Zhanke Zhou - RankMe

45 papers A* 14B 1Journal 27Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Reference-guided Policy Optimization for Molecular Optimization via LLM Reasoning. CoRR Xuan Li, Zhanke Zhou, Zongze Li, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han
2026	J	`jnl`	RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models. CoRR Xiao Feng, Bo Han, Zhanke Zhou, Jiaqi Fan, Jiangchao Yao, Ka Ho Li, Dahai Yu, Michael Kwok-Po Ng
2025	J	`jnl`	AlphaApollo: Orchestrating Foundation Models and Professional Tools into a Self-Evolving System for Deep Agentic Reasoning. CoRR Zhanke Zhou, Chentao Cao, Xiao Feng, Xuan Li, Zongze Li, Xiangyu Lu, Jiangchao Yao, Weikai Huang, Linrui Xu, Tian Cheng, Guanyu Jiang, Yiming Zheng, Brando Miranda, Tongliang Liu, Sanmi Koyejo, Masashi Sugiyama, Bo Han
2025	J	`jnl`	Co-Reward: Self-supervised Reinforcement Learning for Large Language Model Reasoning via Contrastive Agreement. CoRR Zizhuo Zhang, Jianing Zhu, Xinmu Ge, Zihua Zhao, Zhanke Zhou, Xuan Li, Xiao Feng, Jiangchao Yao, Bo Han
2025	A*	`conf`	Eliciting Causal Abilities in Large Language Models for Reasoning Tasks. AAAI Yajing Wang, Zongwei Luo, Jingzhe Wang, Zhanke Zhou, Yongqiang Chen, Bo Han
2025	J	`jnl`	From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium. CoRR Xie Yi, Zhanke Zhou, Chentao Cao, Qiyu Niu, Tongliang Liu, Bo Han
2025	A*	`conf`	From Debate to Equilibrium: Belief‑Driven Multi‑Agent LLM Reasoning via Bayesian Nash Equilibrium. ICML Xie Yi, Zhanke Zhou, Chentao Cao, Qiyu Niu, Tongliang Liu, Bo Han
2025	A*	`conf`	From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? ICML Zhanke Zhou, Xiao Feng, Zhaocheng Zhu, Jiangchao Yao, Sanmi Koyejo, Bo Han
2025	J	`jnl`	From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? CoRR Zhanke Zhou, Xiao Feng, Zhaocheng Zhu, Jiangchao Yao, Sanmi Koyejo, Bo Han
2025	J	`jnl`	Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models. CoRR Zhanke Zhou, Zhaocheng Zhu, Xuan Li, Mikhail Galkin, Xiao Feng, Sanmi Koyejo, Jian Tang, Bo Han
2025	A*	`conf`	Noisy Test-Time Adaptation in Vision-Language Models. ICLR Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han
2025	J	`jnl`	Noisy Test-Time Adaptation in Vision-Language Models. CoRR Chentao Cao, Zhun Zhong, Zhanke Zhou, Tongliang Liu, Yang Liu, Kun Zhang, Bo Han
2025	B	`conf`	Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models. COLING Xinyu Pang, Ruixin Hong, Zhanke Zhou, Fangrui Lv, Xinwei Yang, Zhilong Liang, Bo Han, Changshui Zhang
2025	A*	`conf`	Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. ICLR Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q. Weinberger
2025	J	`jnl`	Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. CoRR Qizhou Wang, Jin Peng Zhou, Zhanke Zhou, Saebyeol Shin, Bo Han, Kilian Q. Weinberger
2025	A*	`conf`	SATBench: Benchmarking LLMs' Logical Reasoning via Automated Puzzle Generation from SAT Formulas. EMNLP Anjiang Wei, Yuheng Wu, Yingjia Wan, Tarun Suresh, Huanmi Tan, Zhanke Zhou, Sanmi Koyejo, Ke Wang, Alex Aiken
2025	J	`jnl`	SATBench: Benchmarking LLMs' Logical Reasoning via Automated Puzzle Generation from SAT Formulas. CoRR Anjiang Wei, Yuheng Wu, Yingjia Wan, Tarun Suresh, Huanmi Tan, Zhanke Zhou, Sanmi Koyejo, Ke Wang, Alex Aiken
2024	A*	`conf`	Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales? NeurIPS Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang, Bo Han
2024	J	`jnl`	Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales? CoRR Zhanke Zhou, Rong Tao, Jianing Zhu, Yiwen Luo, Zengmao Wang, Bo Han
2024	J	`jnl`	Eliciting Causal Abilities in Large Language Models for Reasoning Tasks. CoRR Yajing Wang, Zongwei Luo, Jingzhe Wang, Zhanke Zhou, Yongqiang Chen, Bo Han
