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20182026
most citedImproving Native Ads CTR Prediction by Large Scale Event Embedding and Recurrent Networks

7 citations · 12 across the 8 of their papers we have counts for

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Showing 2026Show all

5 papers · 1 filter

cs.IR2026

LLM-based User-Product Relevance Evaluation for Dynamic Product Advertising

Wen Zhang, Xiao Bai, Hsiang-wei Chao +9

Dynamic Product Advertising (DPA) retrieval systems are a core component of modern e-commerce advertising; however, their evaluation remains challenging. Conventional offline engag…

cs.IR2026

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

Xiaodong Liu, Siman Wang, Congfei Zhang +9

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 challe…

cs.IR2026

SetMIR: Multi-Interest Retrieval as Set Prediction

Xiaodong Liu, Congfei Zhang, Hsiang-wei Chao +13

Embedding-based retrieval is at the core of industrial recommender systems, but a single user embedding is often too limited to capture a user's diverse interests. Multi-interest r…

cs.IR2026

SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads

Congfei Zhang, Jingxiao Ma, Xiaodong Liu +14

Dynamic Product Ads (DPA) require retrieving relevant items from multi-million product catalogs, balancing two competing objectives: retargeting (re-surfacing known interests) and…

cs.IR2026

EGR: Embedding-Native Generative Retrieval with a Shared LLM

Xiaodong Liu, Congfei Zhang, Hsiang-wei Chao +13

Generative retrieval is increasingly popular in large-scale recommendation and advertising systems, yet current methods introduce practical complications. Semantic-ID methods rely…