Tootfinder

ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
Nata\v{s}a Kreji\'c, Nata\v{s}a Krklec Jerinki\'c, Tijana Ostoji\'c, Nemanja Vu\v{c}i\'cevi\'c
https://arxiv.org/abs/2508.02299

ASPEN: An Additional Sampling Penalty Method for Finite-Sum Optimization Problems with Nonlinear Equality Constraints
We propose a novel algorithm for solving non-convex, nonlinear equality-constrained finite-sum optimization problems. The proposed algorithm incorporates an additional sampling strategy for sample size update into the well-known framework of quadratic penalty methods. Thus, depending on the problem at hand, the resulting method may exhibit a sample size strategy ranging from a mini-batch on one end, to increasing sample size that achieves the full sample eventually, on the other end of the spec…

VergeIO: Depth-Aware Eye Interaction on Glasses
Xiyuxing Zhang, Duc Vu, Chengyi Shen, Yuntao Wang, Yuanchun Shi, Justin Chan
https://arxiv.org/abs/2507.02187

VergeIO: Depth-Aware Eye Interaction on Glasses
There is growing industry interest in creating unobtrusive designs for electrooculography (EOG) sensing of eye gestures on glasses (e.g. JINS MEME and Apple eyewear). We present VergeIO, the first EOG-based glasses that enables depth-aware eye interaction using vergence with an optimized electrode layout and novel smart glass prototype. It can distinguish between four and six depth-based eye gestures with 83-98% accuracy using personalized models in a user study across 11 users and 1,320 gestur…

On Performance of IoT Networks with Coordinated NOMA Transmission: Covert Monitoring and Information Decoding
Thai-Hoc Vu, Anh-Tu Le, Ngo Hoang Tu, Tan N. Nguyen, Miroslav Voznak
https://arxiv.org/abs/2509.01935

On Performance of IoT Networks with Coordinated NOMA Transmission: Covert Monitoring and Information Decoding
This work investigates the covertness and security performance of Internet-of-Things (IoTs) networks under Rayleigh fading environments. Specifically, a cellular source transmits covert information to cell-edge users with the assistance of an IoT master node, employing a coordinated direct and relay transmission strategy combined with non-orthogonal multiple access (NOMA). This approach not only enhances spectrum utilization but also generates friendly interference to complicate a warden's surv…

First Steps Towards Voice Anonymization for Code-Switching Speech
Sarina Meyer, Ekaterina Kolos, Ngoc Thang Vu
https://arxiv.org/abs/2507.01765 https://

First Steps Towards Voice Anonymization for Code-Switching Speech
The goal of voice anonymization is to modify an audio such that the true identity of its speaker is hidden. Research on this task is typically limited to the same English read speech datasets, thus the efficacy of current methods for other types of speech data remains unknown. In this paper, we present the first investigation of voice anonymization for the multilingual phenomenon of code-switching speech. We prepare two corpora for this task and propose adaptations to a multilingual anonymizati…

A ChatGPT-based approach for questions generation in higher education
Sinh Trong Vu, Huong Thu Truong, Oanh Tien Do, Tu Anh Le, Tai Tan Mai
https://arxiv.org/abs/2507.21174 http…

A ChatGPT-based approach for questions generation in higher education
Large language models have been widely applied in many aspects of real life, bringing significant efficiency to businesses and offering distinctive user experiences. In this paper, we focus on exploring the application of ChatGPT, a chatbot based on a large language model, to support higher educator in generating quiz questions and assessing learners. Specifically, we explore interactive prompting patterns to design an optimal AI-powered question bank creation process. The generated questions a…

Enhancing Document Retrieval in COVID-19 Research: Leveraging Large Language Models for Hidden Relation Extraction
Hoang-An Trieu, Dinh-Truong Do, Chau Nguyen, Vu Tran, Minh Le Nguyen
https://arxiv.org/abs/2506.18311

