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Yanaka Lab
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The lab studies natural language processing that understands the meaning of language the way humans do, in order to uncover how humans understand meaning.
AboutAbout the lab
Understanding the meaning of language like a human.
Through research on natural language processing technologies that understand the meaning of language the way humans do, the Yanaka Lab aims to uncover the mechanisms by which humans understand the meaning of language.
Artificial intelligence technologies that process natural language, such as information retrieval and machine translation, have become part of everyday life.
However, it is still not clear whether these technologies understand meaning the way we do, nor how we ourselves understand it.
Working with researchers in Japan and abroad, the lab pursues its research based on the integration of machine learning and symbolic logic.
Key terms
- Language model
- A computer model that has learned patterns in how words are arranged from a large amount of text. It is used to generate and understand text.
- Natural language inference
- A technology that compares two sentences and uses a computer to determine the relationship between them, such as whether one can be derived from the other.
- Symbolic logic
- A method in logic that expresses the meaning of sentences with symbols and formulas, and reasons correctly according to fixed rules.
NewsLab news
Presented research results at EMNLP 2026, an international conference on natural language processing
A student won the Best Paper Award at the ACL 2026 Student Research Workshop
Presented research results at ACL 2026, an international conference on computational linguistics
Presented research results at EACL 2026, an international conference on computational linguistics
ResearchResearch themes
The lab works with researchers in Japan and abroad on natural language processing technologies that understand the meaning of language the way humans do. Its research centers on three areas: analysis of language models, reasoning that integrates machine learning and symbolic logic, and collaboration between humans and systems.
*Illustrative imageInterdisciplinary Analysis of Language Models
The lab investigates how well language models understand the meaning of language, and whether they have learned unintended biases from their data. In collaboration with researchers in fields such as theoretical linguistics, it creates datasets and analysis methods for examining language models from multiple perspectives.
*Illustrative imageReasoning Integrating Machine Learning and Symbolic Logic
The lab studies natural language inference, the technology of determining the relationship between sentences. By combining the strengths of machine learning, whose interpretation process is hard to see, and symbolic logic, which is weak at flexible processing, it develops reasoning technologies that address the weaknesses of each.
*Illustrative imageLanguage Processing Through Human-System Collaboration
The lab is exploring applied research that draws on human knowledge for uses such as checking medical texts and internal company documents, and that stores human feedback in an reasoning system to make the work more efficient.
MembersFaculty
The members of the Yanaka Lab consist of faculty, administrative assistants, technical assistants, project researchers, research fellows, doctoral and master's students, and exchange students.As of 2026
- Associate ProfessorHitomi YanakaPublications ↗
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Bookshelves and interior of the library of the Academy for Judiciary” Szeronine / CC BY 4.0 (cropped)
- Interdisciplinary Analysis of Language Models: “Artificial Neural Network with Chip” mikemacmarketing / photo on flickr / CC BY 2.0 (cropped)
- Reasoning Integrating Machine Learning and Symbolic Logic: “Venn diagram of three sets” Oleg Alexandrov / Public domain (cropped)
- Language Processing Through Human-System Collaboration: “IMG Dokumentationsmappe” BlankeVla / CC BY-SA 4.0 (cropped)
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