March 2026 arXiv papers — page 23

Matteo Rucco

We present a computational framework for characterizing the molecular self-organization of cocoa butter (Theobroma cacao) during dark chocolate tempering through the lens of Topological Data Analysis (TDA). A physics-inspired particle simulation models N=100 triglyceride molecules across the full temperature range 15--60 degrees C, spanning all six crystalli

Anas S. Mohammed, Krishnendu S. Tharakan, Hussein A. Ammar, Hesham ElSawy

The deployment of ultra-dense networks (UDNs), particularly cell-free massive MIMO (CF-mMIMO), is mainly hindered by costly and capacity-limited fronthaul links. This work proposes a two-tiered optimization framework for cost-effective hybrid fronthaul planning, comprising a Near-Optimal Fronthaul Association and Configuration (NOFAC) algorithm in the first

Wanqi Sun, Jungang Xu, Chenghua Duan

Embedding high-dimensional data into resource-limited quantum devices remains a significant challenge for practical quantum machine learning. In multimodal face anti-spoofing, while linear compression methods such as principal component analysis can reduce dimensionality to accommodate limited quantum budgets, such approaches often lose critical high-order c

Alexandre Bispo, Renato Macedo, Joedson Santos

In this paper we present a new criterion to determine when the normalized Haar measure on a compact topological group is a Pietsch measure for nonlinear summing mappings. As a consequence, we provide a partial answer to a problem raised by Botelho et al. in \cite{haar botelho} motivated by a question posed to the authors by J. Diestel. It is explicitly shown

Zimu Wang, Yuling Shi, Mengfan Li, Zijun Liu

Code efficiency is a fundamental aspect of software quality, yet how to harness large language models (LLMs) to optimize programs remains challenging. Prior approaches have sought for one-shot rewriting, retrieved exemplars, or prompt-based search, but they do not explicitly distill reusable optimization knowledge, which limits generalization beyond individu

Jayrylle R. Jaylo, Mia Chastain, Alli Nemec, Christina S. Ouch

Little is known about the representations used in qualitative research studies and why. A data-driven literature review was employed to explore the use of media in qualitative research reporting. A study by Verdinelli & Scagnoli (2013) was replicated and extended by conducting a content analysis of papers and figures published across three qualitative method

Boris Gulyak

We study the Willmore flow for graphs over a bounded domain in $\mathbb{R}^2$ with Dirichlet (clamped) boundary conditions, a still little-studied setting that also serves as a prototype for higher-order flows with fixed boundary data. We develop a low-regularity theory that avoids the classical fourth-order compatibility condition at $t=0$. Combining a refo

Tommaso Barbieri, Massimiliano Berti, Marco Mazzucchelli

We establish novel existence results of $3d$ gravity-capillary periodic traveling waves. In particular we prove the bifurcation of multiple, geometrically distinct truly $3d$ Stokes waves having the same momentum of any non-resonant $2d$ Stokes wave. This unexpected clustering phenomenon of Stokes waves, observed in physical fluids, is a fundamental conseque

Carlota Andres, Fabio Dominguez

Jets produced in relativistic heavy-ion collisions are modified by their interactions with the quark-gluon plasma (QGP), making jet substructure observables sensitive probes of QGP dynamics. A quantitative description of these modifications requires understanding how the medium affects elementary parton splittings with full dependence on both their energy fr

Alisson Serracín Morales, Buddhika Nettasinghe

Affective polarization, the emotional divide characterized by in-group love (trust towards fellow partisans) and out-group hate (mistrust towards those with opposite political views), has become prevalent in the current society. Despite its prevalence, the role of social network structure in the dynamics of affective polarization is yet to be well-understood

Natapong Nitarach

Majority voting over multiple LLM attempts improves mathematical reasoning, but correlated errors limit the effective sample size. A natural fix is to assign different reasoning strategies to different voters. The approach, Diverse Prompt Mixer, is tested on the AIMO 3 competition: 3 models, 23+ experiments, 50 IMO-level problems, one H100 80 GB, 5-hour limi

Hao Wu

Adapting Bauer and Furuta's constructions of the refinement of the Seiberg-Witten invariants, we establish the analogous stable cohomotopy refinement of the $Pin^{-}(2)$ monopole invariants proposed by Nakamura \cite{nakamura2015pin}, and give the corresponding connected sum formula.

