March 2026 arXiv papers — page 102

Hesong Li, Ziqi Wu, Ruiwen Shao, Ying Fu

High-Resolution Transmission Electron Microscopy (HRTEM) enables atomic-scale observation of nucleation dynamics, which boosts the studies of advanced solid materials. Nonetheless, due to the millisecond-scale rapid change of nucleation, it requires short-exposure rapid imaging, leading to severe noise that obscures atomic positions. In this work, we propose

Uche Mbaka, Jiguo Cao, Michelle Carey

Sparse functional data arise when measurements are observed infrequently and at irregular time points for each subject, often in the presence of measurement error. These characteristics introduce additional challenges for functional principal component analysis. In this paper, we propose a new approach for extracting functional principal components from such

Guillaume Estienne

In 2007, Papanikolas established that if Carlitz logarithms of algebraic functions are linearly independent over the rational function field, then they are algebraically independent. The purpose of the present paper is to provide a new proof of this theorem using Mahler s method instead of the theory of t-motives. We revisit and extend the approach developed

Radek Zavorka, Ondrej Zeleny, Jiri Blumenstein, Tomas Mikulasek

Understanding the impact of vegetation and small-scale antenna movements on signal propagation is important for the design and optimization of high-frequency wireless communication systems. This paper presents an experimental study analyzing signal propagation at 60 GHz and 80 GHz in the presence of vegetation, with a focus on forward scattering and microdiv

Shaoxiang Sheng, Yang Luo, Chenyu Wang, Sayooj Sateesh

Controlling nonequilibrium responses in optically driven quantum materials is essential for advancing applications in energy conversion, ultrafast electronics, and quantum computation. Nonlinear optical spectroscopy serves as a powerful tool to investigate ultrafast electron and phonon dynamics in these systems; however, conventional nonlinear approaches oft

Marcelo Fernandez

Autonomous agents can produce harmful behavioral patterns from individually valid requests -- a threat class per-request policy evaluation cannot address, because stateless engines evaluate each request in isolation. We present ACP, a temporal admission control protocol enforcing behavioral properties over execution traces via static risk scoring combined wi

Egle Pagliaro, Leonardo Zambrano, Mir Alimuddin, Alioscia Hamma

Ergotropy, the maximum work extractable from a quantum system, is a central resource in quantum physics. Computing ergotropy is well established when the system state is fully known, but its estimation under partial information remains an open problem. Here we introduce a general certification framework that lower bounds ergotropy using only the expectation

Tudor-Dan Mihoc, Manuela-Andreea Petrescu, Emilia-Loredana Pop

An investigation, from a gender perspective, of how students view the ethical implications and societal effects of artificial intelligence is conducted, examining concepts that could have a big influence on how artificial intelligence may be taught in the future. For this, we conducted a survey on a cohort of 230 second year computer science students to reve

C. Pallis

We review two types of fractional Kaehler potentials $K$ which reduce, along the inflationary path, to the form $N/(1-\phi^{q_{\rm M}})^{p}$ with $q_{\rm M}=1$ or $2$ and $0.1\leq p\leq10$. Their coexistence, within a non-linear sigma model, with chaotic inflationary potentials of the form $\phi^n$ (where $n=2$ or $4$) determines, independently from $q_{\rm

Augustine Kshetrimayum, Saeed S. Jahromi, Sukhbinder Singh, Román Orús

We review the recent quantum advantage experiments by IBM, D-Wave, and Google, focusing on cases where efficient classical simulations of the experiment were demonstrated or attempted using tensor network methods. We assess the strengths and limitations of these tensor network-based approaches and examine how the interplay between classical simulation and qu

Kyoko Shibata, Hana Kanda, Yoshimi Tanaka, Yutaka Sumino

We investigate the encapsulation of water by a thin elastic film as a minimal model of elastocapillary self-folding with fluid transport. An equilateral triangular polydimethylsiloxane film is lifted quasi-statically from a water surface, while its side length and thickness are systematically varied. Depending on these parameters, the film exhibits three dis

Harsh Varshney, Amit Agarwal

Longitudinal nonreciprocal charge transport is usually associated with broken time-reversal symmetry, either from magnetic order or an external magnetic field. Here, we show that it can also arise in nonmagnetic conductors preserving time-reversal symmetry through disorder-induced asymmetric scattering. Within a semiclassical Boltzmann theory, skew-scatterin

Maria Milkova, Maksim Rudnev

This study presents a multi-stage classification framework for detecting human values in noisy Russian language social media, validated on a random sample of 7.5 million public text posts. Drawing on Schwartz's theory of basic human values, we design a multi-stage pipeline that includes spam and nonpersonal content filtering, targeted selection of value rele

