arXiv papers from July 2025

Yihong Dong, Xue Jiang, Yongding Tao, Huanyu Liu

Reinforcement Learning with Verifiable Reward (RLVR) has significantly advanced the complex reasoning abilities of Large Language Models (LLMs). However, it struggles to break through the inherent capability boundaries of the base LLM, due to its essentially on-policy strategy coupled with LLM's immense action space and sparse reward. Critically, RLVR can le

Sam Bender, Christopher Beattie

Time-periodic dynamical systems occur commonly both in nature and as engineered systems. Large-scale linear time-periodic dynamical systems, for example, may arise through linearization of a nonlinear system about a given periodic solution (possibly as a consequence of a baseline periodic forcing) with subsequent spatial discretization. The potential need to

Rana Aref Salama, Abdou Youssef, Mona Diab

Wavelet transforms, a powerful mathematical tool, have been widely used in different domains, including Signal and Image processing, to unravel intricate patterns, enhance data representation, and extract meaningful features from data. Tangible results from their application suggest that Wavelet transforms can be applied to NLP capturing a variety of linguis

Bo Yang, Xingquan Li, Jie Zhao, Ying Jiang

In certain practical engineering applications, there is an urgent need to perform repetitive solving of partial differential equations (PDEs) in a short period. This paper primarily considers three scenarios requiring extensive repetitive simulations. These three scenarios are categorized based on whether the geometry, boundary conditions(BCs), or parameters

Cameron Ake, Spencer F. Lewis, Amanda Louie, Andrés R. Vindas-Meléndez

We show that all stack-sorting polytopes are simplices. Furthermore, we show that the stack-sorting polytopes generated from $Ln1$ permutations have relative volume 1. We establish an upper bound for the number of lattice points in a stack-sorting polytope. In particular, stack-sorting polytopes generated from $2Ln1$ permutations have no interior points.

Aymane Abdali, Bartosz Boguslawski, Lucas Drumetz, Vincent Gripon

In the domain of Few-Shot Image Classification, operating with as little as one example per class, the presence of image ambiguities stemming from multiple objects or complex backgrounds can significantly deteriorate performance. Our research demonstrates that incorporating additional information about the local positioning of an object within its image mark

Xiaofeng Wu, Alan Ritter, Wei Xu

Tables have gained significant attention in large language models (LLMs) and multimodal large language models (MLLMs) due to their complex and flexible structure. Unlike linear text inputs, tables are two-dimensional, encompassing formats that range from well-structured database tables to complex, multi-layered spreadsheets, each with different purposes. Thi

Wei Tao, Jing Ning, Wen Li, Wenyaw Chan

The predictiveness curve is a valuable tool for predictive evaluation, risk stratification, and threshold selection in a target population, given a single biomarker or a prediction model. In the presence of competing risks, regression models are often used to generate predictive risk scores or probabilistic predictions targeting the cumulative incidence func

Shugang Hao, Hongbo Li, Lingjie Duan

The binary exponential backoff scheme is widely used in WiFi 7 and still incurs poor throughput performance under dynamic channel environments. Recent model-based approaches (e.g., non-persistent and $p$-persistent CSMA) simply optimize backoff strategies under a known and fixed node density, still leading to a large throughput loss due to inaccurate node de

Lucien Jezequel, Jens H. Bardarson, Adolfo G. Grushin

Topological band insulators are classified using momentum-space topological invariants, such as Chern or winding numbers, when they feature translational symmetry. The lack of translation symmetry in disordered, quasicrystalline, or amorphous topological systems has motivated alternative, real-space definitions of topological invariants, including the local

Shayan Jalilian, Abdul Bais

The Segment Anything Model (SAM) has demonstrated impressive generalization in prompt-based segmentation. Yet, the potential of semantic text prompts remains underexplored compared to traditional spatial prompts like points and boxes. This paper introduces SAM-PTx, a parameter-efficient approach for adapting SAM using frozen CLIP-derived text embeddings as c

J. Fernando Hernandez-Garcia, Shibhansh Dohare, Jun Luo, Rich S. Sutton

Loss of plasticity is a phenomenon in which a neural network loses its ability to learn when trained for an extended time on non-stationary data. It is a crucial problem to overcome when designing systems that learn continually. An effective technique for preventing loss of plasticity is reinitializing parts of the network. In this paper, we compare two diff

