Year: 2026
Type: preprint
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,
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7119709855