Toward Human-Level Understanding: A Systematic Review of Vision-Language Models for Image Captioning

Ansar Hani; Najiba Tagougui; Monji Kherallah

doi:10.34028/iajit

Article Details

Toward Human-Level Understanding: A Systematic Review of Vision-Language Models for Image Captioning

Authors:

Ansar Hani | Najiba Tagougui | Monji Kherallah

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.23 Issue 1, pp.81-97

Document Type:

Article

Publication Date:

1/2026

Document Language:

English

Document ID (Org No.):

2001389835

pISSN:

2309-4524

DOI:

10.34028/iajit

Keywords:

Abstract:

 Large Language Models (LLMs), particularly multimodal LLMs, have significantly enhanced image captioning in recent years, producing output that is more descriptive, detailed, and context-aware. However, differences in architecture and training data lead to captions that vary in length, style, and level of detail, offering flexibility for diverse applications. In this survey, we provide a comprehensive overview and comparative analysis of prominent Vision-Language Models (VLMs) for image captioning, with a focus on their performance in zero-shot settings on the Microsoft Common Objects in Context (MS- COCO) dataset. We evaluate these models using both human assessments (fluency, groundedness, relevance) and automatic metrics Contrastive Language–Image Pretraining Score (CLIPScore). Our findings reveal trade-offs between efficiency and performance, linking architectural decisions to issues such as hallucinations and caption grounding. Beyond benchmarking, we propose a human evaluation to capture nuances like fluency, factual grounding, and stylistic preferences, leading to recommendations for selecting VLMs based on different use cases.

Article Details

Toward Human-Level Understanding: A Systematic Review of Vision-Language Models for Image Captioning

Authors:

Ansar Hani | Najiba Tagougui | Monji Kherallah

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.23 Issue 1, pp.81-97

Document Type:

Article

Publication Date:

1/2026

Document Language:

English

Document ID (Org No.):

2001389835

pISSN:

2309-4524

DOI:

10.34028/iajit

Image captioning

vision-language models

multimodal learning

large language models

Issues

Article Details

Toward Human-Level Understanding: A Systematic Review of Vision-Language Models for Image Captioning

Authors: Ansar Hani | Najiba Tagougui | Monji Kherallah

Publisher: Zarqa University, Jordan

Journal: The International Arab Journal of Information Technology (IAJIT) Vol.23 Issue 1, pp.81-97

Document Type: Article

Publication Date: 1/2026

Document Language: English

Document ID (Org No.): 2001389835

pISSN: 2309-4524

DOI: 10.34028/iajit

Image captioning

vision-language models

multimodal learning

large language models

Issues

Authors:

Ansar Hani | Najiba Tagougui | Monji Kherallah

Publisher:

Zarqa University, Jordan

Journal:

The International Arab Journal of Information Technology (IAJIT) Vol.23 Issue 1, pp.81-97

Document Type:

Article

Publication Date:

1/2026

Document Language:

English

Document ID (Org No.):

2001389835

pISSN:

2309-4524

DOI:

10.34028/iajit