Asian Legal NLP (ALEN 2026)
Aim and Scope
Recent developments in natural language processing, legal informatics, and AI have created
new opportunities for the computational analysis of legal texts across Asia. This special session
explores Asian Legal NLP by bringing together interdisciplinary research on the analysis and
processing of legal documents in diverse Asian jurisdictions.
We welcome contributions on topics including legal text analysis, information extraction, sum-
marization, question answering, statutory and case law retrieval, semantic similarity, machine
translation, terminology alignment, corpus construction, and benchmark development. We are
particularly interested in research that addresses the linguistic, structural, and institutional char-
acteristics of Asian legal texts, including those of Southeast Asia as well as jurisdictions using
Chinese characters, and in comparative or multilingual approaches that connect legal language
technologies across the region.
By integrating perspectives from NLP, AI, law, and digital humanities, this special session aims
to promote broader collaboration and chart new directions for legal text processing in Asia.
Key Topics
- Legal text analysis and document classification
- Information extraction from statutes, regulations, and case law
- Legal summarization and question answering
- Statutory retrieval and case law retrieval
- Semantic similarity and cross-jurisdictional provision mapping
- Machine translation for legal texts
- Legal terminology alignment and multilingual lexicons
- Construction of legal corpora, datasets, and benchmarks
- NLP for Asian legal languages and multilingual legal systems
- Comparative and interdisciplinary studies on legal language technologies in Asia
Submission Guideline
https://kse2026.kse-conferences.org/call-for-papers/
Session Organizers
Makoto Nakamura
Niigata Institute of Technology, Japan, mnakamur@niit.ac.jp
Chao-Lin Liu
National Chengchi University, Taiwan, chaolin@g.nccu.edu.tw
Le-Minh Nguyen
Japan Advanced Institute of Science and Technology, Japan, nguyenml@jaist.ac.jp