Tan Minh Nguyen

34 papers A* 21A 2C 1Journal 9Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	C	`conf`	Argumentative LLMs for Legal Information Entailment. JURIX Charlie Lindsay, Francesca Toni, Tien Dat Nguyen, Tan Minh Nguyen, Trang Pham Ngoc Anh, Quang-Huy Chu, Hoang Nhat Nguyen, Le Minh Nguyen
2025	A*	`conf`	CAMEx: Curvature-aware Merging of Experts. ICLR Viet Dung Nguyen, Minh Nguyen Hoang, Luc Q. Nguyen, Rachel S. Y. Teo, Tan Minh Nguyen, Linh Duy Tran
2025	A*	`conf`	Demystifying the Token Dynamics of Deep Selective State Space Models. ICLR Thieu N. Vo, Duy-Tung Pham, Xin T. Tong, Tan Minh Nguyen
2025	A*	`conf`	Distance-Based Tree-Sliced Wasserstein Distance. ICLR Hoang V. Tran, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Thanh T. Chu, Tam Le, Tan Minh Nguyen
2025	A*	`conf`	Equivariant Neural Functional Networks for Transformers. ICLR Hoang V. Tran, Thieu Vo, An Nguyen The, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Tran, Duy-Tung Pham, Tan Minh Nguyen
2025	A*	`conf`	Equivariant Polynomial Functional Networks. ICML Thieu Vo, Hoang V. Tran, Tho Tran Huu, An Nguyen The, Thanh Tran, Minh-Khoi Nguyen-Nhat, Duy-Tung Pham, Tan Minh Nguyen
2025	A*	`conf`	MoLEx: Mixture of Layer Experts for Fine-tuning with Sparse Upcycling. ICLR Rachel S. Y. Teo, Tan Minh Nguyen
2025	J	`jnl`	Modeling Expert Interactions in Sparse Mixture of Experts via Graph Structures. CoRR Minh-Khoi Nguyen-Nhat, Rachel S. Y. Teo, Laziz U. Abdullaev, Maurice Mok, Viet-Hoang Tran, Tan Minh Nguyen
2025	A*	`conf`	Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models. ICML Ngoc-Quan Pham, Tuan Truong, Quyen Tran, Tan Minh Nguyen, Dinh Phung, Trung Le
2025	J	`jnl`	Resolving Memorization in Empirical Diffusion Model for Manifold Data in High-Dimensional Spaces. CoRR Yang Lyu, Yuchun Qian, Tan Minh Nguyen, Xin T. Tong
2025	J	`jnl`	Revisiting Kernel Attention with Correlated Gaussian Process Representation. CoRR Long Minh Bui, Tho Tran Huu, Duy Dinh, Tan Minh Nguyen, Trong Nghia Hoang
2025	A*	`conf`	Spherical Tree-Sliced Wasserstein Distance. ICLR Hoang V. Tran, Thanh T. Chu, Minh-Khoi Nguyen-Nhat, Huyen Trang Pham, Tam Le, Tan Minh Nguyen
2025	A*	`conf`	Tight Clusters Make Specialized Experts. ICLR Stefan K. Nielsen, Rachel S. Y. Teo, Laziz U. Abdullaev, Tan Minh Nguyen
2025	A*	`conf`	Transformer Meets Twicing: Harnessing Unattended Residual Information. ICLR Laziz U. Abdullaev, Tan Minh Nguyen
2025	A*	`conf`	Tree-Sliced Wasserstein Distance with Nonlinear Projection. ICML Thanh Tran, Hoang V. Tran, Thanh T. Chu, Huyen Trang Pham, Laurent El Ghaoui, Tam Le, Tan Minh Nguyen
2025	A*	`conf`	Tree-Sliced Wasserstein Distance: A Geometric Perspective. ICML Hoang V. Tran, Huyen Trang Pham, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh T. Chu, Tam Le, Tan Minh Nguyen
2024	J	`jnl`	A Clifford Algebraic Approach to E(n)-Equivariant High-order Graph Neural Networks. CoRR Hoang-Viet Tran, Thieu N. Vo, Tho Tran Huu, Tan Minh Nguyen
