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Fine-Tuning Qwen3 Models for the Legal Domain of Kazakhstan: A Comparative Study of LoRA-Adapted Models for Bilingual Legal Question Answering.

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Title: Fine-Tuning Qwen3 Models for the Legal Domain of Kazakhstan: A Comparative Study of LoRA-Adapted Models for Bilingual Legal Question Answering.
Authors: Yeleussinov, Arman1, Buribayev, Zholdas1,2, zhburibaev@gmail.com, Beisov, Nurbol1, Kalzhanov, Nurlykhan1,2, Satymbekov, Maxatbek2, Akhatov, Ualikhan1, Alimkulov, Yerbol1
Source: Applied Sciences (2076-3417); Jul2026, Vol. 16 Issue 13, p6777, 24p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 195446002
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Fine-Tuning Qwen3 Models for the Legal Domain of Kazakhstan: A Comparative Study of LoRA-Adapted Models for Bilingual Legal Question Answering.
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        Value: 10.3390/app16136777
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      – Code: eng
        Text: English
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        PageCount: 24
        StartPage: 6777
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      – TitleFull: Fine-Tuning Qwen3 Models for the Legal Domain of Kazakhstan: A Comparative Study of LoRA-Adapted Models for Bilingual Legal Question Answering.
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              M: 07
              Text: Jul2026
              Type: published
              Y: 2026
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