| 2026 | AAAI | Beyond Step Pruning: Information Theory Based Step-level Optimization for Self-Refining Large Language Models. | Jinman Zhao, Erxue Min, Hui Wu, Ziheng Li, Zexu Sun, Hengyi Cai, Shuaiqiang Wang, Xu Chen, Gerald Penn |
| 2026 | ACL | Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification. | Yiju Guo, Tianyi Hu, Zexu Sun, Yankai Lin |
| 2026 | ACL | Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement. | Zexu Sun, Yongcheng Zeng, Erxue Min, Heyang Gao, Bokai Ji, Dugang Liu, Xing Tang, Xiuqiang He, Xu Chen |
| 2025 | ACL | KAPA: A Deliberative Agent Framework with Tree-Structured Knowledge Base for Multi-Domain User Intent Understanding. | Jiakai Tang, Shiqi Shen, Zhipeng Wang, Gong Zhi, Xueyang Feng, Zexu Sun, Haoran Tan, Xu Chen |
| 2025 | ICLR | Uncertainty and Influence aware Reward Model Refinement for Reinforcement Learning from Human Feedback. | Zexu Sun, Yiju Guo, Yankai Lin, Xu Chen, Qi Qi, Xing Tang, Xiuqiang He, Ji-Rong Wen |
| 2025 | ICML | Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency. | Zexu Sun, Qiyu Han, Hao Yang, Anpeng Wu, Minqin Zhu, Dugang Liu, Chen Ma, Yunpeng Weng, Xing Tang, Xiuqiang He |
| 2025 | ICML | Rethinking Causal Ranking: A Balanced Perspective on Uplift Model Evaluation. | Minqin Zhu, Zexu Sun, Ruoxuan Xiong, Anpeng Wu, Baohong Li, Caizhi Tang, Jun Zhou, Fei Wu, Kun Kuang |
| 2025 | KDD | Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing. | Zexu Sun, Qiyu Han, Minqin Zhu, Hao Gong, Dugang Liu, Chen Ma |
| 2024 | CIKM | OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction. | Yunpeng Weng, Xing Tang, Zhenhao Xu, Fuyuan Lyu, Dugang Liu, Zexu Sun, Xiuqiang He |
| 2024 | DASFAA | Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing. | Zexu Sun, Dugang Liu, Xing Tang, Yunpeng Weng, Xiuqiang He |
| 2024 | EMNLP | Controllable Preference Optimization: Toward Controllable Multi-Objective Alignment. | Yiju Guo, Ganqu Cui, Lifan Yuan, Ning Ding, Zexu Sun, Bowen Sun, Huimin Chen, Ruobing Xie, Jie Zhou, Yankai Lin, Zhiyuan Liu, Maosong Sun |
| 2024 | ICASSP | M | Zexu Sun, Xu Chen |
| 2024 | KDD | Policy-Based Bayesian Active Causal Discovery with Deep Reinforcement Learning. | Heyang Gao, Zexu Sun, Hao Yang, Xu Chen |
| 2024 | KDD | Rankability-enhanced Revenue Uplift Modeling Framework for Online Marketing. | Bowei He, Yunpeng Weng, Xing Tang, Ziqiang Cui, Zexu Sun, Liang Chen, Xiuqiang He, Chen Ma |
| 2024 | KDD | Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning. | Jiakai Tang, Sunhao Dai, Zexu Sun, Xu Chen, Jun Xu, Wenhui Yu, Lantao Hu, Peng Jiang, Han Li |
| 2024 | RecSys | End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling. | Zexu Sun, Hao Yang, Dugang Liu, Yunpeng Weng, Xing Tang, Xiuqiang He |
| 2023 | ICDM | Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization. | Zexu Sun, Bowei He, Ming Ma, Jiakai Tang, Yuchen Wang, Chen Ma, Dugang Liu |