Mehrab Mahdian, Ferenc Ender, Tamas Pardy

Electrospinning is a versatile nanofabrication technique whose outcomes emerge from a complex, high-dimensional interplay between solution properties, processing parameters, and environmental conditions. Optimizing this parameter space for targeted fiber morphology is inherently challenging, often driving extensive trial-and-error experimentation and generat

Haimi Jha, Hibah Saddal, Chandan Bose

Vortex-induced vibrations (VIV) remain a canonical yet complex manifestation of fluid-structure interactions, where coupled nonlinear dynamics govern the motion of bluff bodies. For several years, we have relied on traditional reduced-order mathematical models derived from empirical and oscillator-based formulations; however, such models often fail to reprod

Charles Audet, Youssef Diouane, Edward Hallé-Hannan, Sébastien Le Digabel

In simulation-based engineering, design choices are often obtained following the optimization of complex blackbox models. These models frequently involve mixed-variable domains with quantitative and categorical variables. Unlike quantitative variables, categorical variables lack an inherent structure, which makes them difficult to handle, especially in the p

Hadas Kotek, Margit Bowler, Patrick Sonnenberg, Yu'an Yang

We introduce ProText, a dataset for measuring gendering and misgendering in stylistically diverse long-form English texts. ProText spans three dimensions: Theme nouns (names, occupations, titles, kinship terms), Theme category (stereotypically male, stereotypically female, gender-neutral/non-gendered), and Pronoun category (masculine, feminine, gender-neutra

Artun Sel, Mehmet Koruturk, Erdi Sayar

This paper presents a novel method for estimating larger Region of Attractions (ROAs) for continuous-time nonlinear systems modeled via the Takagi-Sugeno (TS) framework. While classical approaches rely on a single TS representation derived from the original nonlinear system to compute an ROA using Lyapunov-based analysis, the proposed method enhances this pr

Runjia Zeng, Priyabrata Senapati, Ruixiang Tang, Dongfang Liu

Large language models have recently shown potential in bridging the gap between classical machine learning and quantum machine learning. However, the lack of standardized, high-quality datasets and robust translation frameworks limits progress in this domain. We introduce Q-Bridge, an LLM-guided code translation framework that systematically converts CML imp

Hans--Jürgen Bandelt, Victor Chepoi, Andreas Dress, Jack Koolen

Lopsided sets were introduced by Jim Lawrence in 1983 when he studied the subsets of $\{-1,+1\}^E$ that encode the intersection pattern of a convex set $K$ with the orthants of ${\mathbb R}^E$. Lopsided sets have been independently rediscovered by several other authors, in particular by Andreas Dress in 1995, who called them \emph{ample} sets. Dress defined

Nicolas Tricard, Zituo Chen, Sili Deng

Flame tomography is a compelling approach for extracting large amounts of data from experiments via 3-D thermochemical reconstruction. Recent efforts employing neural-network flame representations have suggested improved reconstruction quality compared with classical tomography approaches, but a rigorous quantitative comparison with the same algorithm using

Charlotte Priestley, Will Handley

As the population of anthropogenic space objects transitions from sparse clusters to mega-constellations exceeding 100,000 satellites, traditional orbital propagation techniques face a critical bottleneck. Standard CPU-bound implementations of the Simplified General Perturbations 4 (SGP4) algorithm are less well suited to handle the requisite scale of collis

Thomas Jannaud, Jonathan Ferreira, Claudio Zanni

It is generally accepted that the launching of astrophysical jets requires a large-scale magnetic field threading a central object (black hole or star) and/or its surrounding accretion disc. However, the collimation mechanism far away from the central object has not yet been fully understood. In a previous work we investigated a mechanism in which the jet is