Esen K. Tütüncü, Mar Gonzalez-Franco, Eric J. Gonzalez

We present HandOver, an extended reality (XR) interaction technique designed to unify the precision of traditional mouse input for object selection with the expressiveness of hand-tracking for object manipulation. With HandOver, the mouse is used to drive a depth-aware 3D cursor enabling precise and restful targeting -by hovering their hand over the mouse, t

Sara Helal, Victor Elvira

Estimating rare events in complex systems is a key challenge in reliability analysis. The challenge grows in multimodal problems, where traditional methods often rely on a small set of design points and risk overlooking critical failure modes. Further, higher dimensions make the probability mass harder to capture and demand substantially larger sample sizes

F. Pozo Nuñez, E. Bañados, S. Panda, J. Heidt

Powered by supermassive black holes at their centers, quasars are among the most luminous objects in the Universe, serving as important probes of cosmic history and galaxy evolution. The size of the accretion disc surrounding the black hole is a critical parameter for understanding quasar physics and their potential use as standard candles in cosmology. Howe

So Katagiri, Yoshiki Matsuoka, Akio Sugamoto

We present a theoretical framework for non-equilibrium thermodynamics, termed Nambu Non-equilibrium Thermodynamics (NNET), which unifies reversible dynamics described by the Nambu bracket and irreversible processes driven by entropy gradients. The formulation provides a covariant description of systems far from equilibrium, where entropy may transiently decr

Esteban G. Tabak, Giulio Trigila, Wenjun Zhao

This paper presents a new method for conditional probability density simulation. The method is design to work with unstructured data set when data are not characterized by the same covariates yet share common information. Specific examples considered in the text are relative to two main classes: homogeneous data characterized by samples with missing value fo

Xiangyu Kong, Hengde Zhu, Haoqin Sun, Zhihao Guo

Automatic real personality recognition (RPR) aims to evaluate human real personality traits from their expressive behaviours. However, most existing solutions generally act as external observers to infer observers' personality impressions based on target individuals' expressive behaviours, which significantly deviate from their real personalities and consist

F. Wu, C. Andreoiu, V. Karayonchev, C. M. Petrache

The lifetime of the $0^+_3$ state in $^{120}$Sn was measured for the first time applying the fast-timing technique following thermal neutron capture. The mean lifetime of $\tau = 50(7)$~ps leads to a $E0$ transition strength of $10^3\times \rho^2(E0;0^+_3\rightarrow0^+_2) = 120(50)$, suggesting shape coexistence and a high degree of mixing between the $0^+_2

Erdem Sucu, Suat Dengiz, İzzet Sakallı

We investigate the thermodynamic properties of black holes in Conformal Weyl Gravity (CWG) using the Mannheim-Kazanas solution, with particular emphasis on quantum corrections that become significant near the Planck scale. Our analysis employs the Hamilton-Jacobi tunneling formalism to derive the Hawking temperature, revealing explicit contributions from the

Ecem Bozkurt, Antonio Ortega

Foundation models (FMs) pretrained on large datasets have become fundamental for various downstream machine learning tasks, in particular in scenarios where obtaining perfectly labeled data is prohibitively expensive. In this paper, we assume an FM has to be fine-tuned with noisy data and present a two-stage framework to ensure robust classification in the p

Mehdi Ben Ayed, Fei Feng, Jay Adams, Vishwakarma Singh

Existing web-scale recommendation systems commonly use supervised learning methods that prioritize immediate user feedback. Although reinforcement learning (RL) offers a solution to optimize longer-term goals, such as in-session engagement, applying it at web scale is challenging due to the extremely large action space and engineering complexity. In this pap

Saurabh Rane

Formula 1 performance is a combination of the car's ability and the driver's ability. While a given race or season can tell you how well a car and driver performed jointly, isolating the individual impact of the driver and constructor remains challenging. This paper extends a Regularized Adjusted Plus Minus (RAPM) methodology (Sill 2010), commonly used in ba

Chris Hull, Neil Lambert

Sen's action for chiral bosons in 2 dimensions describes two chiral scalars, one of which couples to the physical metric and one of which couples to a flat metric. It has a generalisation in which the flat metric is replaced by an arbitrary second metric and so can be formulated on any curved world-sheet. When the two metrics are equal, the theory reduces to

Cleyton Magalhaes, Italo Santos, Brody Stuart-Verner, Ronnie de Souza Santos

Background: Software systems powered by large language models are becoming a routine part of everyday technologies, supporting applications across a wide range of domains. In software engineering, many studies have focused on how LLMs support tasks such as code generation, debugging, and documentation. However, there has been limited focus on how full system

