Yangru Huang - RankMe

22 papers A* 14Journal 6Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Beyond Single-Speed Reasoning: Coordinating Fast and Slow Dynamics for Efficient World Modeling. AAAI Hongwei Wang, Yangru Huang, Guangyao Chen, Xu Wang, Yi Jin
2026	A*	`conf`	Perceiving the Knowledge Boundary: Uncertainty-Guided Exploration and Imagination for World Models. AAAI Zhenxian Liu, Peixi Peng, Yangru Huang, Yonghong Tian
2026	J	`jnl`	S-GRec: Personalized Semantic-Aware Generative Recommendation with Asymmetric Advantage. CoRR Jie Jiang, Hongbo Tang, Wenjie Wu, Yangru Huang, Zhenmao Li, Qian Li, Changping Wang, Jun Zhang, Huan Yu
2026	J	`jnl`	Spend Search Where It Pays: Value-Guided Structured Sampling and Optimization for Generative Recommendation. CoRR Jie Jiang, Yangru Huang, Zeyu Wang, Changping Wang, Yuling Xiong, Jun Zhang, Huan Yu
2025	A*	`conf`	Tree of Prompts: Aligning Hierarchical Visual Prior for Continual Generalized Category Discovery. ACM Multimedia Yiqing Hao, Yangru Huang, Yi Jin, Tao Wang, Yidong Li, Yigang Cen
2025	A*	`conf`	When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Network. ICML Dong Xiao, Guangyao Chen, Peixi Peng, Yangru Huang, Yifan Zhao, Yongxing Dai, Yonghong Tian
2025	J	`jnl`	When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Network. CoRR Dong Xiao, Guangyao Chen, Peixi Peng, Yangru Huang, Yifan Zhao, Yongxing Dai, Yonghong Tian
2024	A*	`conf`	Adaptive Discovering and Merging for Incremental Novel Class Discovery. AAAI Guangyao Chen, Peixi Peng, Yangru Huang, Mengyue Geng, Yonghong Tian
2024	J	`jnl`	Adaptive Discovering and Merging for Incremental Novel Class Discovery. CoRR Guangyao Chen, Peixi Peng, Yangru Huang, Mengyue Geng, Yonghong Tian
2024	A*	`conf`	Seek Commonality but Preserve Differences: Dissected Dynamics Modeling for Multi-modal Visual RL. NeurIPS Yangru Huang, Peixi Peng, Yifan Zhao, Guangyao Chen, Yonghong Tian
2023	A*	`conf`	Hierarchical Adaptive Value Estimation for Multi-modal Visual Reinforcement Learning. NeurIPS Yangru Huang, Peixi Peng, Yifan Zhao, Haoran Xu, Mengyue Geng, Yonghong Tian
2023	—	`conf`	Reinforcement Learning-Based Consensus Reaching in Large-Scale Social Networks. ICONIP (8) Shijun Guo, Haoran Xu, Guangqiang Xie, Di Wen, Yangru Huang, Peixi Peng
2023	A*	`conf`	Simoun: Synergizing Interactive Motion-appearance Understanding for Vision-based Reinforcement Learning. ICCV Yangru Huang, Peixi Peng, Yifan Zhao, Yunpeng Zhai, Haoran Xu, Yonghong Tian
2023	A*	`conf`	Stabilizing Visual Reinforcement Learning via Asymmetric Interactive Cooperation. ICCV Yunpeng Zhai, Peixi Peng, Yifan Zhao, Yangru Huang, Yonghong Tian
2022	A*	`conf`	Spectrum Random Masking for Generalization in Image-based Reinforcement Learning. NeurIPS Yangru Huang, Peixi Peng, Yifan Zhao, Guangyao Chen, Yonghong Tian
2020	A*	`conf`	Discriminative Spatial Feature Learning for Person Re-Identification. ACM Multimedia Peixi Peng, Yonghong Tian, Yangru Huang, Xiangqian Wang, Huilong An
2020	A*	`conf`	Domain Adaptive Attention Learning for Unsupervised Person Re-Identification. AAAI Yangru Huang, Peixi Peng, Yi Jin, Yidong Li, Junliang Xing
2020	A*	`conf`	Masked Face Recognition with Generative Data Augmentation and Domain Constrained Ranking. ACM Multimedia Mengyue Geng, Peixi Peng, Yangru Huang, Yonghong Tian
2020	A*	`conf`	Masked Face Recognition with Latent Part Detection. ACM Multimedia Feifei Ding, Peixi Peng, Yangru Huang, Mengyue Geng, Yonghong Tian
2020	J	`jnl`	Towards Imbalanced Image Classification: A Generative Adversarial Network Ensemble Learning Method. IEEE Access Yangru Huang, Yi Jin, Yidong Li, Zhiping Lin
2019	J	`jnl`	Domain Adaptive Attention Model for Unsupervised Cross-Domain Person Re-Identification. CoRR Yangru Huang, Peixi Peng, Yi Jin, Junliang Xing, Congyan Lang, Songhe Feng
2019	—	`conf`	Unsupervised Person Re-identification Based on Clustering and Domain-Invariant Network. ICIG (3) Yangru Huang, Yi Jin, Peixi Peng, Congyan Lang, Yidong Li

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.