He Zhu - RankMe

38 papers A* 8A 4B 4Misc 1Journal 15Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning from Demonstrations via Capability-Aware Goal Sampling. CoRR Yuanlin Duan, Yuning Wang, Wenjie Qiu, He Zhu
2025	J	`jnl`	Abstraction Refinement-Guided Program Synthesis for Robot Learning from Demonstrations. Proc. ACM Program. Lang. Guofeng Cui, Yuning Wang, Wensen Mao, Yuanlin Duan, He Zhu
2025	—	`conf`	Deductive Synthesis of Reinforcement Learning Agents for Infinite Horizon Tasks. CAV (4) Yuning Wang, He Zhu
2024	J	`jnl`	AutoFlow: Automated Workflow Generation for Large Language Model Agents. CoRR Zelong Li, Shuyuan Xu, Kai Mei, Wenyue Hua, Balaji Rama, Om Raheja, Hao Wang, He Zhu, Yongfeng Zhang
2024	J	`jnl`	Explain the Explainer: Interpreting Model-Agnostic Counterfactual Explanations of a Deep Reinforcement Learning Agent. IEEE Trans. Artif. Intell. Ziheng Chen, Fabrizio Silvestri, Gabriele Tolomei, Jia Wang, He Zhu, Hongshik Ahn
2024	A*	`conf`	Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning. NeurIPS Yuanlin Duan, Guofeng Cui, He Zhu
2024	J	`jnl`	Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning. CoRR Yuanlin Duan, Guofeng Cui, He Zhu
2024	J	`jnl`	Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents. CoRR Zelong Li, Wenyue Hua, Hao Wang, He Zhu, Yongfeng Zhang
2024	A*	`conf`	Learning World Models for Unconstrained Goal Navigation. NeurIPS Yuanlin Duan, Wensen Mao, He Zhu
2024	J	`jnl`	Learning World Models for Unconstrained Goal Navigation. CoRR Yuanlin Duan, Wensen Mao, He Zhu
2024	J	`jnl`	Reward-Guided Synthesis of Intelligent Agents with Control Structures. Proc. ACM Program. Lang. Guofeng Cui, Yuning Wang, Wenjie Qiu, He Zhu
2024	—	`conf`	Safe Exploration in Reinforcement Learning by Reachability Analysis over Learned Models. CAV (3) Yuning Wang, He Zhu
2023	A*	`conf`	Instructing Goal-Conditioned Reinforcement Learning Agents with Temporal Logic Objectives. NeurIPS Wenjie Qiu, Wensen Mao, He Zhu
2023	—	`conf`	Verification-guided Programmatic Controller Synthesis. TACAS (2) Yuning Wang, He Zhu
2022	—	`conf`	Defending Observation Attacks in Deep Reinforcement Learning via Detection and Denoising. ECML/PKDD (3) Zikang Xiong, Joe Eappen, He Zhu, Suresh Jagannathan
2022	J	`jnl`	Defending Observation Attacks in Deep Reinforcement Learning via Detection and Denoising. CoRR Zikang Xiong, Joe Eappen, He Zhu, Suresh Jagannathan
2022	A	`conf`	Graph Collaborative Reasoning. WSDM Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang
2022	A	`conf`	Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS). CIKM Hanxiong Chen, Yunqi Li, He Zhu, Yongfeng Zhang
2022	J	`jnl`	Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS). CoRR Hanxiong Chen, Yunqi Li, He Zhu, Yongfeng Zhang
2022	A*	`conf`	Programmatic Reinforcement Learning without Oracles. ICLR Wenjie Qiu, He Zhu
2022	A	`conf`	ReLAX: Reinforcement Learning Agent Explainer for Arbitrary Predictive Models. CIKM Ziheng Chen, Fabrizio Silvestri, Jia Wang, He Zhu, Hongshik Ahn, Gabriele Tolomei
2021	A*	`conf`	Differentiable Synthesis of Program Architectures. NeurIPS Guofeng Cui, He Zhu
2021	J	`jnl`	Graph Collaborative Reasoning. CoRR Hanxiong Chen, Yunqi Li, Shaoyun Shi, Shuchang Liu, He Zhu, Yongfeng Zhang
2021	J	`jnl`	ReLACE: Reinforcement Learning Agent for Counterfactual Explanations of Arbitrary Predictive Models. CoRR Ziheng Chen, Fabrizio Silvestri, Gabriele Tolomei, He Zhu, Jia Wang, Hongshik Ahn
2020	B	`conf`	Art: Abstraction Refinement-Guided Training for Provably Correct Neural Networks. FMCAD Xuankang Lin, He Zhu, Roopsha Samanta, Suresh Jagannathan
2020	J	`jnl`	Robustness to Adversarial Attacks in Learning-Enabled Controllers. CoRR Zikang Xiong, Joe Eappen, He Zhu, Suresh Jagannathan
2019	J	`jnl`	ART: Abstraction Refinement-Guided Training for Provably Correct Neural Networks. CoRR Xuankang Lin, He Zhu, Roopsha Samanta, Suresh Jagannathan
2019	J	`jnl`	An Inductive Synthesis Framework for Verifiable Reinforcement Learning. CoRR He Zhu, Zikang Xiong, Stephen Magill, Suresh Jagannathan
2019	A*	`conf`	An inductive synthesis framework for verifiable reinforcement learning. PLDI He Zhu, Zikang Xiong, Stephen Magill, Suresh Jagannathan
2018	A*	`conf`	A data-driven CHC solver. PLDI He Zhu, Stephen Magill, Suresh Jagannathan
2016	A*	`conf`	Automatically learning shape specifications. PLDI He Zhu, Gustavo Petri, Suresh Jagannathan
2016	—	`—`	Learning Program Specifications from Sample Runs He Zhu
2015	B	`conf`	Dependent Array Type Inference from Tests. VMCAI He Zhu, Aditya V. Nori, Suresh Jagannathan
2015	A	`conf`	Learning refinement types. ICFP He Zhu, Aditya V. Nori, Suresh Jagannathan
2015	—	`conf`	Poling: SMT Aided Linearizability Proofs. CAV (2) He Zhu, Gustavo Petri, Suresh Jagannathan
2013	B	`conf`	Compositional and Lightweight Dependent Type Inference for ML. VMCAI He Zhu, Suresh Jagannathan
2010	Misc	`conf`	Compositional Abstraction Refinement for Timed Systems. TASE Fei He, He Zhu, William N. N. Hung, Xiaoyu Song, Ming Gu
2009	B	`conf`	Data mining based decomposition for assume-guarantee reasoning. FMCAD He Zhu, Fei He, William N. N. Hung, Xiaoyu Song, Ming Gu