Eric Mjolsness, Cory B. Scott

Graphs, and sequences of growing graphs, can be used to specify the architecture of mathematical models in many fields including machine learning and computational science. Here we define structured graph "lineages" (ordered by level number) that grow in a hierarchical fashion, so that: (1) the number of graph vertices and edges increases exponentially in le

Tran N. K. Linh, Le Ngoc Long

Given a 0-dimensional scheme $\X$ in $\mathbb{P}^n_K$ over a perfect field $K$, we examine the second differential power of its homogeneous vanishing ideal. This enables us to establish the canonical exact sequence for the associated K\"ahler differential module. We also provide a formula for the Hilbert polynomial of K\"ahler differential modules when $\X$

Jeremy Borden, Yuri V. Kovchegov

We construct an exact analytic solution of the revised small-$x$ helicity evolution equations, where the contributions of the quark-to-gluon and gluon-to-quark transition operators were newly included. These evolution equations are written in the large-$N_c\&N_f$ limit and are double-logarithmic, resumming powers of $\alpha_s\ln^2(1/x)$. Here $N_c$ and $N_f$

Fırat Öncel, Emiliano Penaloza, Haolun Wu, Shubham Gupta

Traditional recommendation systems represent user preferences in dense representations obtained through black-box encoder models. While these models often provide strong recommendation performance, they lack interpretability for users, leaving users unable to understand or control the system's modeling of their preferences. This limitation is especially chal

Yuxi Xie, Ethan J. Wu, Lu Xu, Jimmy Perez

This work presents a practical finite element modeling strategy, the Crack Element Method (CEM), for simulating the dynamic crack propagation in two-dimensional structures. The method employs an element-splitting algorithm based on the Edge-based Smoothed Finite Element Method (ES-FEM) to capture the element-wise crack growth while reducing the formation of

Chao Yang, Zhujun Zhang

Translational tiling problems are among the most fundamental and representative undecidable problems in all fields of mathematics. Greenfeld and Tao obtained two remarkable results on the undecidability of translational tiling in recent years. One is the existence of an aperiodic monotile in a space of sufficiently large dimension. The other is the undecidab

Kevin S. Chen, Andrew M. Leifer, Jonathan W. Pillow

Animals employ different strategies for relating sensory input to behavioral output to navigate sensory environments, but what strategy to use, when to switch and why remain unclear. In C. elegans, navigation is composed of 'steering' and 'turns', corresponding to small heading changes and large reorientation events, respectively. It is unclear whether trans

Larissa Albantakis

Toy models are highly idealized and deliberately simplified models that retain only the essential features of a system in order to explore specific theoretical questions. Long used in physics and other sciences, they have recently begun to play a more visible role in consciousness research. This chapter examines the potential utility of toy models for develo

Toshikazu Miyashita

There exist six Lie groups of type $ E_6 $, and to be specific, ${E_6}^C , E_6, E_{6(6)}, E_{6(-2)}, E_{6(-14)}, E_{6(-26)}$. In order to define these groups, we use usually the Cayley algebra $ \mathfrak{C} $ and the split Cayley algebra $ \mathfrak{C}' $. In the present article, we consider the Lie groups which are defined by replacing $ \mathfrak{C}^C, \m

Nicolas Frantz, Michał Wrochna

We consider a model for internal waves described by a zero order pseudo-differential Hamiltonian $P$ damped by a second order viscosity term $i \nu Q$. Under Morse-Smale or similar weaker global conditions on the classical dynamics, we describe qualitatively the long-time behavior of solutions of the corresponding evolution equation with smooth forcing in a

Renyan Sun, Ashutosh Nayyar

We consider a finite-horizon discrete-time dynamic system jointly controlled by a designer and one or more agents, where the designer can influence the agents' actions through selective information disclosure. At each time step, the designer sends a message to the agent(s) from a prespecified message space. The designer may also take an action that directly

Anas Abu-Odeh, James Warren

Accurate models of precipitation kinetics are essential to control and design structural materials. These models are highly sensitive to the thermodynamic description of precipitates. We use atomistic simulations of a model Fe-Cr system to assess two commonly used assumptions in the thermodynamic modeling of coherent precipitates: that elastic effects can be

Alper Yaman, Jannik Schwab, Christof Nitsche, Abhirup Sinha

Large Language Models (LLMs), such as Generative Pre-trained Transformers (GPTs) are revolutionizing the generation of human-like text, producing contextually relevant and syntactically correct content. Despite challenges like biases and hallucinations, these Artificial Intelligence (AI) models excel in tasks, such as content creation, translation, and code

Maxim Prasolov

We prove that any biLipschitz mapping of the boundary of the unit disk onto the boundary of the domain of the same area can be extended to a biLipschitz mapping of the whole plane which preserves the area of any measurable subset.