Amit Kuber, Annoy Sengupta

Motivated by the recent work of Deaconu, Mousavand and Paquette on the connection between infinite string bricks for certain gentle algebras and Sturmian words, we develop a decorated version of a deterministic automaton, called a multi-entry inverse automaton (MIA, for short) that accepts pointed words. We then associate an MIA $\mathsf M_{\Lambda\delta}$ o

Yong Zhang

Quantum interference provides one of the most sensitive probes of quantum mechanics. While linear superposition fixes the positions and quadratic curvature of interference fringes, it remains unclear whether the probabilistic postulate itself, the Born rule, can be tested through finer, local features of interference patterns. Here we show that a minimal def

Stefano Bianchini, Luca Talamini

Consider a piecewise affine Lipschitz map $\phi : \Omega \to \mathbb R$, where $\Omega \subset \mathbb R^d$ is an open set, and assume that $x \mapsto x + t \nabla \phi(x)$ is injective for almost every $t > 0$. In (J.-G. Liu, R.~L. Pego, \emph{Rigidly breaking potential flows and a countable Alexandrov theorem for polytopes}, Pure Appl. Anal., \textbf{7}(4)

Sophie J. Kersting, Mareike Fischer

We investigate the use of additional 3D and phylogenetic non-3D tree balance indices for analyzing and monitoring forests using an exemplary "virtual forest" dataset from the Wytham Woods, Oxford, UK. This study assesses 3D model quality, species classification performance, and the relevance of these indices. Our study shows that indices stemming from the st

Thalyta T. Martins, Ines Ben-Yedder, Alex Fontana, Loïc Rondin

Understanding the role of inertia in nanoscale heat transport is fundamental to the design of efficient nano-thermodynamics systems. In this work, we experimentally address the non-equilibrium dynamics of a Brownian gyrator, a paradigmatic model for nano-heat machines, that converts heat flow between two thermal baths into steady-state rotation. Using an opt

Hisham Husain, Valentin De Bortoli, Richard Nock

The use of discriminators to train or fine-tune generative models has proven to be a rather successful framework. A notable example is Generative Adversarial Networks (GANs) that minimize a loss incurred by training discriminators along with other paradigms that boost generative models via discriminators that satisfy weak learner constraints. More recently,

Marcin Piotr Pruszczyk, Gregory Schehr

These notes are based on lectures delivered by G. Schehr at the XVIth School on Fundamental Problems in Statistical Physics (FPSP), held in Oropa (Italy) from 30 June to 11 July 2025. After a brief introduction to extreme value statistics (EVS) for independent and identically distributed (IID) random variables, we discuss several paradigmatic examples of str

Hao Zhang, Mingjie Liu, Shaokun Zhang, Songyang Han

Multi-turn LLM agents are increasingly important for solving complex, interactive tasks, and reinforcement learning (RL) is a key ingredient for improving their long-horizon behavior. However, RL training requires generating large numbers of sandboxed rollout trajectories, and existing infrastructures often couple rollout orchestration with the training loop

Xiaoyang Chen, Xiang Jiang

This paper is the second one in a series of work on the mathematical creativity of LLM. In the first paper, the authors proposed three criteria for evaluating the mathematical creativity of LLM and constructed a benchmark dataset to measure it. This paper further explores the mathematical creativity of LLM, with a focus on investigating whether LLM can gener

Oswin Aichholzer, Joseph Dorfer, Sándor P. Fekete, Phillip Keldenich

We give an overview of the 2026 Computational Geometry Challenge targeting the problem of finding a Central Triangulation under Parallel Flip Operations in triangulations of point sets. A flip is the parallel exchange of a set of edges in a triangulation with opposing diagonals of the convex quadrilaterals containing them. The challenge objective was, given

Songjia He, Zixuan Chen, Hongyu Ding, Dian Shao

Training generalist robots demands large-scale, diverse manipulation data, yet real-world collection is prohibitively expensive, and existing simulators are often constrained by fixed asset libraries and manual heuristics. To bridge this gap, we present V-Dreamer, a fully automated framework that generates open-vocabulary, simulation-ready manipulation envir

Jiri Blumenstein, Radek Zavorka, Josef Vychodil, Tomas Mikulasek

A stochastic modeling methodology for 3-D foliage is presented, aimed at enhancing ray-tracing simulations. The model supports adjustable stochastic geometry, density, and shape to capture variability in foliage structures. The model is validated through experimental measurements of representative vegetation. The influence of foliage density and size on path

