ALF: Advertiser Large Foundation Model for Multi-Modal Advertiser Understanding
Journal:
arXiv
Published Date:
Apr 26, 2025
Abstract
We present ALF (Advertiser Large Foundation model), a multi-modal transformer
architecture for understanding advertiser behavior and intent across text,
image, video and structured data modalities. Through contrastive learning and
multi-task optimization, ALF creates unified advertiser representations that
capture both content and behavioral patterns. Our model achieves
state-of-the-art performance on critical tasks including fraud detection,
policy violation identification, and advertiser similarity matching. In
production deployment, ALF reduces false positives by 90% while maintaining
99.8% precision on abuse detection tasks. The architecture's effectiveness
stems from its novel combination of multi-modal transformations, inter-sample
attention mechanism, spectrally normalized projections, and calibrated
probabilistic outputs.
