Cross-Modal AI for Toxicity Detection in Product Reviews
2022
The rise of multimodal content in e-commerce reviews necessitates advanced toxicity detection systems that analyze text, images, and metadata synergistically.This paper introduces a crossmodal AI framework leveraging transformer architectures, hybrid fusion strategies, and contrastive learning to detect toxic content with 89% precision and 86% recall, outperforming unimodal models by 14-22% on a dataset of 600,000 annotated reviews.Technical challenges, including sarcasm detection and cultural bias, are addressed through semantic alignment and adversarial training.The study also benchmarks performance across 12 product categories and proposes scalable deployment strategies for real-world platforms.