HordeVision: An Open-Source Kazakh Vision-Language Model

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Authors: Pavel Zubitskii, Vitaliy Morozov, Sanzhar Murzakhmetov, Beksultan Sagyndyk, Sanzhar Umbet
Cited by: 1

Abstract

We present HordeVision, an open-source Kazakh vision-language model designed for optical character recognition (OCR), image captioning, visual question answering (VQA), reasoning, and instruction following. Supporting local open-source initiatives, HordeVision addresses the critical need for Kazakh-language multimodal AI systems. Our dataset was collected using a syntactic data generation pipeline covering diverse contexts including social life, education, work, economy, media, communications, culture, and heritage. We employ a two-stage training approach combining supervised fine-tuning (SFT) and reinforcement learning from human feedback using Group Relative Policy Optimization (GRPO). Evaluated on a human-annotated benchmark against models including Google Gemma,

Fields of Study & Subjects

Multimodal Machine Learning Applications Advanced Image and Video Retrieval Techniques Topic Modeling

Publication details

Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Publication date
10 January 2026
Document type
Preprint