Keisuke Taga, Hiroya Nakao

In dynamical systems, invariants, i.e., constants of motion conserved along the trajectory, play important roles in characterizing the system's dynamical behavior. Recent applications of the Koopman operator framework to nonlinear dynamical systems have provided new insights into the invariants. For a certain class of globally coupled phase oscillators, whic

Hanbom Yoo, Hyukgun Kwon, Seongjin Hong

Quantum metrology enables parameter estimation beyond classical limits by exploiting nonclassical resources such as squeezing and entanglement. In distributed quantum sensing, Heisenberg scaling has been extended from $1/N^2$ to $1/(NM)^2$ through entanglement across both particles and spatial modes, where $N$ denotes the photon number and $M$ the number of

Wenxuan Zhang, Lemeng Wu, Changsheng Zhao, Ernie Chang

Diffusion Large Language Models (dLLMs) introduce a new paradigm for language generation, which in turn presents new challenges for aligning them with human preferences. In this work, we aim to improve the policy optimization for dLLMs by reducing the cost of the trajectory probability calculation, thereby enabling scaled-up offline policy training. We prove

Jing Huang

M\'oricz and Nagy introduced the problem of maximizing the number of $r$-element subsets with rational sums in an $n$-element set of irrational numbers, and showed that it is equivalent to an extremal zero-sum problem. They determined the exact maximum in several cases. For the remaining range, they presented an explicit construction of an $n$-element set of

Neil Fernandes, Cheng Tang, Tehniyat Shahbaz, Alex Hauschildt

Community literacy programs supporting young newcomer children in Canada face limited staffing and scarce one-to-one time, which constrains personalized English and cultural learning support. This paper reports on a co-design study with United for Literacy tutors that informed Maple, a table-top, peer-like Socially Assistive Robot (SAR) designed as a practic

Akinari Hoshi, Hiroaki Iida

Let $m\in\mathbb{Z}$ be an integer and $L_m=\mathbb{Q}(α)$ be the simplest cubic field with class number $h_m$ and conductor $\mathfrak{f}_m$ where $α$ is a root of $f_m(X)=X^3-mX^2-(m+3)X-1$. Let $\mathcal{O}_{L_m}$ be the ring of integers of $L_m$. By using PARI/GP, we determine that if $[\mathcal{O}_{L_m}:\mathbb{Z}[α]]=1$ $($resp. $3$, $27$$)$, i.e. $m^2

Santiago Lamata-Otín, Alex Arenas, Jesús Gómez-Gardeñes, David Soriano-Paños

The SIR model is the cornerstone model for mathematical epidemiology, explaining key epidemic features such as the second-order transition between disease-free and epidemic states, the initial exponential growth of outbreaks or the short-term benefits of control measures. Nonetheless, the classical SIR model assumes that pathogen traits remain fixed, thus ne

Kiyoshi Takeuchi

This survey paper offers a concise introduction to Kashiwara's work on $\mathcal{D}$-modules, microlocal analysis and related subjects. In this way, we explain his role in the development of algebraic analysis.

Yufei Cao, Penny Sweetser, Ziyu Chen, Xuanying Zhu

User performance is crucial in interactive systems, capturing how effectively users engage with task execution. Prospectively predicting performance enables the timely identification of users struggling with task demands. While ocular and cardiac signals are widely used to characterise performance-relevant visual behaviour and physiological activation, their

Masaru Kajisawa

Using $JWST$/NIRCam data over a 0.28 deg$^{2}$ area from COSMOS-Web survey, together with $HST$/ACS data, we investigate early-type fraction of massive galaxies with $M_{star}>10^{10.5}M_{\odot}$ at $0.2<z<2.0$, and explore the formation of their early-type morphology. We measure concentration index $C$ ($=R_{80}/R_{20}$) and asymmetry index $A$, and select

Yuchen Li, Amanmeet Garg, Shalini Chaudhuri, Rui Zhao

Large Vision Language Models (LVLMs) excel at semantic understanding but struggle with fine grained spatial grounding, as the model must implicitly infer complex geometry without ever producing a spatial interpretation. We present Perceptio, a perception enhanced LVLM with 2D and 3D spatial reasoning abilities, enabled via explicit semantic segmentation toke

Masato Minamitsuji

We investigate exact plane-fronted gravitational wave (pp-wave) solutions within the framework of shift-symmetric quadratic-order higher-order scalar--tensor (HOST) theories. These solutions represent fully nonlinear radiative spacetimes that extend beyond the linearized approximation. We demonstrate that under the algebraic conditions on the coupling functi