2024	A*	`conf`	Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. ICML Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
2024	J	`jnl`	Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. CoRR Chentao Cao, Zhun Zhong, Zhanke Zhou, Yang Liu, Tongliang Liu, Bo Han
2024	A*	`conf`	Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. ICLR Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han
2024	J	`jnl`	Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. CoRR Zhanke Zhou, Yongqi Zhang, Jiangchao Yao, Quanming Yao, Bo Han
2024	A*	`conf`	Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. NeurIPS Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han
2024	J	`jnl`	Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. CoRR Hongduan Tian, Feng Liu, Zhanke Zhou, Tongliang Liu, Chengqi Zhang, Bo Han
2024	J	`jnl`	Model Inversion Attacks: A Survey of Approaches and Countermeasures. CoRR Zhanke Zhou, Jianing Zhu, Fengfei Yu, Xuan Li, Xiong Peng, Tongliang Liu, Bo Han
2024	A*	`conf`	Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel. ICLR Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han
2024	J	`jnl`	Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models. CoRR Xinyu Pang, Ruixin Hong, Zhanke Zhou, Fangrui Lv, Xinwei Yang, Zhilong Liang, Bo Han, Changshui Zhang
2024	J	`jnl`	Understanding Fairness Surrogate Functions in Algorithmic Fairness. Trans. Mach. Learn. Res. Wei Yao, Zhanke Zhou, Zhicong Li, Bo Han, Yong Liu
2023	A*	`conf`	AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning. KDD Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han
2023	A*	`conf`	Combating Bilateral Edge Noise for Robust Link Prediction. NeurIPS Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han
2023	J	`jnl`	Combating Bilateral Edge Noise for Robust Link Prediction. CoRR Zhanke Zhou, Jiangchao Yao, Jiaxu Liu, Xiawei Guo, Quanming Yao, Li He, Liang Wang, Bo Zheng, Bo Han
2023	J	`jnl`	DeepInception: Hypnotize Large Language Model to Be Jailbreaker. CoRR Xuan Li, Zhanke Zhou, Jianing Zhu, Jiangchao Yao, Tongliang Liu, Bo Han
2023	J	`jnl`	Long-Range Neural Atom Learning for Molecular Graphs. CoRR Xuan Li, Zhanke Zhou, Jiangchao Yao, Yu Rong, Lu Zhang, Bo Han
2023	A*	`conf`	On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. ICML Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han
2023	J	`jnl`	On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. CoRR Zhanke Zhou, Chenyu Zhou, Xuan Li, Jiangchao Yao, Quanming Yao, Bo Han
2023	J	`jnl`	Understanding Fairness Surrogate Functions in Algorithmic Fairness. CoRR Wei Yao, Zhanke Zhou, Zhicong Li, Bo Han, Yong Liu
2022	—	`conf`	Efficient Hyper-parameter Search for Knowledge Graph Embedding. ACL (1) Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li
2022	J	`jnl`	KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning. CoRR Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li
2022	J	`jnl`	Learning Adaptive Propagation for Knowledge Graph Reasoning. CoRR Yongqi Zhang, Zhanke Zhou, Quanming Yao, Xiaowen Chu, Bo Han
2021	J	`jnl`	AutoSF+: Towards Automatic Scoring Function Design for Knowledge Graph Embedding. CoRR Yongqi Zhang, Zhanke Zhou, Quanming Yao
2021	J	`jnl`	Enhancing WiFi Multiple Access Performance with Federated Deep Reinforcement Learning. CoRR Lyutianyang Zhang, Hao Yin, Zhanke Zhou, Sumit Roy, Yaping Sun
2020	—	`conf`	Accelerating Spectrum Sharing Algorithms for Cognitive Radio Transmitters in a Momentum Q-Learning Approach. SimuTools (1) Lianghui Zhu, Zhanke Zhou, Zhaochuan Peng, Xiaojun Hei
2020	—	`conf`	Enhancing WiFi Multiple Access Performance with Federated Deep Reinforcement Learning. VTC Fall Lyutianyang Zhang, Hao Yin, Zhanke Zhou, Sumit Roy, Yaping Sun

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.