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@article{178000,
        author = {Tejal Sudhakarrao Mohod and Dr. Ashish A. Bardekar},
        title = {Review Paper On A Prompt Based Modal for Hateful Meme Classification},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {4046-4050},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178000},
        abstract = {This paper presents a prompt-based multimodal framework for hateful meme classification and emotional content analysis, integrating visual and textual cues to identify and interpret harmful content in online memes. The proposed system leverages EasyOCR to extract embedded text from meme images, BLIP for generating descriptive image captions, and RoBERTa for contextual hatefulness classification. Additionally, an emotion detection module based on a DistilRoBERTa model captures the emotional undertone of the memes. To enhance usability, the system generates a comprehensive PDF report summarizing the extracted text, caption, hate classification, and emotion distribution. This architecture addresses the challenges in meme analysis by combining vision-language processing with transformer-based models, delivering a scalable and practical solution for real-world deployment.},
        keywords = {BLIP, Hateful Meme Detection, Multimodal Learning, OCR, RoBERTa, Emotion Detection, PDF Report Generation},
        month = {May},
        }