Zikang Ding, Junhao Li, Suling Wu, Junchi Yao

Model watermarking utilizes internal representations to protect the ownership of large language models (LLMs). However, these features inevitably undergo complex distortions during realistic model modifications such as fine-tuning, quantization, or knowledge distillation, making reliable extraction extremely challenging. Despite extensive research on model-s

Martí Llopart Font, Javier Hernando, Cristina España-Bonet

The standard FlashAttention-3 heuristic exhibits a GPU occupancy bottleneck in low-head-count decoding configurations because it disables sequence splitting based on sequence length alone, underutilizing the Streaming Multiprocessors of Hopper GPUs. Our proposed sequence-aware split policy mitigates this by allowing sequence-level parallelism in low-head-cou

Madhubanti Mukherjee, Ashutosh Srivastava, Abhishek Kumar Singh

Understanding anharmonicity is crucial for designing materials with desired lattice thermal conductivity. Designing a material descriptor that effectively captures anharmonicity while being cost-effective remains a significant challenge. This work proposes a simple metric that helps explain the diversity in lattice thermal conductivity (kl) among materials b

Riku Fushimi

For finite-dimensional algebras over a field, Koenig and Yang established a bijection between silting complexes and simple-minded collections in the bounded derived category, with further contributions by many authors in various settings. In this paper, we work over a commutative complete local noetherian ring $(R,\m,k)$ rather than over a field and establis

Lingming Zhang, Binbin Zhao, Puzhuo Liu, Qinge Xie

The security of modern JavaScript (JS) engines is critical since they provide the primary defense mechanism for executing untrusted code on the web. The recent integration of WebAssembly (Wasm) has transformed these engines into complex polyglot environments, creating a novel attack surface at the JS-Wasm interaction boundary due to the distinct type systems

KT Tech innovation Group

The evolving LLM landscape requires capabilities beyond simple text generation, prioritizing multi-step reasoning, long-context understanding, and agentic workflows. This shift challenges existing models in enterprise environments, especially in Korean-language and domain-specific scenarios where scaling is insufficient. We introduce Mi:dm K 2.5 Pro, a 32B p

Igor Prlina, Milutin Živković

The standard approach to quantum measurements is to assume that they lead to effectively instantaneous collapse of the quantum state. However, if we assume that we are unable to enforce at what exact moment of time the measurement occurs due to a finite resolution of any time measurement device, at the level of the ensemble, the measurement would lead to an

Nitay Alon, Joseph M. Barnby, Reuth Mirsky, Stefan Sarkadi

This volume includes a selection of papers presented at the 2nd Workshop on Advancing Artificial Intelligence through Theory of Mind held at AAAI 2026 in Singapore on 26th January 2026. The purpose of this volume is to provide an open access and curated anthology for the ToM and AI research community.

Jiri Blumenstein, Radek Zavorka, Josef Vychodil, Tomas Mikulasek

In this paper, we show a stochastic approach to generate a 3D model of a foliage, which is then used for deterministic ray-tracing channel modeling. This approach is verified by a measurement campaign at 60 and 80 GHz with 2 GHz bandwidth. The wireless channel is characterized by path-loss and RMS delay spread and we show the angular dependency of those para

Yongqiang Zhao, Haining Luo, Yupeng Wang, Emmanouil Spyrakos Papastavridis

Deformable objects often appear in unstructured configurations. Tracing deformable objects helps bringing them into extended states and facilitating the downstream manipulation tasks. Due to the requirements for object-specific modeling or sim-to-real transfer, existing tracing methods either lack generalizability across different categories of deformable ob

Luca Seemungal

We prove that the index of a CMC surface with capillary boundary is bounded from above linearly by its genus, number of boundary components, and branching order, and also by some Willmore-type energy involving the area, mean curvature, contact angle, and ambient curvature. The main auxiliary theorem of more general interest is a comparison of the second vari

Jiatong Xia, Zicheng Duan, Anton van den Hengel, Lingqiao Liu

Recent progress in 3D generation has been driven largely by models conditioned on images or text, while readily available 3D priors are still underused. In many real-world scenarios, the visible-region point cloud are easy to obtain from active sensors such as LiDAR or from feed-forward predictors like VGGT, offering explicit geometric constraints that curre

Yufei Zhang, Tao Wang, Jingyi Zhang

Recursive partitioning methods provide computationally efficient surrogates for the Wasserstein distance, yet their statistical behavior and their resolution in the small-discrepancy regime remain insufficiently understood. We study Recursive Rank Matching (RRM) as a representative instance of this class under a population-anchored reference. In this setting