Ching-Fang Li, Mary Wootters

Consider the problem of computing quantized linear functions with only a few queries. Formally, given $\mathbf{x}\in \mathbb{R}^k$, our goal is to encode $\mathbf{x}$ as $\mathbf{c} \in \mathbb{R}^n$, for $n > k$, so that for any $\mathbf{w} \in A^k$, $\mathbf{w}^T \mathbf{x}$ can be computed using at most $\ell$ queries to $\mathbf{c}$. Here, $A$ is some fi

A. D. Kazakova, M. G. Plotnikov

A family of M-sets and null-series for the d-dimensional Walsh system is constructed if we consider convergence over rectangles, cubes, or iterated convergence. Non-empty portions of the constructed M-sets are also M-sets. The question of the rate of convergence to zero of the coefficients of zero-series that realize the constructed M-sets is studied, and it

Ying Zhang, Niklas Groene, Karsten Klein, Giuseppe Liotta

Human perception of graph drawings is influenced by a variety of impact factors for which quality measures are used as a proxy indicator. The investigation of those impact factors and their effects is important to evaluate and improve quality measures and drawing algorithms. The number of edge crossings in a 2D graph drawing has long been a main quality meas

Ramón Flores, Elisenda Molina, Juan Tejada

This paper develops a novel methodological framework for assessing leadership potential and productivity within organisational structure represented by directed graphs. In this setting, individuals are modeled as nodes and asymmetric supervisory or reporting relationships as directed edges. Leveraging the theory of transferable utility cooperative games, we

Adam Block, Cyril Zhang

Stochasticity in language model fine-tuning, often caused by the small batch sizes typically used in this regime, can destabilize training by introducing large oscillations in generation quality. A popular approach to mitigating this instability is to take an Exponential moving average (EMA) of weights throughout training. While EMA reduces stochasticity, th

Keisi Kacanja, Kanchan Soni, Alexander Harvey Nitz

Measurement of eccentricity in low-mass binary systems through gravitational waves is crucial to distinguish between various formation channels. Detecting eccentricity in these systems is challenging due to a lack of accurate eccentric waveform models and the high computational cost of Bayesian inferences. We access the eccentricities of six previously obser

Brian Houck, Travis Lowdermilk, Cody Beyer, Steven Clarke

As artificial intelligence (AI) tools become increasingly embedded in software development workflows, questions persist about their true impact on developer productivity and experience. This paper presents findings from a mixed-methods study examining how developers perceive AI's influence across the dimensions of the SPACE framework: Satisfaction, Performan

Thomas Konings, Linus Heinke, Robin Baeyens, Kaustubh Hakim

Observations of WASP-107b suggest a metal-rich and carbon-deprived atmosphere with an extremely hot interior based on detections of SO$_2$, H$_2$O, CO$_2$, CO, NH$_3$, and CH$_4$. In this paper, we aim to determine the reliability of a 1D radiative-convective photochemical-equilibrium (1D-RCPE) retrieval method in inferring atmospheric properties of WASP-107

Ping-Han Huang, Ming-Hung Kao

Efficient data collection is essential in applied studies where frequent measurements are costly, time-consuming, or burdensome. This challenge is especially pronounced in functional data settings, where each subject is observed at only a few time points due to practical constraints. Most existing design approaches focus on selecting optimal time points for

Jose Guadalupe Romero, Romeo Ortega, Leyan Fang, Alexey Bobtsov

Friction is an unavoidable phenomenon that exists in all mechanical systems incorporating parts with relative motion. It is well-known that friction is a serious impediment for precise servo control, hence the interest to devise a procedure to compensate for it -- a subject that has been studied by many researchers for many years. The vast majority of fricti

Yongchao Huang

Standard regression techniques, while powerful, are often constrained by predefined, differentiable loss functions such as mean squared error. These functions may not fully capture the desired behavior of a system, especially when dealing with asymmetric costs or complex, non-differentiable objectives. In this paper, we explore an alternative paradigm: frami

Kevin Braga, Nobuo Sato, Adam P. Szczepaniak

We present a variational neural network approach for solving quantum field theories in the field basis, focusing on the free Klein-Gordon model formulated in momentum space. While recent studies have explored neural-network-based variational methods for scalar field theory in position space, a systematic benchmark of the analytically solvable Klein-Gordon gr

