ILAS-NINJAL Joint Conference on Language Learning and Understanding for AI Scientists and Languists
Conference Room II, HSSB, Academia Sinica, Taipei
November 11-12, 2026
Conference website: https://www.ling.sinica.edu.tw/LLU2026/
Technologies related to languages have never been this close to our daily lives. This development is leading the way to novel perspectives of language learning and understanding, shaped by contributions from linguists and non-linguists. Innovative research and technology are emerging alongside recent advances in model structures. While AI-related methodologies are having noticeable impacts on human language research, what crucial roles does linguistics play? As linguists, we are witnessing profound transformations in our field due to the methodological evolution brought about by large language models and their applications. These developments present both challenges and exciting opportunities to explore human language from both macro- and micro-level perspectives. For example, the inductive nature of learning in large language models potentially challenges assumptions about the role and nature of representations in language acquisition and processing. Motivated by the shared considerations of our colleagues at the Institute of Linguistics (ILAS) and the National Institute for Japanese Language and Linguistics (NINJAL), we decided to host an international conference to collect and process ideas about how the research and applications of language learning and understanding will be viewed and conducted by AI scientists and linguists. Through this conference, we aim to bring together AI scientists and linguists to explore or at least to outline the challenges and opportunities that lie ahead.
We invite submissions of abstracts with a maximum length of 2 pages in PDF format for oral or poster presentations. Submissions may address, but are not limited to, the following topics:
The concept of “understanding a language”: What does it mean to learn and use a language? How to evaluate humans’ and LLMs' performance in understanding a language?
Human language acquisition and AI learning: Comparing how children and machines acquire/learn languages. Is human language development the unique way to learn to use and understand language? How can AI technology help human learn and understand languages?
Cognitive and neural foundations of language and AI: How do language and intelligence emerge from neural mechanisms versus AI models?
Computational models of linguistic representation: How do LLMs represent meaning and sound structure? How do linguists and LLMs study the gaps and connections between symbolic, distributional, and conceptual representation?
Please submit your abstract to ai.linguistics.workshop@gmail.com by May 30, using the abstract template provided on the conference website.
Invited Speakers:
Berlin Chen (National Taiwan Normal University)
Yasuhiro Kondo (Aoyama Gakuin University)
Yohei Oseki (University of Tokyo)
Andreas Witt (Leibniz-Institut für Deutsche Sprache)
Demo/Exhibition:
Leibniz-Institut für Deutsche Sprache (IDS)
Institute of Linguistics, Academia Sinica (ILAS)
National Institute for Japanese Language and Linguistics (NINJAL)
Important Dates:
Abstract submission deadline: May 30, 2026
Notification of acceptance: July 31, 2026
Early registration: August 15, 2026
Final version due: August 31, 2026
Conference dates: November 11-12, 2026
Contact:
Ms. Tiffany Liu
ai.linguistics.workshop@gmail.com
