EMNLP 2020 : Conference on Empirical Methods in Natural Language Processing (EMNLP)

  in Conferences   Posted on April 17, 2020

Conference Information

Submission Deadline Monday 01 Jun 2020 Proceedings indexed by :
Conference Dates Nov 16, 2020 - Nov 20, 2020
Conference Address Online, United States
Conference & Submission Link https://2020.emnlp.org/
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Guide2Research Overall Ranking: 8
Category Rankings
Computational Linguistics & Speech Processing 2
Signal Processing 5
Machine Learning & Arti. Intelligence 8

Google Scholar H5-index:
88

Conference Call for Papers

Overview
The 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020) invites the submission of long and short papers on substantial, original, and unpublished research in empirical methods for Natural Language Processing. As in recent years, some of the presentations at the conference will be for papers accepted by the Transactions of the ACL (TACL) and Computational Linguistics (CL) journals.

Important Dates
Anonymity period begins: May 1, 2020
Submission deadline (long & short papers): June 1, 2020
Author response period: August 7-13, 2020
Notification of acceptance (long & short papers): September 14, 2020
Camera-ready papers due (long & short papers): October 5, 2020
Main conference: November 16-18, 2020
Workshops and tutorials: November 19-20, 2020
All deadlines are 11.59 pm UTC -12h (\”anywhere on Earth\”).

Submissions
EMNLP 2020 has the goal of a broad technical program. Relevant topics for the conference include, but are not limited to, the following areas (in alphabetical order):

Computational Social Science and Social Media
Dialogue and Interactive Systems
Discourse and Pragmatics
Generation
Information Extraction
Information Retrieval and Text Mining
Interpretability and Analysis of Models for NLP
Language Grounding to Vision, Robotics and Beyond
Linguistic Theories, Cognitive Modeling and Psycholinguistics
Machine Learning for NLP
Machine Translation and Multilinguality
NLP Applications
Phonology, Morphology and Word Segmentation
Question Answering
Resources and Evaluation
Semantics: Lexical, Sentence level, Textual Inference and Other areas
Sentiment Analysis, Stylistic Analysis, and Argument Mining
Speech and Multimodality
Summarization
Syntax: Tagging, Chunking and Parsing

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