Anthropogenic Regional Adaptation in Multimodal Vision-Language Model
Abstract
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 dedicated framework for assessing human-centric alignment in vision-language systems. We offer two contributions to address this gap. First, we introduce Anthropogenic Regional Adaptation: a novel paradigm that aims to optimize model relevance to specific regional contexts while ensuring the retention of global generalization capabilities. Second, we present a simple, but effective adaptation method named Geographical-generalization-made-easy (GG-EZ), which utilizes regional data filtering and model merging. Through comprehensive experiments on 3 VL architectures: large vision-language models, text-to-image diffusion models, and vision-language embedding models, and a case study in Southeast Asia (SEA) regional adaptation, we demonstrate the importance of Anthropogenic Regional Adaptation and the effectiveness of GG-EZ, showing 5-15% gains in cultural relevance metrics across SEA while maintaining over 98% of global performance and even occasionally surpassing it. Our findings establish Anthropogenic Regional Alignment as a foundational paradigm towards applicability of multimodal vision-language models in diverse regions and demonstrate a simple-yet-effective baseline method that optimizes regional value alignment while preserving global generalization.
Cite
@article{arxiv.2604.11490,
title = {Anthropogenic Regional Adaptation in Multimodal Vision-Language Model},
author = {Samuel Cahyawijaya and Peerat Limkonchotiwat and Tack Hwa Wong and Hitesh Laxmichand Patel and Amit Agarwal and Manuel Antonio Rufino and Carlos Rafael Catalan and Muhammad Reza Qorib and Vicky Feliren and Holy Lovenia and Aye Hninn Khine and Frederikus Hudi and David Anugraha and Alham Fikri Aji and Romrawin Chumpu and Viet-Thanh Pham and Minghan Wang and Mohamed Fazli Imam and Ruochen Zhang and Joseph Marvin Imperial and Khumaisa Nur'aini and Do Xuan Long and Musa Izzanardi Wijanarko and Joel Ruben Antony Moniz and Patrick Amadeus Irawan and Hanif Muhammad Zhafran and Isaiah Flores and Salsabila Zahirah Pranida and Jun Kevin and Jostin Jerico Rosal and Patricia Nicole Monderin and Kun Kerdthaisong and Ahmad Mustafid and My Chiffon Nguyen and Natchapon Jongwiriyanurak and Siva Worajitwannakul and Haochen Li and Adrian Xuan Wei Lim and Bin Wang and Muhammad Ravi Shulthan Habibi and Lynnette Hui Xian Ng and Mithil Bangera and Yeshil Bangera and Priyaranjan Pattnayak and Dun Li Chan and Sherissa Caren Djuniwar and Cho Chan Myei Oo and Hee Ming Shan},
journal= {arXiv preprint arXiv:2604.11490},
year = {2026}
}