Codezone Research Group at ImageEval Shared-Task 2: Arabic Image Captioning Using BLIP and M2M100: A Two-Stage Translation Approach for ImageEval 2025
Year: 2025
Type: conference-paper
Abstract: This paper details the ImageEval 2025 Shared Task on Arabic image captioning.We designed a two-step, zero-shot framework that utilises the BLIP multimodal vision-language model to first generate English captions.These captions are then converted to Arabic via the M2M100 multilingual translation model.We tested the full pipeline on the official ImageEval 2025 benchmarking set, obtaining a cosine similarity of 0.383 and an LLM Judge score of 15.14.The corroborating numerical and qualitative findings confirm the viability of a translation-driven methodology for cross-lingual image captioning in Arabic, a language often classified as low-resource.Nonetheless, the experiments also uncovered weaknesses: subtle semantic layers and culturally specific references are inadequately conveyed in the output and merit focused attention in subsequent iterations.
Author: Abdulkadir Shehu Bichi
Institution: Baba Ahmed University
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4416037746