Yue Zhao, Guosheng Fu, Huan Lei

We present a data-driven approach for constructing generalized collisional kinetic models for inhomogeneous plasmas in one-dimensional physical space and three-dimensional velocity space (1D-3V). The collision operator is directly learned from micro-scale molecular dynamics (MD) and accurately accounts for the unresolved particle interactions over a broad ra

Sylwia Kondej, Nikoloz Kurtskhalia

We consider a Dirichlet waveguide in $\mathbb{R}^n$ ($n = 2,3$) with an attached cavity. We show that if the cavity admits a small gap, then the original embedded eigenvalues turn into resonances. The main question we address is how the size of the gap affects the resonant properties, in particular the imaginary part of the resonant pole. For example, in the

Xuefeng Liu

We propose a rigorous method for computing two-sided eigenvalue bounds of the Schr\"odinger operator $H=-\Delta+V$ with a confining potential on $\mathbb{R}^2$. The method combines domain truncation to a finite disk $D(R)$ on which the restricted eigenvalue problem is solved with a rigorous eigenvalue bound, where Liu's eigenvalue bound along with the Compos

Pankaj Agrawal, Biswajit Das, Tousik Samui

Following the HL-LHC era, proposed lepton colliders highlight the need to study various important Higgs boson production mechanisms to precisely probe the Standard Model Higgs sector. We propose a novel mechanism $e^\pm \gamma \rightarrow {\bar \nu}_e (\nu_e) H W^\pm$, which can be useful to study Higgs boson properties. This channel is relatively free from

Vik Pant, Eric Yu

Strategic coopetition in multi-stakeholder systems requires understanding how cooperation persists through time without binding contracts. This technical report extends computational foundations for strategic coopetition to sequential interaction dynamics, bridging conceptual modeling (i* framework) with game-theoretic reciprocity analysis. We develop: (1) b

Zhiwen You, Xi Chen, Aniket Vashishtha, Simo Du

Clinical diagnosis is a complex reasoning process in which clinicians gather evidence, form hypotheses, and test them against alternative explanations. In medical training, this reasoning is explicitly developed through counterfactual questioning--e.g., asking how a diagnosis would change if a key symptom were absent or altered--to strengthen differential di

Bo Jiang, Sian Jin

KV cache compression is critical for efficient long-context LLM inference. Approaches that reduce the per-pair footprint -- quantization and low-rank decomposition -- are orthogonal to those that reduce the sequence length of the cache. Along the sequence-length dimension, existing methods range from pure eviction -- selecting which KV pairs to keep -- to me

Xiangzhong Liu, Hao Shen

Modern autonomous driving systems increasingly rely on mixed camera configurations with pinhole and fisheye cameras for full view perception. However, Bird's-Eye View (BEV) 3D object detection models are predominantly designed for pinhole cameras, leading to performance degradation under fisheye distortion. To bridge this gap, we introduce a multi-view BEV d

Robert Aufschläger, Jakob Folz, Gautam Savaliya, Manjitha D Vidanalage

Street-level imagery contains personally identifiable information (PII), some of which is context-dependent. Existing anonymization methods either over-process images or miss subtle identifiers, while API-based solutions compromise data sovereignty. We present an agentic framework CAIAMAR (\underline{C}ontext-\underline{A}ware \underline{I}mage \underline{A}

John Slane, Adam Mate

In recent years, the contribution of renewable energy resources to the electrical grid has increased drastically; the most common of these are photovoltaic solar panels and wind turbines. These resources rely on inverters to interface with the grid, which do not inherently exhibit the same fault characteristics as synchronous generators. Consistently, they c

Cristian Alexe, Aaron Liberman, Saga Westerberg, Andrea Angella

Accurate spatio-temporal and spatio-spectral metrology is critical to the characterization and use of ultra-short, high-power lasers. The emergence of few cycle pulses, with bandwidths of tens or hundreds of nanometers, poses a significant challenge to existing metrology techniques. This is due both to large discrepancies in the sensitivities of the measurem