Fupei Guo, Hao Zheng, Xiang Zhang, Li Chen

The rapid development of artificial intelligence has driven smart health with next-generation wireless communication technologies, stimulating exciting applications in remote diagnosis and intervention. To enable a timely and effective response for remote healthcare, efficient transmission of medical data through noisy channels with limited bandwidth emerges

David Restrepo, Ira Ktena, Maria Vakalopoulou, Stergios Christodoulidis

Clinical decision-making relies on the integrated analysis of medical images and the associated clinical reports. While Vision-Language Models (VLMs) can offer a unified framework for such tasks, they can exhibit strong biases toward one modality, frequently overlooking critical visual cues in favor of textual information. In this work, we introduce Selectiv

ShivaSankar K. A., Alakabha Datta, Danny Marfatia

Some of the simplest models for the origin of neutrino mass involve right-handed neutrinos (RHNs), which could be either Dirac or Majorana particles - a distinction that has profound implications for lepton number conservation and the fundamental nature of neutrinos. We investigate the potential of the FASER experiment to distinguish between these two possib

Bhavya Goyal, Felipe Gutierrez-Barragan, Wei Lin, Andreas Velten

LiDAR-based 3D sensors provide point clouds, a canonical 3D representation used in various scene understanding tasks. Modern LiDARs face key challenges in several real-world scenarios, such as long-distance or low-albedo objects, producing sparse or erroneous point clouds. These errors, which are rooted in the noisy raw LiDAR measurements, get propagated to

Ethan A. Vo, Timothy C. Berkelbach

We report the core binding energies of K-edge and L-edge transitions in simple semiconducting and insulating solids using periodic equation-of-motion coupled-cluster theory with single and double excitations (EOM-CCSD). In our all-electron calculations, we use triple zeta basis sets with core correlation, and we sample the Brillouin zone using up to 4x4x4 k-

Rui Zhang, Oksana A. Chkrebtii, Dongbin Xiu

Generative models and those with computationally intractable likelihoods are widely used to describe complex systems in the natural sciences, social sciences, and engineering. Fitting these models to data requires likelihood-free inference methods that explore the parameter space without explicit likelihood evaluations, relying instead on sequential simulati

Volker Bosserhoff

We give an example of a computably enumerable closed subset of [0,1] that is not homeomorphic to any computably compact space. This answers a question of Koh, Melnikov and Ng.

Radosław Czaja, Piotr Kalita, Alexandre N. Oliveira-Sousa

We use the version of the Lyapunov--Perron method operating on individual solutions to investigate the existence of invariant manifolds for non-autonomous dynamical systems, focusing in particular on inertial and stable manifolds. We establish a characterization of both types of manifolds in terms of solutions exhibiting a common growth behavior, analogous t

Sourya Sengupta, Jianquan Xu, Phuong Nguyen, Frank J. Brooks

Virtual staining, or in-silico-labeling, has been proposed to computationally generate synthetic fluorescence images from label-free images by use of deep learning-based image-to-image translation networks. In most reported studies, virtually stained images have been assessed only using traditional image quality measures such as structural similarity or sign

Fadoua Balabdaoui, Harald Besdziek, Yong Wang

We consider the problem of estimating a mixture of power series distributions with infinite support, to which belong very well-known models such as Poisson, Geometric, Logarithmic or Negative Binomial probability mass functions. We consider the nonparametric maximum likelihood estimator (NPMLE) and show that, under very mild assumptions, it converges to the

Tobias Kyrion

In this work we study integrals of the form $\int_{0}^{\infty}\frac{\tanh(x)}{x}\mathrm{sech}(x)^{L}\exp(-Tx)dx$. For $L \in \mathbb{N}$, $L \leq 4$ and $T \in \mathbb{R}$ we give explicit expressions in terms of derivatives of the Hurwitz zeta function at negative integers. We use these expressions to evaluate these integrals for $T \in \mathbb{N}_{0}$ exac

Luis Vitor Zerkowski, Nina S. T. Hirata

Indigenous communities face ongoing challenges in preserving their cultural heritage, particularly in the face of systemic marginalization and urban development. In Brazil, the Museu Nacional dos Povos Indigenas through the Tainacan platform hosts the country's largest online collection of Indigenous objects and iconographies, providing a critical resource f

Noboru Myers, Obin Kwon, Sankalp Yamsani, Joohyung Kim

Recent advances in teleoperation have demonstrated robots performing complex manipulation tasks. However, existing works rarely support whole-body joint-level teleoperation for humanoid robots, limiting the diversity of tasks that can be accomplished. This work presents Controller for Humanoid Imitation and Live Demonstration (CHILD), a compact reconfigurabl

