HUKUKBERT: Domain-Specific Language Model for Turkish Law
Natural language processing (NLP) advances have powered a generation of LegalTech systems, but Turkish law remains under-served by domain-specific data and models. English has legal encoders such as LEGAL-BERT; no comparable high-volume Turkish counterpart exists. We introduce HukukBERT, a Turkish legal language model trained on a 19 GB cleaned corpus using a hybrid domain-adaptive pre-training (DAPT) recipe that mixes Whole-Word Masking, Token Span Masking, Word Span Masking, and targeted Keyword Masking. We compared our 48K WordPiece tokenizer and DAPT pipeline against general-purpose and existing domain-specific Turkish models. On the Legal Cloze Test - a masked legal term prediction b...
| Authors | Mehmet Utku Öztürk, Tansu Türkoğlu, Buse Buz-Yalug |
|---|---|
| Primary category | cs.CL |
| Published | 6 April 2026 |
| Last updated at source | 4 August 2026 |
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