Indar Kumar, Akanksha Tiwari, Sai Krishna Jasti, Ankit Hemant Lade

Test-time adaptation (TTA) enables neural forecasters to adapt to distribution shifts in streaming time series, but existing methods apply the same adaptation intensity regardless of the nature of the shift. We propose Regime-Guided Test-Time Adaptation (RG-TTA), a meta-controller that continuously modulates adaptation intensity based on distributional simil

Shijian Wang, Jiarui Jin, Runhao Fu, Zexuan Yan

Research agents have recently achieved significant progress in information seeking and synthesis across heterogeneous textual and visual sources. In this paper, we introduce MuSEAgent, a multimodal reasoning agent that enhances decision-making by extending the capabilities of research agents to discover and leverage stateful experiences. Rather than relying

Sadik Yagiz Yetim, Gaofeng Dong, Isaac-Neil Zanoria, Ronit Barman

Accurate observation of dynamic environments traditionally relies on synthesizing raw, signal-level information from multiple distributed sensors. This work investigates an alternative approach: performing geospatial inference using only encrypted packet-level information, without access to the raw sensory data. We further explore how this indirect informati

Gerardo Millar-Sáez, Ignacio Ormazábal, Hernán F. Astudillo

Parliaments dominated by two political blocs often face legislative inefficiencies as polarization increases. A central institutional question concerns how majority and supermajority rules interact with parliamentary composition to balance governability and minority protection. This article examines how the inclusion of independent legislators, introduced th

Andrei Popescu-Belis

In this paper, we discuss the relationship between natural language processing by computers (NLP) and the understanding of the human language capacity, as studied by linguistics and cognitive science. We outline the evolution of NLP from its beginnings until the age of large language models, and highlight for each of its main paradigms some similarities and

Ngoc Duy Tran, Yeman Fan, Feng Dai, Khang Nguyen

Grasping deformable objects with varying stiffness remains a significant challenge in robotics. Estimating the local stiffness of a target object is important for determining an optimal grasp pose that enables stable pickup without damaging the object. This paper presents a probe-to-grasp manipulation framework for estimating the relative stiffness of object

Stefan Steinerberger

Let $\Omega \subset \mathbb{R}^2$ be a convex set. We study the problem of distributing a one-dimensional set $S$ with total length $L$ so that for any line $\ell$ in $\mathbb{R}^2$ the number of intersections $\#(\ell \cap S)$ is proportional to the length $\mathcal{H}^1(\ell \cap \Omega)$ as much as possible; we use the term Buffon discrepancy for the larg

Conrad Borchers, Luiz Rodrigues, Newarney Torrezão da Costa, Cleon Xavier

Large language models (LLMs) increasingly generate formative feedback for students, yet little is known about how teachers revise this feedback before it reaches learners. Teachers' revisions shape what students receive, making revision practices central to evaluating AI classroom tools. We analyze a dataset of 1,349 instances of AI-generated feedback and co

Andrzej A. Zdziarski, Anton Dmytriiev, Karri I. I. Koljonen

We study the physical mechanisms underlying the production of orbitally-modulated PeV photons from Cyg X-3, recently discovered by the LHAASO collaboration. Our key findings are as follows. Helium nuclei are accelerated in a compact and strongly magnetized region within the jet, but they then quickly advect downstream to regions with a weaker field, allowing

Hans-Peter Beise

The recently introduced continuous Hopfield network (see Ramsauer et al.) exhibits large memorization capabilities, which manifest as attractive fixed points of its update rule -- a differentiable function consisting of two linear mappings composed with the scaled softmax function. The authors of the aforementioned work provide proofs for the existence and a

Zirui Xu, Vasileios Tzoumas

We provide a distributed online algorithm for multi-agent submodular maximization under communication delays. We are motivated by the future distributed information-gathering tasks in unknown and dynamic environments, where utility functions naturally exhibit the diminishing-returns property, i.e., submodularity. Existing approaches for online submodular max

