3 papers
cs.AI2026
FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation
Xinhang Yuan, Zexi Huang, Anjia Cao +6
Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates collaborative signals from user inte…
cs.CV2026
ISTASTrack: Bridging ANN and SNN via ISTA Adapter for RGB-Event Tracking
Siying Liu, Zikai Wang, Hanle Zheng +6
RGB-Event tracking has become a promising trend in visual object tracking to leverage the complementary strengths of both RGB images and dynamic spike events for improved performan…
cs.LG2026
PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation
Blake Gella, Wei Wu, Yuhao Yin +6
Recommender systems trained on user interaction data are susceptible to behavioral intensity imbalance--a systematic distortion arising from heterogeneous engagement patterns acros…