Bengong Yu

15 papers Journal 14Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Bridging the gaps: A hierarchical distillation approach to multimodal sentiment analysis with missing modalities. Inf. Fusion Zhonghao Xi, Bengong Yu, Shuping Zhao, Shanlin Yang
2026	J	`jnl`	Graph-Prototype distillation with prototype-Guided contrastive training for multimodal emotion recognition in conversations. Knowl. Based Syst. Bengong Yu, Jun Wang, Chenyue Li, Zhonghao Xi, Xianxian Zhao, Yue Li
2026	J	`jnl`	MS-SMF: A probabilistic-causal multi-layer framework for image-text matching. Inf. Process. Manag. Zhonghao Xi, Bengong Yu, Chenyue Li, Haoyu Wang, Shanlin Yang
2025	J	`jnl`	Cross-modal Interaction and Multi-view Misalignment Network for multimodal sarcasm detection. Neurocomputing Bengong Yu, Chenyue Li, Zhonghao Xi, Haoyu Wang, Shuping Zhao
2025	J	`jnl`	Dynamic position weighting aspect-focused graph convolutional network for aspect-based sentiment analysis. J. Supercomput. Bengong Yu, Chengwei Cao, Ying Yang
2025	J	`jnl`	Hierarchically trusted evidential fusion method with consistency learning for multimodal language understanding. Knowl. Based Syst. Ying Yang, Yan-Qiu Yang, Gang Ren, Bengong Yu
2025	J	`jnl`	Multi-grained feature gating fusion network for multimodal sentiment analysis. Knowl. Inf. Syst. Bengong Yu, Chenyue Li, Zhongyu Shi
2025	J	`jnl`	Multimodal aspect-based sentiment analysis based on a dual syntactic graph network and joint contrastive learning. Knowl. Inf. Syst. Bengong Yu, Yu Xing, Ying Yang, Chengwei Cao, Zhongyu Shi
2025	J	`jnl`	Multimodal sarcasm detection based on sentiment-clue inconsistency global detection fusion network. Expert Syst. Appl. Zhonghao Xi, Bengong Yu, Haoyu Wang
2024	J	`jnl`	Multifaceted and deep semantic alignment network for multimodal sarcasm detection. Knowl. Based Syst. Bengong Yu, Haoyu Wang, Zhonghao Xi
2024	J	`jnl`	TEMM: text-enhanced multi-interactive attention and multitask learning network for multimodal sentiment analysis. J. Supercomput. Bengong Yu, Zhongyu Shi
2024	J	`jnl`	Training with One2MultiSeq: CopyBART for social media keyphrase generation. J. Supercomput. Bengong Yu, Chunyang Gao, Shuwen Zhang
2023	J	`jnl`	A novel weight-oriented graph convolutional network for aspect-based sentiment analysis. J. Supercomput. Bengong Yu, Shuwen Zhang
2020	J	`jnl`	A comprehensive review of conditional random fields: variants, hybrids and applications. Artif. Intell. Rev. Bengong Yu, Zhaodi Fan
2018	—	`conf`	Question Classification Based on MAC-LSTM. DSC Bengong Yu, Qingtang Xu, Peihang Zhang

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.