Diego Alonso-Orán, Rafael Granero-Belinchón, Juliana S. Ziebell

In this work, we derive reduced interface models for hydroelastic water waves coupled to a nonlinear viscoelastic plate. In a weakly nonlinear small-steepness regime we obtain bidirectional nonlocal evolution equations capturing the interface dynamics up to quadratic order, and we also derive two unidirectional models describing one-way propagation while ret

Jnaneshwar Das, Christopher Filkins, Rajesh Moharana, Ekadashi Barik

Navagunjara Reborn: The Phoenix of Odisha was built for Burning Man 2025 as both a sculpture and an experiment-a fusion of myth, craft, and computation. This paper describes the digital-physical workflow developed for the project: a pipeline that linked digital sculpting, distributed fabrication by artisans in Odisha (India), modular structural optimization

Amirul Rahman, Aisha Karim, Kenji Nakamura, Yi-Fan Ng

Scaling test-time compute via extended reasoning has become a key paradigm for improving the capabilities of large language models (LLMs). However, existing approaches optimize reasoning under fixed or uniformly sampled token budgets, ignoring the fundamental mismatch between problem difficulty and allocated compute. This leads to overthinking on easy proble

Nusrat Tasnim, Kutub Uddin, Khalid Malik

The rapid proliferation of AI-generated images, powered by generative adversarial networks (GANs), diffusion models, and other synthesis techniques, has raised serious concerns about misinformation, copyright violations, and digital security. However, detecting such images in a generalized and robust manner remains a major challenge due to the vast diversity

Laura Rayón Ropero, Jasper De Laet, Filip Lemic, Pau Sabater Nácher

Facial Emotion Recognition is a critical research area within Affective Computing due to its wide-ranging applications in Human Computer Interaction, mental health assessment and fatigue monitoring. Current FER methods predominantly rely on Deep Learning techniques trained on 2D image data, which pose significant privacy concerns and are unsuitable for conti

Akash Anand, Aditya Agarwal, Leslie Pack Kaelbling

Robotic manipulation tasks require 3D mesh reconstructions of varying quality: dexterous manipulation demands fine-grained surface detail, while collision-free planning tolerates coarser representations. Multiple reconstruction methods offer different cost-quality tradeoffs, from Image-to-3D models - whose output quality depends heavily on the input viewpoin

Solvin Sigurdson, Benjamin Riviere, Joel Burdick

Planning long duration robotic manipulation sequences is challenging because of the complexity of exploring feasible trajectories through nonlinear contact dynamics and many contact modes. Moreover, this complexity grows with the problem's horizon length. We propose a search tree method that generates trajectories using the spectral decomposition of the inve

Jan van den Brand, Inge Li Gørtz, Chirag Pabbaraju, Debmalya Panigrahi

The goal in the stochastic vertex cover problem is to obtain an approximately minimum vertex cover for a graph $G^\star$ that is realized by sampling each edge independently with some probability $p\in (0, 1]$ in a base graph $G = (V, E)$. The algorithm is given the base graph $G$ and the probability $p$ as inputs, but its only access to the realized graph $

Hibah Saddal, Lucky Babu Jayswal, Chandan Bose

This study investigates the dynamics of passively morphing foils under accelerated plunging, establishing mechanistic links between transient kinematics, structural compliance, and aerodynamic performance. Two-way coupled simulations are performed for three wing geometries: a symmetric NACA0012 foil and two bio-inspired geometries based on falcon and owl win

Huai-Dong Cao, Junming Xie

In this note, we study the classification of four-dimensional complete gradient steady and expanding Ricci solitons. Specifically, under the asymptotically cylindrical (respectively, asymptotically conical) assumption, we classify gradient steady (respectively, expanding) Ricci solitons with half-harmonic Weyl curvature. In addition, we obtain a partial clas

Udo Schlegel, Thomas Seidl

Counterfactual explanations emerge as a powerful approach in explainable AI, providing what-if scenarios that reveal how minimal changes to an input time series can alter the model's prediction. This work presents a survey of recent algorithms for counterfactual explanations for time series classification. We review state-of-the-art methods, spanning instanc

