1st Call For Papers: 6th Workshop on Computational Approaches to Linguistic Code-Switching
This edition will be the sixth edition of the workshop collocated with EMNLP 2023, marking a 10-year anniversary.
This edition will be the sixth edition of the workshop collocated with EMNLP 2023, marking a 10-year anniversary.
SECOND CALL FOR PAPERS - THE 2ND MULTILINGUAL REPRESENTATION LEARNING (MRL) WORKSHOP
7-8 DECEMBER 2022, ABU DHABI (CO-LOCATED WITH EMNLP)
Location: Hybrid
Contact Email: mrlw2022 [at] gmail.com
Dear all,
It is our great pleasure to invite you to the second edition of multilingual representation learning that will be held at EMNLP 2022 (as a hybrid WS) on December 8, 2022. The details regarding the paper submission and the shared task are given below:
Dear all,
This is to invite you to participate in the Multilingual Clause-level Morphology shared task co-located with the 2nd Workshop on Multilingual Representation Learning (MRL) at EMNLP 8 December 2022, Abu Dhabi. More details can be found here: https://sigtyp.github.io/st2022-mrl.html
Best,
On behalf of the MRL 2022 Organizers,
Gözde Gül Şahin,
Koç University, KUIS AI Fellow
Istanbul/Turkey
https://gozdesahin.github.io
[Deadline Extended to April 15]
The 3rd Deep Learning for Low-resource NLP (DeepLo) workshop is co-located with NAACL 2022.
[2nd Call for Papers]
The 3rd Deep Learning for Low-resource NLP (DeepLo) workshop is co-located with NAACL 2022.
The 3rd Deep Learning for Low-resource NLP (DeepLo) workshop is co-located with NAACL 2022.
News
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- The deadline for registration to the task has been extended to October 1!
This is the second call for task participation to SHINRA2020-ML Classification task.
* The registration and result submission deadline has been extended to August 31, 2020.
* We are pleased to inform you that we have released the SHINRA2020-ML leaderboard:
SHINRA2020-ML leaderboard.
https://www.nlp.ecei.tohoku.ac.jp/projects/AIP-LB/task/shinra2020-ml
We look forward to having you join us.
Universal Dependencies (UD) is a framework for cross-linguistically consistent treebank annotation that has so far been applied to over 50 languages.