8 papers
Budgeted Active Experimentation for Treatment Effect Estimation from Observational and Randomized Data
Jiacan Gao, Xinyan Su, Mingyuan Ma +7
Estimating heterogeneous treatment effects is central to data-driven decision-making, yet industrial applications often face a fundamental tension between limited randomized contro…
Orthogonal Uplift Learning with Permutation-Invariant Representations for Combinatorial Treatments
Xinyan Su, Jiacan Gao, Mingyuan Ma +6
We study uplift estimation for combinatorial treatments. Uplift measures the pure incremental causal effect of an intervention (e.g., sending a coupon or a marketing message) on us…
CroPS: Improving Dense Retrieval with Cross-Perspective Positive Samples in Short-Video Search
Ao Xie, Jiahui Chen, Quanzhi Zhu +4
Dense retrieval has become a foundational paradigm in modern search systems, especially on short-video platforms. However, most industrial systems adopt a self-reinforcing training…
GReF: A Unified Generative Framework for Efficient Reranking via Ordered Multi-token Prediction
Zhijie Lin, Zhuofeng Li, Chenglei Dai +5
In a multi-stage recommendation system, reranking plays a crucial role in modeling intra-list correlations among items. A key challenge lies in exploring optimal sequences within t…
Personalized Query Auto-Completion for Long and Short-Term Interests with Adaptive Detoxification Generation
Zhibo Wang, Xiaoze Jiang, Zhiheng Qin +2
Query auto-completion (QAC) plays a crucial role in modern search systems. However, in real-world applications, there are two pressing challenges that still need to be addressed. F…
Unconstrained Monotonic Calibration of Predictions in Deep Ranking Systems
Yimeng Bai, Shunyu Zhang, Yang Zhang +5
Ranking models primarily focus on modeling the relative order of predictions while often neglecting the significance of the accuracy of their absolute values. However, accurate abs…