ENHANCING ATTENTION IN TRANSFORMER ENCODERS FOR AGGLUTINATIVE LANGUAGES THROUGH MORPHOLOGICAL QKV: THE MORPH-QKV MODEL FOR UZBEK
Agglutinative languages encode a substantial part of grammatical relations through ordered affix sequences attached to lexical stems. Encoders in the BERT family can learn some of these regularities implicitly from large corpora, but conventional self-attention does not treat lemma, stem/root, part...

Actual problems in modern technical sciences / 2026 / August

Sharipov Maksud

Volume 10 | Issue 8

3 August 2026, 22:01

DESIGN AND IMPLEMENTATION OF A MODEL AND ALGORITHM FOR PART-OF-SPEECH TAGGING IN UZBEK TEXTS USING THE CONDITIONAL RANDOM FIELDS (CRFs) APPROACH
This paper presents a part-of-speech tagging system for the Uzbek language based on the Conditional Random Fields (CRF) approach. Using a manually annotated corpus and a set of language-specific morphological and contextual features, the model was trained and evaluated through 5-fold...

Actual problems in modern technical sciences / 2025 / July

Sharipov Maksud

Volume 9 | Issue 7