CAMIE: Co-Engagement-Aware Multimodal Item Embeddings for Snap Dynamic Product Ads Retrieval

Xiaodong Liu; Siman Wang; Congfei Zhang; Hsiang-wei Chao; Xiao Bai; Wen Zhang; Jingxiao Ma; Zhe Liu; Yunzhi Zhou; Yajun Wang; Jinchao Li; Yu Zhang

arXiv · 2608.30255

CAMIE: Co-Engagement-Aware Multimodal Item Embeddings for Snap Dynamic Product Ads Retrieval

Xiaodong Liu·Siman Wang·Congfei Zhang·Hsiang-wei Chao·Xiao Bai·Wen Zhang·Jingxiao Ma·Zhe Liu·Yunzhi Zhou·Yajun Wang·Jinchao Li·Yu Zhang

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Abstract

Item-to-item (I2I) retrieval is a core primitive in large-scale recommendation and advertising systems. In production Snap Dynamic Product Ads (DPA), I2I retrieval faces two challenges: separate visual, textual, and multimodal encoders fragment the retrieval stack, and content-only training does not align embeddings with the co-engagement behavior that drives downstream conversions. We present CAMIE, a co-engagement-aware multimodal item embedding framework for Snap DPA retrieval. CAMIE builds on LLM/MLLM backbones, using their native multimodal interfaces to represent item images and metadata in a shared embedding space. It then fine-tunes the backbone on co-engaged item pairs mined from user journeys with a symmetric in-batch InfoNCE objective. Offline, CAMIE outperforms the strongest commercial multimodal embedding model on Recall@10 and serves text-only retrieval from the same checkpoint with minimal quality loss. Online, CAMIE serves as a drop-in replacement for two deployed content-based I2I encoders, delivering +0.390% CTR / +10.832% CVR over the multimodal control, +18.958% CTR / +13.12% CVR over the text control, and +0.211% CTR / +1.911% CVR on overall DPA traffic. CAMIE is deployed in production.

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Xiaodong Liu, Siman Wang, Congfei Zhang, Hsiang-wei Chao, Xiao Bai, Wen Zhang, Jingxiao Ma, Zhe Liu, Yunzhi Zhou, Yajun Wang, Jinchao Li, Yu Zhang. 2026-08-31. CAMIE: Co-Engagement-Aware Multimodal Item Embeddings for Snap Dynamic Product Ads Retrieval. https://arxiv.org/abs/2608.30255

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