlines are calculated at 11:59pm Pacific Daylight Savings Time (UTC -7h).

EMNLP-IJCNLP 2019 Anti-Harassment Policy

EMNLP-IJCNLP 2019 adheres to the ACL Anti-Harassment Policy. Any participant who experiences harassment or hostile behavior may contact any current member of the ACL Executive Committee or contact Priscilla Rasmussen, who is usually available at the registration desk of the conference. Please be assured that if you approach us, your concerns will be kept in strict confidence, and we will consult with you on any actions taken.

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