Volodymyr Monarkha, Massimo Borrelli, Reza Hajitashakkori Kenari, Mohammad Kobba

We report a comparative study on transmon qubit control using (i) conventional attenuated coaxial microwave line and (ii) an optical control system using modulated laser light delivered over telecommunications optical fiber to a photodiode located at the 1K stage of a dilution cryostat. During each experiment, we performed repeated measurements of the energy

Peilin Du, Jing Zhang, Tiancai Zhang, Rongguo Yang

The integration of diverse quantum resources and the exploitation of more degrees of freedom provide key operational flexibility for universal fault-tolerant quantum computation. In this work, we propose a flexible Gottesman-Kitaev-Preskill-state-embedded fault-tolerant quantum computation architecture based on a three-dimensional cluster state constructed i

Xiuzhu Yang, Xiaobo Yin

The Improved Partial Area-Analytical Calculation (IPA-AC) method represents a leading meshfree discretization strategy for peridynamic models, distinguished by its rigorous geometric treatment of boundary intersections via dual corrections of integration weights and quadrature points. Despite its empirical success in suppressing boundary-induced geometric er

Jiguang Yu, Nicholas Brendle, Joel T. Johnson, David Starobinski

We propose a physics-grounded mechanism design for dynamic spectrum sharing that bridges the gap between radiometric retrieval constraints and economic incentives. We formulate the active and passive users coexistence problem as a Vickrey-Clarke-Groves (VCG) auctions mechanism, where the radiometer dynamically procures ``quiet'' time-frequency tiles from act

Joris Witstok, Stefano Carniani, Peter Jakobsen, Andrew J. Bunker

$\require{mediawiki-texvc}$Galaxy assembly was already well underway in the first 400 Myr of cosmic time, as recently revealed by JWST. However, the contribution of these early galaxies to cosmic reionisation remains uncertain. Here we present new JWST/NIRSpec observations of GS-z13-1-LA obtained as part of the OASIS and JADES programmes, whose combined deep

Rojin Chhetri, Sijan Dhakal, Asmita Gautam

Internet of Things devices with 10 to 20 year lifespans need post-quantum migration, yet the finalised NIST standards remain sparsely benchmarked on the most constrained 32-bit ARM class. We present, to our knowledge, the first isolated algorithm-level benchmarks of ML-KEM (FIPS 203) and ML-DSA (FIPS 204) on ARM Cortex-M0+: all six parameter sets on the RP20

Channe Chwa, Xinle Wu, Yao Lu

LLM post-training pipelines that combine supervised fine-tuning and reinforcement learning are difficult to configure under realistic compute budgets: the configuration space is high-dimensional and heterogeneous, stages are strongly coupled, and each end-to-end evaluation is expensive. We propose AutoPipe, a budget-aware two-stage framework for configuratio

. I. Komech, E. A. Kopylova

We consider damped driven Maxwell-Bloch equations which are finite-dimensional approximation of the damped driven Maxwell-Schr\"odinger equations. The equations describe a single-mode Maxwell field coupled to a two-level molecule. Our main result is the construction of solutions with single-frequency asymptotics of the Maxwell field in the case of quasiperio

Fuze Sun, Lingyu Li, Lekan Dai, Xinyu Fan

This article suggests a reasoning-guided vision-language-motion diffusion framework (RG-VLMD) for generating instruction-aware co-speech gestures for humanoid robots in educational scenarios. The system integrates multi-modal affective estimation, pedagogical reasoning, and teaching-act-conditioned motion synthesis to enable adaptive and semantically consist

Alpár R. Mészáros, Guy Parker

We consider a cross-diffusion system for which the diffusion of each species is governed solely by the aggregate density through a pressure law of logarithmic or fast diffusion type. The model is set over a one dimensional bounded interval, equipped with no-flux boundary conditions, and accommodates for the presence of potential drifts which are allowed to d

Gergely Friss, Paul I. Palmer, Marrick Braam, Ken Rice

Hydrogen cyanide (HCN) is crucial for the RNA World hypothesis, forming biomolecules essential for early life. Life likely emerged around 4 billion years ago during the early Archean Eon, a period on Earth with a fainter sun, frequent impacts, and a weakly reducing atmosphere. Warm little ponds (WLPs) are hypothetical protective aqueous environments that hel

Boštjan Gabrovšek, Matic Simonič, Wanda Niemyska

We present a systematic classification of uncolored bonded knots with singularity number at most seven. Bonded knots provide a topological model for closed protein chains with intramolecular bridges, such as disulfide bonds. Following the tradition of knot tabulation, we describe a procedure based on the generation of planar graphs, their conversion into bon

