Fanshuang Kong

16 papers A* 7Journal 7Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	inversedMixup: Data Augmentation via Inverting Mixed Embeddings. CoRR Fanshuang Kong, Richong Zhang, Qiyu Sun, Zhijie Nie, Ting Deng, Chunming Hu
2025	J	`jnl`	Incomplete graph learning via data and representation-level interaction. Knowl. Based Syst. Dezhi Liu, Richong Zhang, Junfan Chen, Fanshuang Kong, Jaein Kim
2025	—	`conf`	LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning. KDD (1) Fanshuang Kong, Richong Zhang, Ziqiao Wang
2025	J	`jnl`	Lost-in-the-Middle in Long-Text Generation: Synthetic Dataset, Evaluation Framework, and Mitigation. CoRR Junhao Zhang, Richong Zhang, Fanshuang Kong, Ziyang Miao, Yanhan Ye, Yaowei Zheng
2025	A*	`conf`	Preserving Label Correlation for Multi-label Text Classification by Prototypical Regularizations. WWW Fanshuang Kong, Richong Zhang, Xiaohui Guo, Junfan Chen, Ziqiao Wang
2024	J	`jnl`	Activated Parameter Locating via Causal Intervention for Model Merging. CoRR Fanshuang Kong, Richong Zhang, Ziqiao Wang
2024	J	`jnl`	LH-Mix: Local Hierarchy Correlation Guided Mixup over Hierarchical Prompt Tuning. CoRR Fanshuang Kong, Richong Zhang, Ziqiao Wang
2024	A*	`conf`	On Unsupervised Domain Adaptation: Pseudo Label Guided Mixup for Adversarial Prompt Tuning. AAAI Fanshuang Kong, Richong Zhang, Ziqiao Wang, Yongyi Mao
2024	J	`jnl`	Rethink the Evaluation Protocol of Model Merging on Classification Task. CoRR Fanshuang Kong, Richong Zhang, Zhijie Nie, Ziqiao Wang
2023	A*	`conf`	Word Sense Disambiguation by Refining Target Word Embedding. WWW Xuefeng Zhang, Richong Zhang, Xiaoyang Li, Fanshuang Kong, Junfan Chen, Samuel Mensah, Yongyi Mao
2022	A*	`conf`	DropMix: A Textual Data Augmentation Combining Dropout with Mixup. EMNLP Fanshuang Kong, Richong Zhang, Xiaohui Guo, Samuel Mensah, Yongyi Mao
2021	—	`conf`	Hypernym Discovery via a Recurrent Mapping Model. ACL/IJCNLP (Findings) Yuhang Bai, Richong Zhang, Fanshuang Kong, Junfan Chen, Yongyi Mao
2020	J	`jnl`	Pairwise Link Prediction Model for Out of Vocabulary Knowledge Base Entities. ACM Trans. Inf. Syst. Richong Zhang, Samuel Mensah, Fanshuang Kong, Zhiyuan Hu, Yongyi Mao, Xudong Liu
2019	A*	`conf`	A Neural Bag-of-Words Modelling Framework for Link Prediction in Knowledge Bases with Sparse Connectivity. WWW Fanshuang Kong, Richong Zhang, Hongyu Guo, Samuel Mensah, Zhiyuan Hu, Yongyi Mao
2019	A*	`conf`	LENA: Locality-Expanded Neural Embedding for Knowledge Base Completion. AAAI Fanshuang Kong, Richong Zhang, Yongyi Mao, Ting Deng
2018	A*	`conf`	Embedding of Hierarchically Typed Knowledge Bases. AAAI Richong Zhang, Fanshuang Kong, Chenyue Wang, Yongyi Mao

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.