Yang Zhao - RankMe

14 papers Journal 10Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration. CoRR Yang Zhao, Yangou Ouyang, Xiao Ding, Hepeng Wang, Bibo Cai, Kai Xiong, Jinglong Gao, Zhouhao Sun, Li Du, Bing Qin, Ting Liu
2026	J	`jnl`	MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization. CoRR Yang Zhao, Hepeng Wang, Xiao Ding, Yangou Ouyang, Bibo Cai, Kai Xiong, Jinglong Gao, Zhouhao Sun, Li Du, Bing Qin, Ting Liu
2025	—	`conf`	Analyzing the Rapid Generalization of SFT via the Perspective of Attention Head Activation Patterns. ACL (1) Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin
2025	J	`jnl`	Benchmarking and Pushing the Multi-Bias Elimination Boundary of LLMs via Causal Effect Estimation-guided Debiasing. CoRR Zhouhao Sun, Zhiyuan Kan, Xiao Ding, Li Du, Yang Zhao, Bing Qin, Ting Liu
2025	—	`conf`	Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection. ACL (1) Yang Zhao, Li Du, Xiao Ding, Yangou Ouyang, Hepeng Wang, Kai Xiong, Jinglong Gao, Zhouhao Sun, Dongliang Xu, Qing Yang, Dongchen Li, Bing Qin, Ting Liu
2025	J	`jnl`	Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection. CoRR Yang Zhao, Li Du, Xiao Ding, Yangou Ouyang, Hepeng Wang, Kai Xiong, Jinglong Gao, Zhouhao Sun, Dongliang Xu, Qing Yang, Dongchen Li, Bing Qin, Ting Liu
2025	J	`jnl`	Information Gain-Guided Causal Intervention for Autonomous Debiasing Large Language Models. CoRR Zhouhao Sun, Xiao Ding, Li Du, Yunpeng Xu, Yixuan Ma, Yang Zhao, Bing Qin, Ting Liu
2025	J	`jnl`	Think straight or think again? Continual joint learning of deduction, abduction and induction. Neural Networks Kai Xiong, Xiao Ding, Yixin Cao, Yang Zhao, Ting Liu, Bing Qin
2025	J	`jnl`	UFO-RL: Uncertainty-Focused Optimization for Efficient Reinforcement Learning Data Selection. CoRR Yang Zhao, Kai Xiong, Xiao Ding, Li Du, YangouOuyang, Zhouhao Sun, Jiannan Guan, Wenbin Zhang, Bin Liu, Dong Hu, Bing Qin, Ting Liu
2024	—	`conf`	Causal-Guided Active Learning for Debiasing Large Language Models. ACL (1) Zhouhao Sun, Li Du, Xiao Ding, Yixuan Ma, Yang Zhao, Kaitao Qiu, Ting Liu, Bing Qin
2024	J	`jnl`	Causal-Guided Active Learning for Debiasing Large Language Models. CoRR Li Du, Zhouhao Sun, Xiao Ding, Yixuan Ma, Yang Zhao, Kaitao Qiu, Ting Liu, Bing Qin
2024	—	`conf`	Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning. ACL (Findings) Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Zhouhao Sun, Shi Jun, Ting Liu, Bing Qin
2024	J	`jnl`	Deciphering the lmpact of Pretraining Data on Large Language Models through Machine Unlearning. CoRR Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Zhouhao Sun, Jun Shi, Ting Liu, Bing Qin
2024	J	`jnl`	Supervised Fine-Tuning: An Activation Pattern Optimization Process for Attention Heads. CoRR Yang Zhao, Li Du, Xiao Ding, Kai Xiong, Ting Liu, Bing Qin

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.