00Research archive Publications 2026 IdeaTrail: Full-Process Agent Trajectories for Scientific Ideation 2026 Hengquan Guo ArXiv preprint BLOCK: An Open-Source Bi-Stage MLLM Character-to-Skin Pipeline for Minecraft 2026 Hengquan Guo ArXiv preprint GRB: A Generative Reinforcement Bidding Framework for Multi-Channel Online Advertising 2026 Hongchang Wu*, Weitong Ou*, Hengquan Guo*, Zixin Shao*, Hongyan Xue, Junwei Pan, Shudong Huang, Zhangbin Zhu, Xin Liu, Nianhua Xie, Lei Xiao, Haijie Gu * equal contribution ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026, Applied Data Science Track) Towards Temporal Interest Modeling in Recommendation via Reinforcement Learning 2026 Hengquan Guo, Haobo Zhang, Junwei Pan, Wentao Ning, Xiaotian Li, Zhixiang Feng, Shoujun Liu, Gong Chen, Shudong Huang, Haijie Gu, Xin Liu In Submission SABO: Safe and Aggressive Bayesian Optimization for Automatic Legged Locomotion Controller Tuning 2026 Haobo Zhang, Zhiyong Yu, Hengquan Guo, Yuning Jiang, Xin Liu, Yuanming Shi Submitted to ICRA Towards Safe and Optimal Online Bidding: A Modular Look-ahead Lyapunov Framework 2026 Hengquan Guo, Haobo Zhang, Junwei Pan, Shudong Huang, Nianhua Xie, Lei Xiao, Haijie Gu, Jie Jiang, Xin Liu International Conference on Learning Representations (ICLR 2026) 2025 Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization 2025 Xiyue Peng, Hengquan Guo, Jiawei Zhang, Dongqing Zou, Ziyu Shao, Honghao Wei, Xin Liu Advances in Neural Information Processing Systems (NeurIPS 2025) No Regret Reinforcement Learning Algorithms for Online Scheduling with Multi-Stage Tasks 2025 Yongxin Xu, Hengquan Guo, Ziyu Shao, Xin Liu International Joint Conference on Artificial Intelligence (IJCAI 2025) On the Power of Optimism in Constrained Online Convex Optimization 2025 Haobo Zhang, Hengquan Guo, Xin Liu International Joint Conference on Artificial Intelligence (IJCAI 2025) Safe Learning in Stochastic Continuum-Armed Bandit With Constraints and Its Application to Network Resource Management 2025 Hengquan Guo, Qi Zhu, Xin Liu IEEE/ACM Transactions on Networking Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints 2025 Hengquan Guo, Lingkai Zu, Xin Liu International Conference on Machine Learning (ICML 2025) On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime 2025 Hengquan Guo, Xin Liu International Conference on Learning Representations (ICLR 2025) 2024 QueueFlower: Orchestrating Microservice Workflows via Dynamic Queue Balancing 2024 Hongchen Cao, Xinrui Liu, Hengquan Guo, Jingzhu He, Xin Liu IEEE International Conference on Web Services (ICWS 2024) Stochastic Constrained Contextual Bandits via Lyapunov Optimization Based Estimation to Decision Framework 2024 Hengquan Guo, Xin Liu Annual Conference on Learning Theory (COLT 2024, Oral) Learning to Schedule Online Tasks with Bandit Feedback 2024 Yongxin Xu, Shangshang Wang, Hengquan Guo, Xin Liu, Ziyu Shao International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024) 2023 POBO: Safe and Optimal Resource Management for Cloud Microservices 2023 Hengquan Guo, Hongchen Cao, Jingzhu He, Xin Liu, Yuanming Shi Performance Evaluation 162 Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-Armed Bandit with Constraints 2023 Hengquan Guo, Qi Zhu, Xin Liu Learning for Dynamics and Control Conference (L4DC 2023) 2022 Online Convex Optimization with Hard Constraints: Towards the Best of Two Worlds and Beyond 2022 Hengquan Guo, Xin Liu, Honghao Wei, Lei Ying Advances in Neural Information Processing Systems (NeurIPS 2022)
