【Call for Papers】《Language Learning and Understanding for AI Scientists and Linguists (LLU 2026)》Institute of Linguistics, Academia Sinica (ILAS) and National Institute for Japanese Language and Linguistics (NINJAL)

Language Learning and Understanding for AI Scientists and Linguists

(LLU 2026)

Conference Room II, HSSB, Academia Sinica, Taipei

November 11-12, 2026

Conference websitehttps://www.ling.sinica.edu.tw/LLU2026/

As recent advances in AI and large language models continue to reshape language research, LLU 2026 aims to foster dialogue between AI scientists and linguists on research and applications related to language learning, representation, and understanding. Jointly organized by the Institute of Linguistics, Academia Sinica (ILAS) and the National Institute for Japanese Language and Linguistics (NINJAL), LLU 2026 welcomes submissions presenting ideas, approaches, and findings from linguistic, cognitive, and AI perspectives on topics including, but not limited to, the following:

–   Language understanding in humans and large language models

–   Human language acquisition and AI learning

–   Cognitive and neural foundations of language and AI

–   Computational models of linguistic representation

 

Submission:

Abstracts of no more than two pages in PDF format should be submitted to

ai.linguistics.workshop@gmail.com no later than June 30, 2026.

 

Exhibition:

LLU 2026 will feature research from three national institutes specializing in language and linguistics studies.

–   Leibniz-Institut für Deutsche Sprache (IDS, Germany)

–   Institute of Linguistics, Academia Sinica (ILAS, Taiwan)

–   National Institute for Japanese Language and Linguistics (NINJAL, Japan)

 

Invited Speakers:

–      Berlin Chen (National Taiwan Normal University): Advances and Challenges of Automatic Spoken Language Assessment and Feedback

–      Yasuhiro Kondo (Aoyama Gakuin University): Does AI See Like We Speak? The Egocentric-Allocentric Axis in Vector Spaces

–      Yohei Oseki (University of Tokyo): Large Language Models in Computational Psycholinguistics

–      Andreas Witt (Leibniz-Institut für Deutsche Sprache): Artificial Intelligence for Language: Text- Structures-Humans

 

Contact: Ms. Tiffany Liu (ai.linguistics.workshop@gmail.com)

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