Alexander Grigor'yan, Jin Sun, Philipp Sürig

We consider on Riemannian manifolds the Leibenson equation $\partial _{t}u=\Delta _{p}u^{q}$ that is also known as a doubly nonlinear evolution equation. We prove sharp upper estimates of weak subsolutions to this equation on Riemannian manifolds with non-negative Ricci curvature in the whole range of $p>1$ and $q>0$ satisfying $q(p-1)<1$. In this way, we im

Haoshun Chen, Enze Lv, Ning Xi, Fei Ye

Quantum fluctuations can give rise to a singular quantum critical point (QCP) in the ground state, whose influence extends to finite temperatures, forming a quantum critical regime (QCR). Recently, it has been shown that in the quantum Ising model, the symmetry-breaking, longitudinal field can induce a quantum supercritical regime (QSR) emanating from the QC

Amir Asiaee, Samhita Pal, Jared D. Huling

Randomized controlled trials (RCTs) yield internally valid causal effect estimates, but generalizing these results to target populations with different characteristics requires an untestable selection ignorability assumption: conditional on observed covariates, trial participation must be independent of potential outcomes. This assumption fails when unobserv

Zeinab Esmaeilpour, A. Ali Heydari, Daniel McDuff, Anthony Z Faranesh

Cardiovascular-Kidney-Metabolic (CKM) syndrome represents a growing public health crisis, yet its subclinical heterogeneity remains underexplored. Early detection of physiological deviation is critical for preventing irreversible organ damage. Here, we characterize the prevalence and interplay of CKM impairment in a US cohort (N=819) by integrating continuou

Greg Kestin, Nate Soares

We report the results of identical pre- and post-event surveys given to attendees of a talk, two-sided conversation, and Q&A centered around the book If Anyone Builds It, Everyone Dies at Harvard University in March 2026, covering perceived probability of AI-caused extinction or severe disempowerment resulting from unimpeded AI development, confidence in tho

Long Ling, Xiyu Zheng, Gengchen Cao, Ray LC

People traditionally divine the future by interpreting natural phenomena as oracular signals, especially in societies adhering to traditional beliefs like China. With the advent of Generative AI (GenAI), people gain access to new ways of probing digital oracles for predicting the future. To understand how people use and interpret GenAI for divination in Chin

Vadim E. Levit, Eugen Mandrescu, Kevin Pereyra

Let $G$ be a finite simple graph. An independent set $I$ of $G$ is critical if $\left|I\right|-\left|N(I)\right|\ge\left|J\right|-\left|N(J)\right|$ for every independent set $J$ of $G$. A critical independent set is maximum if it has maximum cardinality. The $core$ and the $nucleus$ of $G$ are defined as the intersection of all maximum independent sets and

Yogesh Phalak

Given an arbitrary sequence $(\alpha_1, \ldots, \alpha_n) \in \mathbb{C}^n$, we show that the degree-$n$ truncation of the formal exponential $\exp\bigl(-\sum_{k=1}^{\infty} \frac{\alpha_k}{k} x^k\bigr)$ produces a polynomial whose roots $\rho_1, \ldots, \rho_n$ satisfy $\sum_{i=1}^n \rho_i^{-k} = \alpha_k$ exactly for $k = 1, \ldots, n$. This truncation-exa

Sina Elahimanesh, Mohammadali Mohammadkhani, Shohreh Kasaei

In contemporary society, social media is deeply integrated into daily life, yet emotional expression often differs between real and online contexts. We studied the Persian community on X to explore this gap, designing a human-centered pipeline to measure alignment between real-world and social media emotions. Recent tweets and images of participants were col

Linfei Li, Lin Zhang, Zhong Wang, Ying Shen

Recently, the multi-modal fusion of RGB, depth, and semantics has shown great potential in dense Simultaneous Localization and Mapping (SLAM). However, a prerequisite for generating consistent semantic maps is the availability of dense, efficient, and scalable scene representations. Existing semantic SLAM systems based on explicit representations are often l