Ziqian Zhong, Aditi Raghunathan

The releases of powerful open-weight large language models (LLMs) are often not accompanied by access to their full training data. Existing interpretability methods, particularly those based on activations, often require or assume distributionally similar data. This is a significant limitation when detecting and defending against novel potential threats like

Igor Rivin

We computationally resolve an open problem concerning the expressibility of $4 \times 4$ full-rank matrices as Hadamard products of two rank-2 matrices. Through exhaustive search over $\mathbb{F}_2$, we identify 5,304 counterexamples among the 20,160 full-rank binary matrices (26.3\%). We verify that these counterexamples remain valid over $\mathbb{Z}$ throu

Ziqing Xu, Nick Bryan-Kinns

Many existing AI music generation tools rely on text prompts, complex interfaces, or instrument-like controls, which may require musical or technical knowledge that non-musicians do not possess. This paper introduces DeformTune, a prototype system that combines a tactile deformable interface with the MeasureVAE model to explore more intuitive, embodied, and

Jobst Heitzig, Ram Potham

Power is a key concept in AI safety: power-seeking as an instrumental goal, sudden or gradual disempowerment of humans, power balance in human-AI interaction and international AI governance. At the same time, power as the ability to pursue diverse goals is essential for wellbeing. This paper explores the idea of promoting both safety and wellbeing by forcing

Mike Pols, Helena Boom, Geert Brocks, Sofía Calero

Chiral two-dimensional (2D) halide perovskites are formed by embedding chiral organic cations in a perovskite crystal structure. The chirality arises from distortions of the 2D metal halide layers induced by the packing of these organic cations. Sn-based octahedra spontaneously distort, but it remains unclear whether this intrinsic structural instability enh

Jeremy L. Martin, May B. Trist

A MacMahon symmetric function is an invariant of the diagonal action of the symmetric group on power series in multiple alphabets of variables. We introduce an analogue of the chromatic symmetric function for vertex-weighted graphs, taking values in the MacMahon symmetric functions on two sets of variables, recording information about both cardinalities and

Shuhao Qi, Zhiqi Tang, Zhiyong Sun, Sofie Haesaert

As the airspace becomes increasingly congested, decentralized conflict resolution methods for airplane encounters have become essential. While decentralized safety controllers can prevent dangerous midair collisions, they do not always ensure prompt conflict resolution. As a result, airplane progress may be blocked for extended periods in certain situations.

Tomasz Szczepański, Szymon Płotka, Michal K. Grzeszczyk, Arleta Adamowicz

Tooth segmentation in Cone-Beam Computed Tomography (CBCT) remains challenging, especially for fine structures like root apices, which is critical for assessing root resorption in orthodontics. We introduce GEPAR3D, a novel approach that unifies instance detection and multi-class segmentation into a single step tailored to improve root segmentation. Our meth

Babak Esmaeili, Hamidreza Modares, Stefano Di Cairano

This paper proposes a data-driven motion-planning framework for nonlinear systems that constructs a sequence of overlapping invariant polytopes. Around each randomly sampled waypoint, the algorithm identifies a convex admissible region and solves data-driven linear-matrix-inequality problems to learn several ellipsoidal invariant sets together with their loc

Jorge Garcia, Jasmine Torres, Thomas Crawford, Miles Obrien

After analyzing the 4x4 determinant of a matrix, a shortcut was obtained to find such a determinant. Similarly to the Sarrus method for 2x2 or 3x3 determinants, the method consists of laying 19 columns of size 4 each and adding and subtracting some diagonal multiplications. There is a symmetry in the arrangement of these columns. A very symmetric pattern eme

Sayed Mahbub Hasan Amiri, Prasun Goswami, Md. Mainul Islam, Mohammad Shakhawat Hossen

Green computing represents a critical pathway to decarbonize the digital economy while maintaining technological progress. This article examines how sustainable IT strategies including energy-efficient hardware, AI-optimized data centres, and circular e-waste systems can transform computing into a net carbon sink. Through analysis of industry best practices

Li Mi, Manon Bechaz, Zeming Chen, Antoine Bosselut

Active Geo-localization (AGL) is the task of localizing a goal, represented in various modalities (e.g., aerial images, ground-level images, or text), within a predefined search area. Current methods approach AGL as a goal-reaching reinforcement learning (RL) problem with a distance-based reward. They localize the goal by implicitly learning to minimize the

