3 papers
cs.IR2024
LTP-MMF: Towards Long-term Provider Max-min Fairness Under Recommendation Feedback Loops
Chen Xu, Xiaopeng Ye, Jun Xu +3
Multi-stakeholder recommender systems involve various roles, such as users, and providers. Previous work pointed out that max-min fairness (MMF) is a better metric to support weak…
cs.IR2024
Generative Retrieval with Semantic Tree-Structured Item Identifiers via Contrastive Learning
Zihua Si, Zhongxiang Sun, Jiale Chen +7
The retrieval phase is a vital component in recommendation systems, requiring the model to be effective and efficient. Recently, generative retrieval has become an emerging paradig…
cs.IR2024
Unbiased Top-k Learning to Rank with Causal Likelihood Decomposition
Haiyuan Zhao, Jun Xu, Xiao Zhang +3
Unbiased learning to rank has been proposed to alleviate the biases in the search ranking, making it possible to train ranking models with user interaction data. In real applicatio…