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CLNLP 2023 : 2023 4th International Conference on Computational Linguistics and Natural Language Processing (CLNLP 2023)


When Aug 18, 2023 - Aug 20, 2023
Where Nanjing, China
Submission Deadline Jul 10, 2023
Notification Due Jul 10, 2023
Final Version Due Jul 10, 2023
Categories    computational linguistics   natural language processing

Call For Papers

★2023 4th International Conference on Computational Linguistics and Natural Language Processing (CLNLP 2023)-- Ei Compendex & Scopus—Call for paper
August 18-20, 2023|Nanjing, China|Website:

★CLNLP 2023 welcomes researchers, engineers, scientists and industry professionals to an open forum where advances in the field of Computational Linguistics and Natural Language Processing can be shared and examined. The conference is an ideal platform for keeping up with advances and changes to a consistently morphing field. Leading researchers and industry experts from around the globe will be presenting the latest studies through papers and oral presentations.

★Publication and Indexing
Accepted and presented papers will be published in the digital conference proceedings which will submitted to Ei Compendex, Scopus, CPCI, Google Scholar and other major databases for index.
Excellent Papers from CLNLP 2023 will be recommended to be submitted for publication in journal.

★Keynote Speakers
Prof. Haofen Wang——Tongji University, China
Prof. Huiyu Zhou——University of Leicester, UK
Prof. Yulan He——Kings College London, UK

★Program Preview/ Program at a glance
August 18: Registration + Icebreaker Reception
August 19: Opening Ceremony+ KN Speech+ Technical Sessions
August 20: Technical Sessions+ Half day tour/Lab tours

★Paper Submission
PDF version submit via CMT:

Ms. Riva H. W. Wong

Call for papers(

Information extraction

Natural language generation


Discourse and Pragmatics

Tagging, Chunking, Syntax and Parsing

Machine learning for NLP

Sentiment Analysis and Argument Mining


Computational Social Science and Cultural Analytics

Information retrieval and text mining

Interpretability and Analysis of Models for NLP

NLP applications

Question Answering

Large-scale grammars of natural languages

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