Zexu Sun

According to our database, Zexu Sun authored at least 31 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

AgentSkiller: Scaling Generalist Agent Intelligence through Semantically Integrated Cross-Domain Data Synthesis.

Zexu Sun, Bokai Ji, Hengyi Cai, Shuaiqiang Wang, Lei Wang, Guangxia Li, Xu Chen

CoRR, February, 2026

Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification.

Yiju Guo, Tianyi Hu, Zexu Sun, Yankai Lin

CoRR, January, 2026

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

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Cog-Rethinker: Hierarchical Metacognitive Reinforcement Learning for LLM Reasoning.

Zexu Sun, Yongcheng Zeng, Erxue Min, Heyang Gao, Bokai Ji, Xu Chen

CoRR, October, 2025

Solving the Granularity Mismatch: Hierarchical Preference Learning for Long-Horizon LLM Agents.

Heyang Gao, Zexu Sun, Erxue Min, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Xu Chen

CoRR, October, 2025

CurES: From Gradient Analysis to Efficient Curriculum Learning for Reasoning LLMs.

Yongcheng Zeng, Zexu Sun, Bokai Ji, Erxue Min, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Haifeng Zhang, Xu Chen, Jun Wang

CoRR, October, 2025

Prompt and Parameter Co-Optimization for Large Language Models.

Xiaohe Bo, Rui Li, Zexu Sun, Quanyu Dai, Zeyu Zhang, Zihang Tian, Xu Chen, Zhenhua Dong

CoRR, September, 2025

Staying in the Sweet Spot: Responsive Reasoning Evolution via Capability-Adaptive Hint Scaffolding.

Ziheng Li, Zexu Sun, Jinman Zhao, Erxue Min, Yongcheng Zeng, Hui Wu, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Xu Chen, Zhi-Hong Deng

CoRR, September, 2025

Learning to Focus: Causal Attention Distillation via Gradient-Guided Token Pruning.

Yiju Guo, Wenkai Yang, Zexu Sun, Ning Ding, Zhiyuan Liu, Yankai Lin

CoRR, June, 2025

What, How, Where, and How Well? A Survey on Test-Time Scaling in Large Language Models.

Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, Lei Wang, Weixu Zhang, Zhihan Guo, Yufei Wang, Irwin King, Xue Liu, Chen Ma

CoRR, March, 2025

Sequential Causal Effect Estimation by Jointly Modeling the Unmeasured Confounders and Instrumental Variables.

Zexu Sun, Bowei He, Shiqi Shen, Zhipeng Wang, Zhi Gong, Chen Ma, Qi Qi, Xu Chen

IEEE Trans. Knowl. Data Eng., February, 2025

ARIES: Stimulating Self-Refinement of Large Language Models by Iterative Preference Optimization.

Yongcheng Zeng, Xinyu Cui, Xuanfa Jin, Guoqing Liu, Zexu Sun, Quan He, Dong Li, Ning Yang, Jianye Hao, Haifeng Zhang, Jun Wang

CoRR, February, 2025

Counterfactual Multi-player Bandits for Explainable Recommendation Diversification.

Yansen Zhang, Bowei He, Xiaokun Zhang, Haolun Wu, Zexu Sun, Chen Ma

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2025

Robust Uplift Modeling with Large-Scale Contexts for Real-time Marketing.

Zexu Sun, Qiyu Han, Minqin Zhu, Hao Gong, Dugang Liu, Chen Ma

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

Proceedings of the Forty-second International Conference on Machine Learning, 2025

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

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024

Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression.

Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Xiangwei Chen, Zexu Sun, Fei Wu, Kun Zhang

CoRR, 2024

Benchmarking for Deep Uplift Modeling in Online Marketing.

Dugang Liu, Xing Tang, Yang Qiao, Miao Liu, Zexu Sun, Xiuqiang He, Zhong Ming

CoRR, 2024

Revisiting Counterfactual Regression through the Lens of Gromov-Wasserstein Information Bottleneck.

Hao Yang, Zexu Sun, Hongteng Xu, Xu Chen

CoRR, 2024

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

Proceedings of the 18th ACM Conference on Recommender Systems, 2024

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

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

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

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Policy-Based Bayesian Active Causal Discovery with Deep Reinforcement Learning.

Heyang Gao, Zexu Sun, Hao Yang, Xu Chen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

M³TN: Multi-Gate Mixture-of-Experts Based Multi-Valued Treatment Network for Uplift Modeling.

Zexu Sun, Xu Chen

Proceedings of the IEEE International Conference on Acoustics, 2024

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

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Towards Effective and Efficient Multi-valued Treatment Uplift Modeling in Online Marketing.

Zexu Sun, Dugang Liu, Xing Tang, Yunpeng Weng, Xiuqiang He

Proceedings of the Database Systems for Advanced Applications, 2024

OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction.

Yunpeng Weng, Xing Tang, Zhenhao Xu, Fuyuan Lyu, Dugang Liu, Zexu Sun, Xiuqiang He

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Offline Imitation Learning with Variational Counterfactual Reasoning.

Zexu Sun, Bowei He, Jinxin Liu, Xu Chen, Chen Ma, Shuai Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization.

Zexu Sun, Bowei He, Ming Ma, Jiakai Tang, Yuchen Wang, Chen Ma, Dugang Liu

Proceedings of the IEEE International Conference on Data Mining, 2023