Fan Liu

16 papers A* 4Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bag of Tricks for Inference-time Computation of LLM Reasoning. CoRR Fan Liu, Wenshuo Chao, Naiqiang Tan, Hao Liu
2025	—	`conf`	Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network. ECML/PKDD (2) Fan Liu, Siqi Lai, Yansong Ning, Hao Liu
2025	J	`jnl`	Foundation Models for Scientific Discovery: From Paradigm Enhancement to Paradigm Transition. CoRR Fan Liu, Jindong Han, Tengfei Lyu, Weijia Zhang, Zhe-Rui Yang, Lu Dai, Cancheng Liu, Hao Liu
2025	J	`jnl`	Large Language Model Powered Intelligent Urban Agents: Concepts, Capabilities, and Applications. CoRR Jindong Han, Yansong Ning, Zirui Yuan, Hang Ni, Fan Liu, Tengfei Lyu, Hao Liu
2025	A*	`conf`	Subgraph Federated Unlearning. WWW Fan Liu, Hao Liu
2025	A*	`conf`	TP-RAG: Benchmarking Retrieval-Augmented Large Language Model Agents for Spatiotemporal-Aware Travel Planning. EMNLP Hang Ni, Fan Liu, Xinyu Ma, Lixin Su, Shuaiqiang Wang, Dawei Yin, Hui Xiong, Hao Liu
2025	J	`jnl`	TP-RAG: Benchmarking Retrieval-Augmented Large Language Model Agents for Spatiotemporal-Aware Travel Planning. CoRR Hang Ni, Fan Liu, Xinyu Ma, Lixin Su, Shuaiqiang Wang, Dawei Yin, Hui Xiong, Hao Liu
2024	J	`jnl`	Adversarial Tuning: Defending Against Jailbreak Attacks for LLMs. CoRR Fan Liu, Zhao Xu, Hao Liu
2024	J	`jnl`	Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs. CoRR Zhao Xu, Fan Liu, Hao Liu
2024	J	`jnl`	JAILJUDGE: A Comprehensive Jailbreak Judge Benchmark with Multi-Agent Enhanced Explanation Evaluation Framework. CoRR Fan Liu, Yue Feng, Zhao Xu, Lixin Su, Xinyu Ma, Dawei Yin, Hao Liu
2024	J	`jnl`	Spatial-Temporal Mixture-of-Graph-Experts for Multi-Type Crime Prediction. CoRR Ziyang Wu, Fan Liu, Jindong Han, Yuxuan Liang, Hao Liu
2023	J	`jnl`	Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network. CoRR Fan Liu, Siqi Lai, Yansong Ning, Hao Liu
2023	A*	`conf`	Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training. KDD Fan Liu, Weijia Zhang, Hao Liu
2023	J	`jnl`	Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training. CoRR Fan Liu, Weijia Zhang, Hao Liu
2022	A*	`conf`	Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models. NeurIPS Fan Liu, Hao Liu, Wenzhao Jiang
2022	J	`jnl`	Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models. CoRR Fan Liu, Hao Liu, Wenzhao Jiang

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.