AntProphet: an Intention Mining System behind Alipay's Intelligent Customer Service Bot. - Cen Chen 001; Xiaolu Zhang; Sheng Ju; Chilin Fu; Caizhi Tang; Jun Zhou 011; Xiaolong Li 005 (IJCAI, 2019)

AutoRec: A Comprehensive Platform for Building Effective and Explainable Recommender Models. - Qing Cui; Qitao Shi; Hao Qian 003; Caizhi Tang; Xixi Li; Yiming Zhao; Tao Jiang; Longfei Li; Jun Zhou 011 (ECML/PKDD (5), 2020)

Semi-Supervised Learning with Data Augmentation for Tabular Data. - Jun-Peng Fang; Caizhi Tang; Qing Cui; Feng Zhu 011; Longfei Li; Jun Zhou 011; Wei Zhu (CIKM, 2022)

Debiased Causal Tree: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. - Caizhi Tang; Huiyuan Wang; Xinyu Li; Qing Cui; Ya-Lin Zhang 001; Feng Zhu 011; Longfei Li; Jun Zhou 011; Linbo Jiang (NeurIPS, 2022)

Interpreting Model Predictions with Constrained Perturbation and Counterfactual Instances. - Jun-Peng Fang; Jun Zhou 011; Qing Cui; Caizhi Tang; Longfei Li (Int. J. Pattern Recognit. Artif. Intell., 2022)

Difference-in-Differences Meets Tree-based Methods: Heterogeneous Treatment Effects Estimation with Unmeasured Confounding. - Caizhi Tang; Huiyuan Wang; Xinyu Li; Qing Cui; Longfei Li; Jun Zhou 011 (ICML, 2023)

FAST: a Fused and Accurate Shrinkage Tree for Heterogeneous Treatment Effects Estimation. - Jia Gu; Caizhi Tang; Han Yan; Qing Cui; Longfei Li; Jun Zhou 011 (NeurIPS, 2023)

Alleviating Matching Bias in Marketing Recommendations. - Junpeng Fang; Qing Cui; Gongduo Zhang; Caizhi Tang; Lihong Gu; Longfei Li; Jinjie Gu; Jun Zhou 011; Fei Wu 001 (SIGIR, 2023)

DGBCT: A Scalable Distributed Gradient Boosting Causal Tree at Alipay. - Jun Zhou 011; Caizhi Tang; Qing Cui; Yi Ding 006; Longfei Li; Fei Wu 001 (WWW (Companion Volume), 2023)

GINT: A Generative Interpretability method via perturbation in the latent space. - Caizhi Tang; Qing Cui; Longfei Li; Jun Zhou 011 (Expert Syst. Appl., 2023)

Backdoor Adjustment via Group Adaptation for Debiased Coupon Recommendations. - Junpeng Fang; Gongduo Zhang; Qing Cui; Caizhi Tang; Lihong Gu; Longfei Li; Jinjie Gu; Jun Zhou 011 (AAAI, 2024)

Combining Incomplete Observational and Randomized Data for Heterogeneous Treatment Effects. - Dong Yao; Caizhi Tang; Qing Cui; Longfei Li (CIKM, 2024)

Domain Level Interpretability: Interpreting Black-box Model with Domain-specific Embedding. - Ya-Lin Zhang 001; Caizhi Tang; Lu Yu 006; Jun Zhou 011; Longfei Li; Qing Cui; Fangfang Fan; Linbo Jiang; Xiaosong Zhao (WSDM, 2024)

Invariant Graph Learning for Causal Effect Estimation. - Yongduo Sui; Caizhi Tang; Zhixuan Chu; Junfeng Fang; Yuan Gao 020; Qing Cui; Longfei Li; Jun Zhou 011; Xiang Wang 010 (WWW, 2024)