nlp

We are pleased to invite participation in the First Workshop on Optimal Reliance and Accountability in Interaction with Generative Language Models (ORIGen) to be held in conjuction with the Conference on Language Modeling (COLM) in Montreal, Canada, on October 10, 2025.

***Call for Papers WASP @ IJCNLP-AACL 2025***

https://ui.adsabs.harvard.edu/WIESP/2025/

The 8th International Conference on Natural Language and Speech Processing (ICNLSP 2025) welcomes contributions on both the theoretical foundations and applied aspects of Natural Language Processing (NLP) and Speech Processing. The conference will feature regular sessions, along with keynote talks delivered by distinguished international researchers.
We invite authors to submit their work on topics relevant to ICNLSP 2025 and contribute to advancing research in the field.

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. Assessing whether LLMs understand 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.

The 8th International Conference on Natural Language and Speech Processing (ICNLSP 2025) welcomes contributions on both the theoretical foundations and applied aspects of Natural Language Processing (NLP) and Speech Processing. The conference will feature regular sessions, along with keynote talks delivered by distinguished international researchers.
We invite authors to submit their work on topics relevant to ICNLSP 2025 and contribute to advancing research in the field.

The conference will be hybrid.

The 12th Mid-Atlantic Student Colloquium on Speech, Language and Learning (MASC-SLL 2025) is a one day event bringing together students, postdocs, faculty and researchers from universities and industry in the Mid-Atlantic area. The colloquium is an opportunity for students and postdocs to present preliminary or completed work and to network with other researchers working in related fields.

The 30th International Conference on Natural Language & Information Systems (NLDB 2025)
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Conference Website
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https://www.jaist.ac.jp/event/nldb2025

Dates and Venue
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4-6 July 2025
Kanazawa Chamber of Commerce and Industry
9-13 Oyamamachi, Kanazawa, Ishikawa 920-0918, Japan

Call for Papers

Call for Papers
The quantitative turn: NLP and AI Methods in Romance Linguistics

With this shared task, we aim to fuel research on automatic analysis and detection of greenwashing by challenging participants to build systems that categorize excerpts from German sustainability reports for (A) content class and (B) statement verifiability.