3 papers
cs.AI2026
Anthropogenic Regional Adaptation in Multimodal Vision-Language Model
Samuel Cahyawijaya, Peerat Limkonchotiwat, Tack Hwa Wong +45
While the field of vision-language (VL) has achieved remarkable success in integrating visual and textual information across multiple languages and domains, there is still no dedic…
cs.CV2025
When Better Teachers Don't Make Better Students: Revisiting Knowledge Distillation for CLIP Models in VQA
Pume Tuchinda, Parinthapat Pengpun, Romrawin Chumpu +3
Vision-language models (VLMs) have achieved remarkable success across multimodal tasks, yet their substantial computational demands hinder efficient deployment. Knowledge distillat…
cs.CL2025
Distilling Multilingual Vision-Language Models: When Smaller Models Stay Multilingual
Sukrit Sriratanawilai, Jhayahgrit Thongwat, Romrawin Chumpu +3
Vision-language models (VLMs) exhibit uneven performance across languages, a problem that is often exacerbated when the model size is reduced. While Knowledge distillation (KD) dem…