25 citations · 132 across the 68 of their papers we have counts for
70 papers
A one-dimensional coherent domain with non-Prüfer integral closure
Viet-Hoang Tran, Thieu N. Vo, Tan M. Nguyen
In a question recorded in 1978, Vasconcelos asked whether the integral closure of a one-dimensional coherent local domain in its fraction field is Prüfer. We construct such a domai…
Locality of Bernoulli Site Percolation on Transitive Graphs
Tho Tran, Tan M. Nguyen
We prove locality of the critical probability for Bernoulli site percolation on infinite, connected, locally finite, vertex-transitive graphs, under the usual assumption that the c…
Bouvier's Conjecture and Dimension Sequences of Unique Factorization Domains
Viet-Hoang Tran, Thieu N. Vo, Tan M. Nguyen
We prove Bouvier's conjecture. More generally, an integer sequence with is realized by a unique factorization domain (UFD) with $\dim R[X_1,\ldo…
Topological Steering
Benoît Guérand, Tan Minh Nguyen
With the rapid rise of large language models (LLMs), controlling undesirable model behaviors has become increasingly important. Existing behavioral control methods typically interv…
The Erdős-Hajnal Property for the six-vertex Graph with Edge Set
Viet-Hoang Tran, Tan M. Nguyen
We prove that the six-vertex graph with edge set has the Erdős-Hajnal property. The proof adapts the iterative-sparsification method of Nguyen, Scott, an…
Polynomial extensions do not preserve the strong finite type property
Viet-Hoang Tran, Phan Thanh Toan, Thieu N. Vo +1
Arnold introduced the strong finite type (SFT) property in 1973 while studying the dimension of power series rings. For several classes of rings, polynomial extension is known to p…
The Noetherian Case of Bayart's Power-Series Question
Viet-Hoang Tran, Dung V. Nguyen, Quang X. Nguyen +2
Let be a commutative Noetherian ring. We prove that if the one-variable formal power-series ring is a unique factorization domain, then so is the two-variable formal p…
MuonSSM: Orthogonalizing State Space Models for Sequence Modeling
Thai-Khanh Nguyen, Ngoc-Bich-Uyen Vo, Thieu N. Vo +2
State space models (SSMs) have emerged as efficient linear-time alternatives to attention for long-sequence modeling. However, existing SSMs often suffer from instability and memor…
Geometric and Stochastic Analysis of Discontinuities in Sparse Mixture-of-Experts
Tho Tran Huu, Huu-Tuan Nguyen, Thien-Hai Nguyen +4
Sparse Mixture-of-Experts (SMoE) architectures are now widely deployed in state-of-the-art language and vision models, where conditional routing allows scaling to very large networ…
Functional Equivalence in Attention: A Comprehensive Study with Applications to Linear Mode Connectivity
Viet-Hoang Tran, Vinh Khanh Bui, Van-Hoan Trinh +2
Neural network parameter spaces are inherently non-injective, as distinct parameter configurations can realize identical functions through functional equivalence. While this symmet…
Conservation Laws for Modern Neural Architectures
Viet-Hoang Tran, Vinh Khanh Bui, Tan Lai Ngoc +3
Understanding gradient descent dynamics is key to explaining the success of over-parameterized models, where implicit bias manifests through conservation laws in gradient flow. Whi…
High-Dimensional Random Projection for Activation Steering in Language Models
Minh-Hieu Pham, Bach Do, Laziz Abdullaev +2
Activation steering has emerged as a key methodology for controlling the behavior of large language models (LLMs). Existing difference-in-means based methods, however, are fundamen…
Quasi-Equivariant Metanetworks
Viet-Hoang Tran, An Nguyen, Benoît Guérand +2
Metanetworks are neural architectures designed to operate directly on pretrained weights to perform downstream tasks. However, the parameter space serves only as a proxy for the un…
Concept Heterogeneity-aware Representation Steering
Laziz U. Abdullaev, Noelle Y. L. Wong, Ryan T. Z. Lee +3
Representation steering offers a lightweight mechanism for controlling the behavior of large language models (LLMs) by intervening on internal activations at inference time. Most e…
MMA: A Momentum Mamba Architecture for Human Activity Recognition with Inertial Sensors
Thai-Khanh Nguyen, Uyen Vo, Tan M. Nguyen +3
Human activity recognition (HAR) from inertial sensors is essential for ubiquitous computing, mobile health, and ambient intelligence. Conventional deep models such as Convolutiona…
Dynamical Properties of Tokens in Self-Attention and Effects of Positional Encoding
Duy-Tung Pham, An The Nguyen, Viet-Hoang Tran +4
This paper investigates the dynamical properties of tokens in pre-trained Transformer models and explores their application to improving Transformers. To this end, we analyze the d…
Selective Sinkhorn Routing for Improved Sparse Mixture of Experts
Duc Anh Nguyen, Huu Binh Ta, Nhuan Le Duc +2
Sparse Mixture-of-Experts (SMoE) models are scalable and computationally efficient, enabling large increases in model capacity with limited inference overhead. Existing SMoE method…
Angular Steering: Behavior Control via Rotation in Activation Space
Hieu M. Vu, Tan M. Nguyen
Controlling specific behaviors in large language models while preserving their general capabilities is a central challenge for safe and reliable artificial intelligence deployment.…
On Linear Mode Connectivity of Mixture-of-Experts Architectures
Viet-Hoang Tran, Van Hoan Trinh, Khanh Vinh Bui +1
Linear Mode Connectivity (LMC) is a notable phenomenon in the loss landscapes of neural networks, wherein independently trained models have been observed to be connected--up to per…
Modeling Expert Interactions in Sparse Mixture of Experts via Graph Structures
Minh-Khoi Nguyen-Nhat, Rachel S. Y. Teo, Laziz Abdullaev +3
Sparse Mixture of Experts (SMoE) has emerged as a promising solution to achieving unparalleled scalability in deep learning by decoupling model parameter count from computational c…
Expert Merging in Sparse Mixture of Experts with Nash Bargaining
Dung V. Nguyen, Anh T. Nguyen, Minh H. Nguyen +6
Existing expert merging strategies for Sparse Mixture of Experts (SMoE) typically rely on input-dependent or input-independent averaging of expert parameters, but often lack a prin…
Activation Steering with a Feedback Controller
Dung V. Nguyen, Hieu M. Vu, Nhi Y. Pham +2
Controlling the behaviors of large language models (LLM) is fundamental to their safety alignment and reliable deployment. However, existing steering methods are primarily driven b…
The Blessing and Curse of Dimensionality in Safety Alignment
Rachel S. Y. Teo, Laziz U. Abdullaev, Tan M. Nguyen
The focus on safety alignment in large language models (LLMs) has increased significantly due to their widespread adoption across different domains. The scale of LLMs play a contri…
Tree-Sliced Wasserstein Distance with Nonlinear Projection
Thanh Tran, Viet-Hoang Tran, Thanh Chu +4
Tree-Sliced methods have recently emerged as an alternative to the traditional Sliced Wasserstein (SW) distance, replacing one-dimensional lines with tree-based metric spaces and i…