collaborators

5 papers

cs.CL2026

Can Large Language Models Identify Meaningful Touchpoints in Conversion Attribution?

Jinqi Wu, Sishuo Chen, Zhangming Chan +9

Touchpoint selection in conversion attribution, namely identifying meaningful touchpoints contributing to conversions, is essential for e-commerce recommendation and online adverti…

cs.LG2026

MAC: A Conversion Rate Prediction Benchmark Featuring Labels Under Multiple Attribution Mechanisms

Jinqi Wu, Sishuo Chen, Zhangming Chan +9

Multi-attribution learning (MAL), which enhances model performance by learning from conversion labels yielded by multiple attribution mechanisms, has emerged as a promising learnin…

cs.IR2026

EST: Towards Efficient Scaling Laws in Click-Through Rate Prediction via Unified Modeling

Mingyang Liu, Yong Bai, Zhangming Chan +5

Efficiently scaling industrial Click-Through Rate (CTR) prediction has recently attracted significant research attention. Existing approaches typically employ early aggregation of…

cs.LG2026

Modeling Cascaded Delay Feedback for Online Net Conversion Rate Prediction: Benchmark, Insights and Solutions

Mingxuan Luo, Guipeng Xv, Sishuo Chen +8

In industrial recommender systems, conversion rate (CVR) is widely used for traffic allocation, but it fails to fully reflect recommendation effectiveness because it ignores refund…

cs.LG2026

Delayed Feedback Modeling for Post-Click Gross Merchandise Volume Prediction: Benchmark, Insights and Approaches

Xinyu Li, Sishuo Chen, Guipeng Xv +7

The prediction objectives of online advertisement ranking models are evolving from probabilistic metrics like conversion rate (CVR) to numerical business metrics like post-click gr…