Duc Hao Pham, Van Duy Truong, Duy Khanh Dinh, Tien Cuong Nguyen

Concept unlearning has emerged as a promising direction for reducing the risks of harmful content generation in text-to-image diffusion models by selectively erasing undesirable concepts from a model's parameters. Existing approaches typically rely on keywords to identify the target concept to be unlearned. However, we show that this keyword-based formulatio

Rudra Jadhav, Janhavi Danve, Sonalika Shaw

As large language models (LLMs) are increasingly deployed as automated graders in educational settings, concerns about fairness and bias in their evaluations have become critical. This study investigates whether LLMs exhibit implicit grading bias based on writing style when the underlying content correctness remains constant. We constructed a controlled data

Ying Zheng, Yiyi Zhang, Yi Wang, Lap-Pui Chau

Source-Free Domain Adaptation (SFDA) adapts pre-trained models to unlabeled target domains without requiring access to source data. Although state-of-the-art methods leveraging local neighborhood structures show promise for SFDA, they tend to over-rely on prediction similarity among neighbors. This over-reliance accelerates the forgetting of source knowledge

Tuoping Du, Zhifeng Pen, Haoyang Wan

In this paper, we establish the triality twisted trace formula for PGSO(8), including its discrete part, and obtain a coarse classification of its automorphic representations by combining the properties of triality. By comparing the standard trace formula for G_2 with the triality twisted trace formula for PGSO(8), we derive a corresponding coarse classifica

Haochen Zhao, Shaoyang Cui

Autonomous web agents such as \textbf{OpenClaw} are rapidly moving into high-impact real-world workflows, but their security robustness under live network threats remains insufficiently evaluated. Existing benchmarks mainly focus on static sandbox settings and content-level prompt attacks, which leaves a practical gap for network-layer security testing. In t

Djamel Bouchaffra, Faycal Ykhlef, Hanene Azzag, Mustapha Lebbah

Standard attention mechanisms in transformers are limited by their pairwise formulation, which hinders the modeling of higher-order dependencies among tokens. We introduce the NeuroGame Transformer (NGT) to overcome this by reconceptualizing attention through a dual perspective: tokens are treated simultaneously as players in a cooperative game and as intera

Nicolas Barré

Atmospheric turbulence severely limits the coupling of received optical wavefronts into single-mode fibers in satellite-to-ground free-space optical links. Spatial demultiplexing receivers address this challenge by distributing the incoming field across a bundle of single-mode fibers whose outputs are recombined coherently, relaxing the requirements on wavef

Alberto Marcone, Andrea Volpi

Order dimension theory measures the complexity of partially ordered sets by quantifying how far they are from being linearly ordered. In this paper we study classical bounding results for order dimension within the framework of reverse mathematics. We focus on principles asserting that the dimension of a poset can be bounded in terms of the dimension of subp

Hung-Yue Suen, Kuo-En Hung, Fan-Hsun Tseng

This paper outlines a machine learning-enabled speaker-centric Emotion AI approach capable of predicting audience-affective engagement and vocal attractiveness in asynchronous video-based learning, relying solely on speaker-side affective expressions. Inspired by the demand for scalable, privacy-preserving affective computing applications, this speaker-centr

Haochen Li, Rui Zhang, Hantao Yao, Xin Zhang

Domain Adaptive Object Detection (DAOD) aims to transfer detectors from a labeled source domain to an unlabeled target domain. Existing DAOD methods employ multi-granularity feature alignment to learn domain-invariant representations. However, the local connectivity of their CNN-based backbone and detection head restricts alignment to local regions, failing

Dayu Wang, Jiaye Yang, Weikang Li, Jiahui Liang

Flow Matching (FM) has recently emerged as a leading approach for high-fidelity visual generation, offering a robust continuous-time alternative to ordinary differential equation (ODE) based models. However, despite their success, FM models are highly sensitive to dataset biases, which cause severe semantic degradation when generating out-of-distribution or

Gabriele Carrino, Andrea Sassella, Nicolo Brunello, Federico Toschi

Recent advances in large language models (LLMs) highlight the importance of post training techniques for improving reasoning and mathematical ability. Group Relative Policy Optimization (GRPO) has shown promise in this domain by combining group relative advantage estimation, PPO style clipping, and KL regularization. However, its complexity raises the questi

G. Landi, A. Scaravelli, M. C. Tesi, C. Testa

Mathematical modeling offers a valuable approach to understanding Alzheimers disease (AD) given its complexity, unknown causes, and lack of effective treatments. Models, once validated, offer a powerful tool to test medical hypotheses that are otherwise difficult to verify directly. Our focus here is on elucidating the spread of misfolded tau protein, a crit