Enhancing Document Retrieval in COVID-19 Research: Leveraging Large Language Models for Hidden Relation Extraction
In recent years, with the appearance of the COVID-19 pandemic, numerous publications relevant to this disease have been issued. Because of the massive volume of publications, an efficient retrieval system is necessary to provide researchers with useful information if an unexpected pandemic happens so suddenly, like COVID-19. In this work, we present a method to help the retrieval system, the Covrelex-SE system, to provide more high-quality search results. We exploited the power of the large lan…

Ultrahigh Anomalous Nernst Thermopower and Thermal Hall Angle in YbMnBi2
Jiamin Wen, Kaustuv Manna, Dung Vu, Subhadeep Bej, Yu Pan, Claudia Felser, Brian Skinner, Joseph P. Heremans
https://arxiv.org/abs/2506.20721

Ultrahigh Anomalous Nernst Thermopower and Thermal Hall Angle in YbMnBi2
Thermoelectrics (TEs) are solid-state devices that can realize heat-electricity conversion. Transverse TEs require materials with a large Nernst effect, which typically requires a strong applied magnetic field. However, topological materials with magnetic order offer an alternative pathway for achieving large Nernst via the anomalous Hall effect and the accompanying anomalous Nernst effect (ANE) that arise from band topology. Here, we show that YbMnBi2 with a low Hall density and a chemical pot…

An Empirical Study of Multi-Agent RAG for Real-World University Admissions Counseling
Anh Nguyen-Duc, Chien Vu Manh, Bao Anh Tran, Viet Phuong Ngo, Luan Le Chi, Anh Quang Nguyen
https://arxiv.org/abs/2507.11272

An Empirical Study of Multi-Agent RAG for Real-World University Admissions Counseling
This paper presents MARAUS (Multi-Agent and Retrieval-Augmented University Admission System), a real-world deployment of a conversational AI platform for higher education admissions counseling in Vietnam. While large language models (LLMs) offer potential for automating advisory tasks, most existing solutions remain limited to prototypes or synthetic benchmarks. MARAUS addresses this gap by combining hybrid retrieval, multi-agent orchestration, and LLM-based generation into a system tailored fo…

Distinguishing symmetric digraphs by proper arc-colourings of type I
Rafa{\l} Kalinowski, Monika Pil\'sniak, Magdalena Prorok
https://arxiv.org/abs/2506.13979

Distinguishing symmetric digraphs by proper arc-colourings of type I
A symmetric digraph $\overleftrightarrow{G}$ is obtained from a simple graph $G$ by replacing each edge $uv$ with a pair of opposite arcs $\vec{uv}$, $\overrightarrow{vu}$. An arc-colouring $c$ of a digraph $\overleftrightarrow{G}$ is distinguishing if the only automorphism of $\overleftrightarrow{G}$ preserving the colouring $c$ is the identity. Behzad introduced the proper arc-colouring of type I as an arc-colouring such that any two consecutive arcs $\overrightarrow{uv}$, $\overrightarrow{vw…

Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis
Paul Mayer, Florian Lux, Alejandro P\'erez-Gonz\'alez-de-Martos, Angelina Elizarova, Lindsey Vanderlyn, Dirk V\"ath, Ngoc Thang Vu
https://arxiv.org/abs/2507.00227

Investigating Stochastic Methods for Prosody Modeling in Speech Synthesis
While generative methods have progressed rapidly in recent years, generating expressive prosody for an utterance remains a challenging task in text-to-speech synthesis. This is particularly true for systems that model prosody explicitly through parameters such as pitch, energy, and duration, which is commonly done for the sake of interpretability and controllability. In this work, we investigate the effectiveness of stochastic methods for this task, including Normalizing Flows, Conditional Flow…

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment
Long-Vu Hoang, Tuan Nguyen, Tran Huy Dat
https://arxiv.org/abs/2506.14148

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment
This paper presents a novel non-invasive object classification approach using acoustic scattering, demonstrated through a case study on hair assessment. When an incident wave interacts with an object, it generates a scattered acoustic field encoding structural and material properties. By emitting acoustic stimuli and capturing the scattered signals from head-with-hair-sample objects, we classify hair type and moisture using AI-driven, deep-learning-based sound classification. We benchmark compr…

