collaborators

5 papers

cs.IR2026

Bi-Level Optimization for Generative Recommendation: Bridging Tokenization and Generation

Yimeng Bai, Chang Liu, Yang Zhang +5

Generative recommendation is emerging as a transformative paradigm by directly generating recommended items, rather than relying on matching. Building such a system typically invol…

cs.IR2026

SODA: Semantic-Oriented Distributional Alignment for Generative Recommendation

Ziqi Xue, Dingxian Wang, Yimeng Bai +7

Generative recommendation has emerged as a scalable alternative to traditional retrieve-and-rank pipelines by operating in a compact token space. However, existing methods mainly r…

cs.IR2026

UniGRec: Unified Generative Recommendation with Soft Identifiers for End-to-End Optimization

Jialei Li, Yang Zhang, Yimeng Bai +7

Generative recommendation has recently emerged as a transformative paradigm that directly generates target items, surpassing traditional cascaded approaches. It typically involves…

cs.LG2025

Delayed Feedback Modeling with Influence Functions

Chenlu Ding, Jiancan Wu, Yancheng Yuan +5

In online advertising under the cost-per-conversion (CPA) model, accurate conversion rate (CVR) prediction is crucial. A major challenge is delayed feedback, where conversions may…

cs.IR2025

Graph Neural Network for Product Recommendation on the Amazon Co-purchase Graph

Mengyang Cao, Frank F. Yang, Yi Jin +1

Identifying relevant information among massive volumes of data is a challenge for modern recommendation systems. Graph Neural Networks (GNNs) have demonstrated significant potentia…