computational linguistics

The goals of BabyLM are to bring together multiple disciplines to answer an enduring question: how can a computational system learn language from limited inputs? Cognitive scientists investigate this question by trying to understand how humans learn their native language during childhood. Computer scientists tackle this question by attempting to build efficient machine-learning systems to accomplish this task.

SIGTURK—
The Second Workshop on
Natural Language Processing for Turkic Languages
At EACL 2026

Rabat, Morocco
March 28-29, 2026[1]

# Introduciton

We are excited to announce the Second Meeting of the ACL Special
Interest Group on Turkic Languages, held in conjunction with The 19th
Conference of the European Chapter of the Association for Computational
Linguistics (EACL 2026), Rabat, Morocco.

Second International Workshop on Construction Grammars and NLP (CxGs+NLP 2025)
Call for Papers

Please join the workshop’s Google Group for the latest updates and to post any questions you might have.

Overview

CoNLL 2025: 2nd Call for Papers
Vienna, Austria, July 31 - August 1, 2025 (co-located with ACL)
https://www.conll.org/

NEW! This year, CoNLL will only accept direct submissions…
NEW! … both archival and non-archival! (see below)

LaTeCH-CLfL 2025:
The 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

to be held on May 3rd or 4th, 2025 in conjunction with NAACL 2025 in Albuquerque, NM.

https://sighum.wordpress.com/latech-clfl-2025/

Second Call for Papers (with apologies for cross-posting)

Organisers: Diego Alves, Yuri Bizzoni, Stefania Degaetano-Ortlieb, Anna Kazantseva, Janis Pagel, Stan Szpakowicz

LaTeCH-CLfL 2025:
The 9th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature

to be held on May 3rd or 4th, 2025 in conjunction with NAACL 2025 in Albuquerque, NM.

https://sighum.wordpress.com/latech-clfl-2025/

Second Call for Papers (with apologies for cross-posting)

Organisers: Diego Alves, Yuri Bizzoni, Stefania Degaetano-Ortlieb, Anna Kazantseva, Janis Pagel, Stan Szpakowicz

*** CMCL 2025 – Second Call for Papers***
The 14th edition of the Workshop on Cognitive Modeling and Computational Linguistics (CMCL 2025)
https://openreview.net/group?id=aclweb.org/NAACL/2025/Workshop/CMCL

CMCL 2025 will be co-located with the 2025 Annual Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025).

===Final Call for Main Conference Papers===
EMNLP 2024 invites the submission of long and short papers featuring substantial, original, and unpublished research on empirical methods for Natural Language Processing. EMNLP2024 has a goal of a diverse technical program—in addition to traditional research results, papers may contribute negative findings, survey an area, announce the creation of a new resource, argue a position, report novel linguistic insights derived using existing computational techniques, and reproduce, or fail to reproduce, previous results.

Dear colleagues,

This is the second Call for Workshops for the 31st International Conference on Computational Linguistics, scheduled to take place from 19th to 24th January 2025 in Abu Dhabi, UAE.

Website: https://coling2025.org

submission link: https://softconf.com/coling2025/wsCL25/

Proposal submission due May 31, 2024

Large language models (LLMs) have revolutionized the development of interactional artificial intelligence (AI) systems by democratizing their use. These models have shown remarkable advancements in various applications such as conversational AI and machine translation, marking the undeniable advent of the human-machine era. However, despite their significant achievements, state-of-the-art systems still exhibit shortcomings in language understanding, raising questions about their true comprehension of human languages.
The concept of language understanding has always been contentious, as meaning-making depends not only on form and immediate meaning but also on context. Therefore, understanding natural language involves more than just parsing form and meaning; it requires access to grounding for true comprehension. Equipping language models with linguistics-grounded capabilities remains a complex task, given the importance of discourse, pragmatics, and social context in language understanding.
Understanding language is a doubly challenging task as it necessitates not only grasping the intrinsic capabilities of LLMs but also examining their impact and requirements in real-world applications. While LLMs have shown effectiveness in various applications, the lack of supporting theories raises concerns about ethical implications, particularly in applications involving human interaction.
The “Language Understanding in the Human-Machine Era” (LUHME) workshop aims to reignite the debate on the role of understanding in natural language use and its applications. It seeks to explore the necessity of language understanding in computational tasks like machine translation and natural language generation, as well as the contributions of language professionals in enhancing computational language understanding.