Enrico Della Valle, Arianna Nigro, Miki Bonacci, Nicola Colonna

Germanium-silicon-germanium (Ge/Si$_{x}$Ge$_{1-x}$) heterostructures have emerged as a promising platform for hole-spin quantum technologies and high-mobility electronics, where strain and quantum confinement strongly reshape the Ge valence bands. However, the momentum-resolved valence-band structure of buried strained Ge quantum wells has so far been inferr

Thomas Weikert, Eljas Roellin, Lukas Heumos, Fabian J. Theis

Neurological disorders represent a growing global health burden requiring long-term, interdisciplinary rehabilitation. Computational neurorehabilitation (compNR) - the use of data-driven and model-based approaches to personalize treatment - offers new opportunities for precision rehabilitation. However, its clinical deployment is limited by fragmented data s

Isabel Rio-Torto, Jaime S. Cardoso, Luís F. Teixeira

Natural language explanations provide an inherently human-understandable way to explain black-box models, closely reflecting how radiologists convey their diagnoses in textual reports. Most works explicitly supervise the explanation generation process using datasets annotated with explanations. Thus, though plausible, the generated explanations are not faith

Om Prakash Bhardwaj, Kanoy Kumar Das, Rutuja Sawant

In this article, we investigate when the ordinary and symbolic powers of the Alexander dual of connected ideals of graphs coincide, and provide a complete classification of all such graphs. Furthermore, we prove Conforti--Cornu\`ejols conjecture for this class of ideals.

Cristian Buttaro, Irene Amerini

The rapid proliferation of Large Language Models has significantly increased the difficulty of distinguishing between human-written and AI generated texts, raising critical issues across academic, editorial, and social domains. This paper investigates the problem of AI generated text detection through the design, implementation, and comparative evaluation of

John Kerfoot, David Schaich, Emanuele Mendicelli

The study of spontaneous supersymmetry breaking (SSB) on the lattice is obstructed by a severe sign problem. Quantum computing provides a promising alternative approach. In particular, properties of supersymmetry relate SSB to the ground-state energy, which can be probed using hybrid quantum--classical algorithms such as the variational quantum eigensolver (

Johannes Bäumler, Noam Berger, Tal Orenshtein, Martin Slowik

We establish annealed and quenched invariance principles for random walks in random conductances lifted to the p-variation rough path topology, allowing for degenerate environments and long-range jumps. Our proof is based on a unified structural strategy where pathwise convergence is viewed as a natural upgrade of the classical theory. This approach decouple

Daniel Dick, Florian Fuchs, Sibylle Gemming, Jörg Schuster

Local composition fluctuations in random alloys become crucial when one or more dimensions are reduced to the nanoscale. Using extended H\"uckel theory, we study the semiconductor random alloy SiGe sandwiched between Si due to its relevance for transistor devices. We evaluate the effects of the alloy composition, layer thickness, and local fluctuations of th

Sanghyun Park, Soohee Han

SLAM (Simultaneous Localization and Mapping) and Odometry are important systems for estimating the position of mobile devices, such as robots and cars, utilizing one or more sensors. Particularly in camera-based SLAM or Odometry, effectively tracking visual features is important as it significantly impacts system performance. In this paper, we propose a meth

Eduardo Casas, Nicolai Jork

We consider semilinear parabolic optimal control problems subject to Neumann boundary conditions, control constraints, and an infinite time horizon. The control constraints are pointwise in time, but they can be pointwise or integral in the space variable. Crucially, the optimal control problem does not include a Tikhonov regularization in the cost functiona

Huichi Zhou, Siyuan Guo, Anjie Liu, Zhongwei Yu

We introduce \emph{Memento-Skills}, a generalist, continually-learnable LLM agent system that functions as an \emph{agent-designing agent}: it autonomously constructs, adapts, and improves task-specific agents through experience. The system is built on a memory-based reinforcement learning framework with \emph{stateful prompts}, where reusable skills (stored

Rundong Su, Jintao Zhang, Zhihang Yuan, Haojie Duanmu

Diffusion transformers have demonstrated remarkable capabilities in generating videos. However, their practical deployment is severely constrained by high memory usage and computational cost. Post-Training Quantization provides a practical way to reduce memory usage and boost computation speed. Existing quantization methods typically apply a static bit-width

Santiago Berrezueta-Guzman, Vanesa Metaj, Stefan Wagner

As the landscape of software engineering evolves, introductory programming courses must go beyond teaching syntax to foster comprehensive technical competencies and professional soft skills. This paper reports on a pedagogical experience in a "Fundamentals of Programming" course that used a Project-Based Learning (PBL) framework to develop a 2D "Maze Runner"

Dimitris Mitropoulos, Nikolaos Alexopoulos, Georgios Alexopoulos, Diomidis Spinellis