Faruk Alpay, Hamdi Al Alakkad

The Ordinal Folding Index (OFI) is a new, fully computable yard-stick that measures how many rounds of self-reference a statement, protocol or position must unfold before its truth or outcome stabilises. By turning this abstract 'fold-back' depth into a single ordinal number, OFI forges a direct link between areas that are usually studied in isolation: the c

Poulami Chatterjee, Cesar Nieto, Juan Manuel Pedraza, Abhyudai Singh

A population of individuals with the same genes can present heterogeneous traits (phenotypes). The prevalence of this heterogeneity can be explained as a bet-hedging strategy that improves the population proliferation rate (fitness) in fluctuating environments. The phenotype distribution is influenced by factors such as competition between phenotypes, the du

Katinka den Nijs, Elisa Omodei, Vedran Sekara

Large-scale human mobility datasets play increasingly critical roles in many algorithmic systems, business processes and policy decisions. Unfortunately there has been little focus on understanding bias and other fundamental shortcomings of the datasets and how they impact downstream analyses and prediction tasks. In this work, we study `data production', qu

Ognian Kassabov, Velichka Milousheva

In the present paper, we study surfaces in the four-dimensional Euclidean space $\mathbb{R}^4$. We define special principal parameters, which we call canonical, on each surface without minimal points, and prove that the surface admits (at least locally) canonical principal parameters. They can be considered as a generalization of the canonical parameters for

Bernhard Albach

We prove that for any reversible Finsler metric on S2, the number of prime closed geodesics grows quadratically with respect to length. The main tools are an improvement on Franks' theorem about the number of periodic points of area-preserving annulus maps, and the theory of cylindrical contact homology in the complement of a link.

Felipe Huenchuguala, Luis Fuenzalida, Oscar Orellana, Arne Scholtissek

Solving the spray flamelet equations in composition space is very challenging, which is attributable to the fact that the maximum value of the mixture fraction, $Z_\mathrm{max}$, is a priori unknown in such flames. In this work, an analytical solution for this quantity is proposed, which allows its determination in spray flames subject to imposed quadratic e

Akshat Rakheja, Aarsh Ashdhir, Aryan Bhattacharjee, Vanshika Sharma

We introduce World Consistency Score (WCS), a novel unified evaluation metric for generative video models that emphasizes internal world consistency of the generated videos. WCS integrates four interpretable sub-components - object permanence, relation stability, causal compliance, and flicker penalty - each measuring a distinct aspect of temporal and physic

Cory B. Scott, Charlie Rothschild, Benjamin Nye

We introduce a pipeline for representing a protein, or protein complex, as the union of signed distance functions (SDFs) by representing each atom as a sphere with the appropriate radius. While this idea has been used previously as a way to render images of proteins, it has not, to our knowledge, been widely adopted in a machine learning setting. Mirroring r

Danielle R. Thomas, Conrad Borchers, Kenneth R. Koedinger

Humans can be notoriously imperfect evaluators. They are often biased, unreliable, and unfit to define "ground truth." Yet, given the surging need to produce large amounts of training data in educational applications using AI, traditional inter-rater reliability (IRR) metrics like Cohen's kappa remain central to validating labeled data. IRR remains a corners

H. Liu, L. S. Moreu, T. S. Andersen, V. V. Puche

The increasing demand for critical raw materials has revitalized interest in abandoned underground mines, which pose extreme challenges for conventional drilling machinery due to confined, unstructured, and infrastructure-less environments. This paper presents the Stinger Robot, a novel compact robotic platform specifically designed for autonomous high-force

Rahul Gupta, Judith L. Racusin, R. Sanchez-Ramirez, Y. Hu

We present a comprehensive multiwavelength analysis of GRB 240825A, a bright gamma-ray burst (GRB) detected by Fermi and Swift, with a prompt duration ($T_{\rm 90}$ ~ 4 sec in 50-300 keV) near the boundary separating short and long GRBs, prompting a detailed investigation into its classification and progenitor. Using classical prompt metrics (duration, minim

Mohit Gupta, Debjit Bhowmick, Rhys Newbury, Meead Saberi

Accurate link-level bicycling volume estimation is essential for sustainable urban transportation planning. However, many cities face significant challenges of high data sparsity due to limited bicycling count sensor coverage. To address this issue, we propose INSPIRE-GNN, a novel Reinforcement Learning (RL)-boosted hybrid Graph Neural Network (GNN) framewor