Relaxed and inertial nonlinear Forward-Backward algorithm
Juan Jos\'e Maul\'en, Fernando Rold\'an, Cristian Vega
https://arxiv.org/abs/2507.18856 https://

Relaxed and inertial nonlinear Forward-Backward algorithm
The Nonlinear Forward-Backward (NFB) algorithm, also known as warped resolvent iterations, is a splitting method for finding zeros of sums of monotone operators. In particular cases, NFB reduces to well-known algorithms such as Forward-Backward, Forward-Backward-Forward, Chambolle--Pock, and Condat-Vu. Therefore, NFB can be used to solve monotone inclusions involving sums of maximally monotone, cocoercive, monotone and Lipschitz operators as well as linear compositions terms. In this article, w…

Exact downfolding and its perturbative approximation
Jonas B. Profe, Jak\v{s}a Vu\v{c}i\v{c}evi\'c, P. Peter Stavropoulos, Malte R\"osner, Roser Valent\'i, Lennart Klebl
https://arxiv.org/abs/2507.16916

Exact downfolding and its perturbative approximation
Solving the many-electron problem, even approximately, is one of the most challenging and simultaneously most important problems in contemporary condensed matter physics with various connections to other fields. The standard approach is to follow a divide and conquer strategy that combines various numerical and analytical techniques. A crucial step in this strategy is the derivation of an effective model for a subset of degrees of freedom by a procedure called downfolding, which often correspon…

Expanding a 4-qubit Dicke State a to 5-qubit Dicke State with Limited Qubit Access
Bibhuti Thapa, Oberon Moran, Duc-Kha Vu, Fatih Ozaydin
https://arxiv.org/abs/2508.07977 https:…

Expanding a 4-qubit Dicke State a to 5-qubit Dicke State with Limited Qubit Access
In scenarios where full access to all qubits of a multipartite quantum system is available and global operations can be implemented, the preparation of arbitrary entangled states - including multipartite Dicke states - is theoretically straightforward. However, practical constraints often limit direct control over all qubits. In this work, we first present an efficient method for preparing a four-qubit Dicke state, and then demonstrate how a four-qubit Dicke state can be expanded to a five-qubi…

Singularity of non-pluripolar cohomology classes
Duc-Bao Nguyen, Shuang Su, Duc-Viet Vu
https://arxiv.org/abs/2508.14669 https://arxiv.org/pdf/2508.14669…

Singularity of non-pluripolar cohomology classes
We establish a relation between Lelong numbers and the full mass property of relative non-pluripolar products. We use it to show that if the restricted volume of a big cohomology class $α$ in a compact Kähler $n$-dimensional manifold $X$ to an effective divisor $D$ is of full mass, then the Lelong numbers of the non-pluripolar class $\langle α^{n-1}\rangle$ at every point in the support of $D$ is zero. In particular, we obtain that on projective manifolds, the Lelong numbers of the non-pluri…

Long time behavior of the Vlasov-Maxwell-Fokker-Planck system with a strong external magnetic field
Anh-Tuan Vu
https://arxiv.org/abs/2508.12231 https://ar…

Long time behavior of the Vlasov-Maxwell-Fokker-Planck system with a strong external magnetic field
The subject matter of this paper concerns the magnetic confinement of plasma. We investigate the long time behavior of the Vlasov-Maxwell-Fokker-Planck system under the effect of a strong external magnetic field. We first formally derive an asymptotically reduced model. In three space dimensions, a constraint occurs along the parallel direction to the magnetic field. To eliminate the corresponding Lagrange multiplier, we then study the Vlasov-Maxwell-Fokker-Planck system in two spatial dimensio…

Associated primes of the second power of closed neighborhood ideals of graphs
Ha Thi Thu Hien, Thanh Vu
https://arxiv.org/abs/2507.08777 https://

Associated primes of the second power of closed neighborhood ideals of graphs
We study simple graphs for which the maximal homogeneous ideal is an associated prime of the second power of their closed neighborhood ideals. In particular, we show that such graphs must have diameter at most $6$, and that those with diameter $2$ must be vertex diameter-$2$-critical.

