3 papers
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.CV2024
Panda-70M: Captioning 70M Videos with Multiple Cross-Modality Teachers
Tsai-Shien Chen, Aliaksandr Siarohin, Willi Menapace +8
The quality of the data and annotation upper-bounds the quality of a downstream model. While there exist large text corpora and image-text pairs, high-quality video-text data is mu…