Zhanna Kaufman, Madeline Endres, Cindy Xiong Bearfield, Yuriy Brun

Systems relying on ML have become ubiquitous, but so has biased behavior within them. Research shows that bias significantly affects stakeholders' trust in systems and how they use them. Further, stakeholders of different backgrounds view and trust the same systems differently. Thus, how ML models' behavior is explained plays a key role in comprehension and

Christian W. Binder, Guido Burkard, Andrew J. Fisher

We present a rigorous method to reduce the three-dimensional (3D) description of a quantum dot in silicon to an effective two-dimensional (2D) envelope function theory for electron spin qubits. By systematically integrating out the strongly confined vertical dimension using a Born-Oppenheimer-inspired ansatz at the envelope-function level, we derive an effec

Rashid Mushkani, Hugo Berard, Toumadher Ammar, Cassandre Chatonnier

Despite efforts to mitigate the inherent risks and biases of artificial intelligence (AI) algorithms, these algorithms can disproportionately impact culturally marginalized groups. A range of approaches has been proposed to address or reduce these risks, including the development of ethical guidelines and principles for responsible AI, as well as technical s

Shqiponja Ahmetaj, George Konstantinidis, Magdalena Ortiz, Paolo Pareti

SHACL (SHApe Constraint Language) is a W3C standardized constraint language for RDF graphs. In this paper, we study SHACL validation in RDF graphs under updates. We present a SHACL-based update language that can capture intuitive and realistic modifications on RDF graphs and study the problem of static validation under such updates. This problem asks to veri

Kecheng Li

We investigate the thermodynamic formalism for Viana maps-skew products obtained by coupling an expanding circle map with a slightly perturbed quadratic family on the fibers. For every H\"older potential $\varphi$ whose oscillation is below an explicit threshold, we show that an equilibrium state not only exists but is unique and satisfies an upper level-2 l

Basna Mohammed Salih Hasan, Ramadhan J. Mstafa

Gender classification has emerged as a crucial aspect in various fields, including security, human-machine interaction, surveillance, and advertising. Nonetheless, the accuracy of this classification can be influenced by factors such as cosmetics and disguise. Consequently, our study is dedicated to addressing this concern by concentrating on gender classifi

James Cruickshank, Sean Dewar, Derek Kitson

The algebraic connectivity of a graph $G$ in a finite dimensional real normed linear space $X$ is a geometric counterpart to the Fiedler number of the graph and can be regarded as a measure of the rigidity of the graph in $X$. We analyse the behaviour of the algebraic connectivity of $G$ in $X$ with respect to graph decomposition, vertex deletion and isometr

Michele Schiavina, Jonas Schnitzer

Consider the variational bicomplex for $\mathcal{E}$ the space of sections of a graded, affine bundle. Local functionals $\mathcal{F}$ are defined as an equivalence class of density-valued functionals, which represent Lagrangian densities. A choice of a $k$-symplectic local form $\omega$ on $\mathcal{E}$ induces a Lie$[k]$ algebra structure on (Hamiltonian)

Christine Cho, James Oxley, Suijie Wang

If $C_1$ and $C_2$ are circuits in a matroid $M$ with $e_1$ in $C_1-C_2$ and $e$ in $C_1\cap C_2$, then $M$ has a circuit $C_3$ such that $e\in C_3\subseteq (C_1\cup C_2)-e$. This strong circuit elimination axiom is inherently asymmetric. A matroid $M$ has the symmetric strong circuit elimination property (SSCE) if, when the above conditions hold and $e_2\in

Christopher Harvey, Sumaiya Shomaji, Zijun Yao, Amit Noheria

The electrocardiogram (ECG) is an inexpensive and widely available tool for cardiac assessment. Despite its standardized format and small file size, the high complexity and inter-individual variability of ECG signals (typically a 60,000-size vector with 12 leads at 500 Hz) make it challenging to use in deep learning models, especially when only small trainin

Drew Gao, Yihang Sun, Jan Vondrák

Approval-based committee selection is a model of significant interest in social choice theory. In this model, we have a set of voters $\mathcal{V}$, a set of candidates $\mathcal{C}$, and each voter has a set $A_v \subset \mathcal{C}$ of approved candidates. For any committee size $K$, the goal is to choose $K$ candidates to represent the voters' preferences

Agustín Borda, Juan Bautista Cabral, Gonzalo Giarda, Diego Nicolás Gimenez Irusta

In Multi-Criteria Decision Analysis, Rank Reversals are a serious problem that can greatly affect the results of a Multi-Criteria Decision Method against a particular set of alternatives. It is therefore useful to have a mechanism that allows one to measure the performance of a method on a set of alternatives. This idea could be taken further to build a glob