2024	A*	`conf`	Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders. ICLR Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho
2024	J	`jnl`	Demystifying the Token Dynamics of Deep Selective State Space Models. CoRR Thieu N. Vo, Tung D. Pham, Xin T. Tong, Tan Minh Nguyen
2024	J	`jnl`	Equivariant Neural Functional Networks for Transformers. CoRR Viet-Hoang Tran, Thieu N. Vo, An Nguyen The, Tho Tran Huu, Minh-Khoi Nguyen-Nhat, Thanh Tran, Duy-Tung Pham, Tan Minh Nguyen
2024	J	`jnl`	Equivariant Polynomial Functional Networks. CoRR Thieu N. Vo, Viet-Hoang Tran, Tho Tran Huu, An Nguyen The, Thanh Tran, Minh-Khoi Nguyen-Nhat, Duy-Tung Pham, Tan Minh Nguyen
2024	A	`conf`	From Coupled Oscillators to Graph Neural Networks: Reducing Over-smoothing via a Kuramoto Model-based Approach. AISTATS Tuan Nguyen, Hirotada Honda, Takashi Sano, Vinh Nguyen, Shugo Nakamura, Tan Minh Nguyen
2024	A*	`conf`	Monomial Matrix Group Equivariant Neural Functional Networks. NeurIPS Hoang V. Tran, Thieu N. Vo, Tho Huu, An Nguyen The, Tan Minh Nguyen
2024	J	`jnl`	Monomial Matrix Group Equivariant Neural Functional Networks. CoRR Hoang V. Tran, Thieu N. Vo, Tho H. Tran, An T. Nguyen, Tan Minh Nguyen
2024	A*	`conf`	Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model. ICML Hien Dang, Tho Tran Huu, Tan Minh Nguyen, Nhat Ho
2024	A*	`conf`	PIDformer: Transformer Meets Control Theory. ICML Tam Minh Nguyen, César A. Uribe, Tan Minh Nguyen, Richard G. Baraniuk
2024	A	`conf`	Revisiting Kernel Attention with Correlated Gaussian Process Representation. UAI Long Minh Bui, Tho Tran Huu, Duy Dinh, Tan Minh Nguyen, Trong Nghia Hoang
2023	A*	`conf`	A Primal-Dual Framework for Transformers and Neural Networks. ICLR Tan Minh Nguyen, Tam Minh Nguyen, Nhat Ho, Andrea L. Bertozzi, Richard G. Baraniuk, Stanley J. Osher
2023	A*	`conf`	Neural Collapse in Deep Linear Networks: From Balanced to Imbalanced Data. ICML Hien Dang, Tho Tran Huu, Stanley J. Osher, Hung Tran-The, Nhat Ho, Tan Minh Nguyen
2023	A*	`conf`	Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature. ICML Khang Nguyen, Nong Minh Hieu, Vinh Duc Nguyen, Nhat Ho, Stanley J. Osher, Tan Minh Nguyen
2022	A*	`conf`	GRAND++: Graph Neural Diffusion with A Source Term. ICLR Matthew Thorpe, Tan Minh Nguyen, Hedi Xia, Thomas Strohmer, Andrea L. Bertozzi, Stanley J. Osher, Bao Wang
2022	A*	`conf`	Improving Transformers with Probabilistic Attention Keys. ICML Tam Minh Nguyen, Tan Minh Nguyen, Dung D. Le, Duy Khuong Nguyen, Viet-Anh Tran, Richard G. Baraniuk, Nhat Ho, Stanley J. Osher
2022	—	`conf`	Momentum Transformer: Closing the Performance Gap Between Self-attention and Its Linearization. MSML Tan Minh Nguyen, Richard G. Baraniuk, Robert M. Kirby, Stanley J. Osher, Bao Wang
2022	J	`jnl`	Robustify Transformers with Robust Kernel Density Estimation. CoRR Xing Han, Tongzheng Ren, Tan Minh Nguyen, Khai Nguyen, Joydeep Ghosh, Nhat Ho

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.