Privacy Preserving Inference of Personalized Content for Out of Matrix Users
Michael Sun, Tai Vu, Andrew Wang
https://arxiv.org/abs/2508.14905 https://arxi…

Privacy Preserving Inference of Personalized Content for Out of Matrix Users
Recommender systems for niche and dynamic communities face persistent challenges from data sparsity, cold start users and items, and privacy constraints. Traditional collaborative filtering and content-based approaches underperform in these settings, either requiring invasive user data or failing when preference histories are absent. We present DeepNaniNet, a deep neural recommendation framework that addresses these challenges through an inductive graph-based architecture combining user-item in…

TotalRegistrator: Towards a Lightweight Foundation Model for CT Image Registration
Xuan Loc Pham, Gwendolyn Vuurberg, Marjan Doppen, Joey Roosen, Tip Stille, Thi Quynh Ha, Thuy Duong Quach, Quoc Vu Dang, Manh Ha Luu, Ewoud J. Smit, Hong Son Mai, Mattias Heinrich, Bram van Ginneken, Mathias Prokop, Alessa Hering
https://arxiv.org/abs/2508.0…

TotalRegistrator: Towards a Lightweight Foundation Model for CT Image Registration
Image registration is a fundamental technique in the analysis of longitudinal and multi-phase CT images within clinical practice. However, most existing methods are tailored for single-organ applications, limiting their generalizability to other anatomical regions. This work presents TotalRegistrator, an image registration framework capable of aligning multiple anatomical regions simultaneously using a standard UNet architecture and a novel field decomposition strategy. The model is lightweight…

Benchmark Dataset Generation and Evaluation for Excel Formula Repair with LLMs
Ananya Singha, Harshita Sahijwani, Walt Williams, Emmanuel Aboah Boateng, Nick Hausman, Miguel Di Luca, Keegan Choudhury, Chaya Binet, Vu Le, Tianwei Chen, Oryan Rokeah Chen, Sulaiman Vesal, Sadid Hasan
https://arxiv.org/abs/2508.11715

Benchmark Dataset Generation and Evaluation for Excel Formula Repair with LLMs
Excel is a pervasive yet often complex tool, particularly for novice users, where runtime errors arising from logical mistakes or misinterpretations of functions pose a significant challenge. While large language models (LLMs) offer promising assistance by explaining formula errors, the automated correction of these semantic runtime errors remains an open problem. A primary challenge to advancing models for such scenarios is the severe lack of high-quality, comprehensive datasets for training a…

Bridging Simulation and Experiment: A Self-Supervised Domain Adaptation Framework for Concrete Damage Classification
Chen Xu, Giao Vu, Ba Trung Cao, Zhen Liu, Fabian Diewald, Yong Yuan, G\"unther Meschke
https://arxiv.org/abs/2508.04538

Bridging Simulation and Experiment: A Self-Supervised Domain Adaptation Framework for Concrete Damage Classification
Reliable assessment of concrete degradation is critical for ensuring structural safety and longevity of engineering structures. This study proposes a self-supervised domain adaptation framework for robust concrete damage classification using coda wave signals. To support this framework, an advanced virtual testing platform is developed, combining multiscale modeling of concrete degradation with ultrasonic wave propagation simulations. This setup enables the generation of large-scale labeled syn…

Dynamics of rotationally invariant polynomial root sets under iterated differentiations
Andr\'e Galligo, Joseph Najnudel, Truong Vu
https://arxiv.org/abs/2506.06263

Dynamics of rotationally invariant polynomial root sets under iterated differentiations
We associate to an $N$-sample of a given rotationally invariant probability measure $μ_0$ with compact support in the complex plane, a polynomial $P_N$ with roots given by the sample. Then, for $t \in (0,1)$, we consider the empirical measure $μ_t^{N}$ associated to the root set of the $\lfloor t N\rfloor$-th derivative of $P_N$. A question posed by O'Rourke and Steinerberger \cite{o2021nonlocal}, reformulated as a conjecture by Hoskins and Kabluchko \cite{hoskins2021dynamics}, and recently…