BLOCK: An Open-Source Bi-Stage MLLM Character-to-Skin Pipeline for Minecraft 2026 Hengquan Guo ArXiv preprint
GRB: A Generative Reinforcement Bidding Framework for Multi-Channel Online Advertising 2026 Hongchang Wu*, Weitong Ou*, Hengquan Guo*, Zixin Shao*, Hongyan Xue, Junwei Pan, Shudong Huang, Zhangbin Zhu, Xin Liu, Nianhua Xie, Lei Xiao, Haijie Gu * equal contribution ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026, Applied Data Science Track)
Towards Temporal Interest Modeling in Recommendation via Reinforcement Learning 2026 Hengquan Guo, Haobo Zhang, Junwei Pan, Wentao Ning, Xiaotian Li, Zhixiang Feng, Shoujun Liu, Gong Chen, Shudong Huang, Haijie Gu, Xin Liu In Submission
SABO: Safe and Aggressive Bayesian Optimization for Automatic Legged Locomotion Controller Tuning 2026 Haobo Zhang, Zhiyong Yu, Hengquan Guo, Yuning Jiang, Xin Liu, Yuanming Shi Submitted to ICRA
Towards Safe and Optimal Online Bidding: A Modular Look-ahead Lyapunov Framework 2026 Hengquan Guo, Haobo Zhang, Junwei Pan, Shudong Huang, Nianhua Xie, Lei Xiao, Haijie Gu, Jie Jiang, Xin Liu International Conference on Learning Representations (ICLR 2026)
Enhancing Safety in Reinforcement Learning with Human Feedback via Rectified Policy Optimization 2025 Xiyue Peng, Hengquan Guo, Jiawei Zhang, Dongqing Zou, Ziyu Shao, Honghao Wei, Xin Liu Advances in Neural Information Processing Systems (NeurIPS 2025)
No Regret Reinforcement Learning Algorithms for Online Scheduling with Multi-Stage Tasks 2025 Yongxin Xu, Hengquan Guo, Ziyu Shao, Xin Liu International Joint Conference on Artificial Intelligence (IJCAI 2025)
On the Power of Optimism in Constrained Online Convex Optimization 2025 Haobo Zhang, Hengquan Guo, Xin Liu International Joint Conference on Artificial Intelligence (IJCAI 2025)
Safe Learning in Stochastic Continuum-Armed Bandit With Constraints and Its Application to Network Resource Management 2025 Hengquan Guo, Qi Zhu, Xin Liu IEEE/ACM Transactions on Networking
Triple-Optimistic Learning for Stochastic Contextual Bandits with General Constraints 2025 Hengquan Guo, Lingkai Zu, Xin Liu International Conference on Machine Learning (ICML 2025)
On Stochastic Contextual Bandits with Knapsacks in Small Budget Regime 2025 Hengquan Guo, Xin Liu International Conference on Learning Representations (ICLR 2025)
QueueFlower: Orchestrating Microservice Workflows via Dynamic Queue Balancing 2024 Hongchen Cao, Xinrui Liu, Hengquan Guo, Jingzhu He, Xin Liu IEEE International Conference on Web Services (ICWS 2024)
Stochastic Constrained Contextual Bandits via Lyapunov Optimization Based Estimation to Decision Framework 2024 Hengquan Guo, Xin Liu Annual Conference on Learning Theory (COLT 2024, Oral)
Learning to Schedule Online Tasks with Bandit Feedback 2024 Yongxin Xu, Shangshang Wang, Hengquan Guo, Xin Liu, Ziyu Shao International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2024)
POBO: Safe and Optimal Resource Management for Cloud Microservices 2023 Hengquan Guo, Hongchen Cao, Jingzhu He, Xin Liu, Yuanming Shi Performance Evaluation 162
Rectified Pessimistic-Optimistic Learning for Stochastic Continuum-Armed Bandit with Constraints 2023 Hengquan Guo, Qi Zhu, Xin Liu Learning for Dynamics and Control Conference (L4DC 2023)
Online Convex Optimization with Hard Constraints: Towards the Best of Two Worlds and Beyond 2022 Hengquan Guo, Xin Liu, Honghao Wei, Lei Ying Advances in Neural Information Processing Systems (NeurIPS 2022)