Automated Code Review (ACR) systems integrating Large Language Models (LLMs) are increasingly adopted in software development workflows, ranging from interactive assistants to autonomous agents in CI/CD pipelines. In this paper, we study how LLM-based vulnerability detection in ACR is affected by the framing effect: the tendency to let the presentation of in

Longfei Liu, Yongjie Hou, Yang Li, Qirui Wang

Deploying high-performance dense prediction models on resource-constrained edge devices remains challenging due to strict computation and memory budgets. In practice, lightweight systems for object detection, instance segmentation, and pose estimation are still dominated by CNN-based architectures such as YOLO, while compact Vision Transformers (ViTs) often

Karl Fiteni, Xingchen Li, Mattia C. Sormani, Victor P. Debattista

There is now strong evidence that the Milky Way (MW) hosts a nuclear stellar disc (NSD). However, whether the NSD is purely axisymmetric or contains a nuclear bar remains unresolved. Since approximately $50\%$ of barred galaxies with MW-like mass in the local Universe host a nuclear bar, investigating whether the MW hosts one is of interest. We conduct a sys

Karl Fiteni, Stuart Robert Anderson, Victor. P. Debattista, Joseph Caruana

We leveraged reliable age and distance estimates from LAMOST-DR3 and APOGEE-DR17+AstroNN combined with \gaia\ data to perform a detailed analysis of the stellar age distribution in the Milky Way's (MW) outer disc using giant stars. Selecting stars near the midplane ($|z|<0.3$ kpc) on near-circular orbits ($\lambda_c > 0.9$), we analysed these independent dat

Hao Wang, Licheng Pan, Zhichao Chen, Chunyuan Zheng

Despite the success of reinforcement learning from human feedback (RLHF) in aligning language models, current reward modeling heavily relies on experimental feedback data collected from human annotators under controlled and costly conditions. In this work, we introduce observational reward modeling -- learning reward models with observational user feedback (

Jean-Baptiste Döderlein, Djamel Eddine Khelladi, Mathieu Acher, Benoit Combemale

Programming environments typically separate the world of static code from the dynamic execution of programs. Developers must switch between writing code and observing its execution, often with limited tools to understand the relationship between code changes and runtime behavior. Several paradigms and approaches exist to bridge this gap, including explorator

Vincenzo De Martino, Silverio Martínez-Fernández, Fabio Palomba

Context: The increasing adoption of machine learning (ML) and artificial intelligence (AI) technologies raises growing concerns about their environmental sustainability. Developing and deploying ML-enabled systems is computationally intensive, particularly during training and inference. Green AI has emerged to address these issues by promoting efficiency wit

F. M. Brunbauer, R. Aleksan, Y. Angelis, S. Aune

The combination of a Cherenkov radiator with a semi-transparent photocathode and a Micromegas based amplification stage allows PICOSEC Micromegas detectors to achieve a time resolution of better than 15ps. While tileable prototypes with 10x10 channels feature 1x1 cm^2 readout pads, finer readout granularity can be used to improve the spatial resolution. We r

Debajyoti Choudhuri, Dušan D. Repovš, Kamel Saoudi

This study is devoted to proving the existence of weak solutions for a nonlinear elliptic problem with Neumann-type boundary data. The problem is driven by a discontinuous power nonlinearity and a nonsmooth prescribed data. Additionally, we aim to derive an estimate that proves the well-posedness of the problem. This estimate serves as an evidence for the un

Paul D. Nation, Abdullah Ash Saki, Hwajung Kang

We present a framework for computing the solution to Hamiltonian eigenproblems in a subspace defined by bit-strings sampled from a quantum computer. Hamiltonians are represented using an extended alphabet that includes projection and ladder operators, yielding a unified solution method for qubit and fermionic systems. Operators are grouped and sorted so that

Thomas Rahab Lacroix, Pierre Lemaire, Anne-Marie Lagrange, Julien Milli

The observation of celestial objects is a fundamental activity in astronomy. Ground-based and space telescopes are used to gather electromagnetic radiation from space, allowing astronomers to study a wide range of celestial objects and phenomena, such as stars, planets, galaxies, and black holes. The European Southern Observatory (ESO) charges each night 83

Martina Ullasci, Marco Rondina, Riccardo Coppola, Flavio Giobergia

Many works in the literature show that LLM outputs exhibit discriminatory behaviour, triggering stereotype-based inferences based on the dialect in which the inputs are written. This bias has been shown to be particularly pronounced when the same inputs are provided to LLMs in Standard American English (SAE) and African-American English (AAE). In this paper,