Tao Tan

12 papers A* 2Misc 1Journal 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AgentCAT: An LLM Agent for Extracting and Analyzing Catalytic Reaction Data from Chemical Engineering Literature. CoRR Wei Yang, Zihao Liu, Tao Tan, Xiao Hu, Hong Xie, Lulu Li Xin Li, Jianyu Han, Defu Lian, Mao Ye
2026	J	`jnl`	Demystifying Design Choices of Reinforcement Fine-tuning: A Batched Contextual Bandit Learning Perspective. CoRR Hong Xie, Xiao Hu, Tao Tan, Haoran Gu, Xin Li, Jianyu Han, Defu Lian, Enhong Chen
2026	J	`jnl`	Model Specific Task Similarity for Vision Language Model Selection via Layer Conductance. CoRR Wei Yang, Hong Xie, Tao Tan, Xin Li, Defu Lian, Enhong Chen
2026	A*	`conf`	Multiple-play Stochastic Bandits with Prioritized Arm Capacity Sharing. AAAI Hong Xie, Haoran Gu, Yanying Huang, Tao Tan, Defu Lian
2026	J	`jnl`	Rethinking Reinforcement fine-tuning of LLMs: A Multi-armed Bandit Learning Perspective. CoRR Xiao Hu, Hong Xie, Tao Tan, Defu Lian, Jianyu Han
2025	Misc	`conf`	A 3D Attenuation Coefficient based Degradation Estimation for Real Non-Homogeneous Dehazing. ICASSP Hanyu Jiang, Zemin Ren, Tao Tan
2025	J	`jnl`	Multiple-play Stochastic Bandits with Prioritized Arm Capacity Sharing. CoRR Hong Xie, Haoran Gu, Yanying Huang, Tao Tan, Defu Lian
2024	J	`jnl`	A Meta-Learning Approach to Mitigating the Estimation Bias of Q-Learning. ACM Trans. Knowl. Discov. Data Tao Tan, Hong Xie, Xiaoyu Shi, Mingsheng Shang
2024	A*	`conf`	Adaptive Order Q-learning. IJCAI Tao Tan, Hong Xie, Defu Lian
2024	J	`jnl`	Adaptive moving average Q-learning. Knowl. Inf. Syst. Tao Tan, Hong Xie, Yunni Xia, Xiaoyu Shi, Mingsheng Shang
2024	J	`jnl`	Asynchronous SGD with stale gradient dynamic adjustment for deep learning training. Inf. Sci. Tao Tan, Hong Xie, Yunni Xia, Xiaoyu Shi, Mingsheng Shang
2024	J	`jnl`	Q-learning with heterogeneous update strategy. Inf. Sci. Tao Tan, Hong Xie, Liang Feng

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.

In 2025, he co-authored Assessing the Effectiveness of the Tigress Obfuscator Against MOPSA and BinaryNinja, published at CheckMATE. The paper evaluates the effectiveness of obfuscation techniques and their impact on source-level static analysis and binary-level decompilation.

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.