Mohd Asad Siddiqui, Md Qutubuddin, Tabish Qureshi

Wave--particle duality is a cornerstone of quantum mechanics, traditionally formulated under definite causal order. We investigate how complementarity is modified when the temporal order of operations is coherently superposed, as in the quantum switch. We show that no universal linear additive complementarity relation exists that simultaneously captures path

Pranav Garimidi, Michael Neuder, Tim Roughgarden

Blockchain protocols often seek to procure computationally challenging work from a decentralized set of participants. While there are simple procurement auctions that result in the minimal cost of acquisition and maximal efficiency, they also lead to concentration in the provider set due to the winner-take-all market structure. We design and analyze single-g

Harpreet Singh, Jaspreet Singh, Satwant Singh, Rupinder Singh

The rapid proliferation of Generative Artificial Intelligence (GenAI) is reshaping pedagogical practices and assessment models in higher education. While institutional and educator perspectives on GenAI integration are increasingly documented, the student perspective remains comparatively underexplored. This study examines how students perceive, use, and eva

Yoshihiro Nambu

This paper presents classical benchmark simulations of a practical hybrid decoding scheme for parity-encoded spin systems, which is well-suited to the development of quantum annealing devices based on on-chip superconducting technology. We compared the performance of finding the optimal solution using two embedding schemes for emulating all-to-all connectivi

Ritwik Yadav, Supun Abeysinghe, Min Yang, Jeffrey Helt

Materialized views are a core construct in database systems, used to accelerate analytical queries and optimize batch pipelines for extract-transform-load (ETL) workflows. Maintaining view consistency as underlying data evolves is a fundamental challenge, especially in high-throughput and real-time settings. Incremental view maintenance (IVM) has been studie

Benjamin Przybocki, Bernardo Subercaseaux, Marijn J. H. Heule

Bounded Variable Addition (BVA) is a central preprocessing method in modern state-of-the-art SAT solvers. We provide a graph-theoretic characterization of which 2-CNF encodings can be constructed by an idealized BVA algorithm. Based on this insight, we prove new results about the behavior and limitations of BVA and its interaction with other preprocessing te

Maolin Gao, Shao Jie Hu-Chen, Congyue Deng, Riccardo Marin

Dense 3D shape correspondence remains a central challenge in computer vision and graphics as many deep learning approaches still rely on intermediate geometric features or handcrafted descriptors, limiting their effectiveness under non-isometric deformations, partial data, and non-manifold inputs. To overcome these issues, we introduce RINO, an unsupervised,

Dragos-Patru Covei

This study develops a unified mathematical framework for the analysis of radial differential equations, revealing a fundamental connection between three distinct classes of problems: the nonlinear Riccati equation, the linear Schr\"odinger equation, and the Hamilton--Jacobi--Bellman equation for stochastic control. We establish the existence and uniqueness o

Yue Huang, Yu Jiang, Wenjie Wang, Haomin Zhuang

Multi-agent systems composed of large generative models are rapidly moving from laboratory prototypes to real-world deployments, where they jointly plan, negotiate, and allocate shared resources to solve complex tasks. While such systems promise unprecedented scalability and autonomy, their collective interaction also gives rise to failure modes that cannot

Rodrigo Serra, Carlos Azevedo, André Silva, Kevin Alcedo

This paper presents a novel framework for cooperative robotics competitions (coopetitions) that promote the transferability and composability of robotics modules, including software, hardware, and data, across heterogeneous robotic systems. The framework is designed to incentivize collaboration between teams through structured task design, shared infrastruct

Lia Draetta, Michael Oliverio, Virginia Ramón-Ferrer, Pier Felice Balestrucci

The automatic verbalization of structured knowledge is a key task for making knowledge graphs accessible to non-expert users and supporting retrieval-augmented generation systems. Although recent advances in Data-to-Text generation have improved multilingual coverage, little attention has been paid to potential biases in the verbalization of rare entities, f

Yizhi Song, Renxi Liu, Chunyi Zhang, Yifan Li

After melting, at ambient pressure, the density of water continues to increase with temperature until it reaches a maximum around 4 {\deg}C. For nearly a century, this phenomenon has been qualitatively attributed to a mixture of ordered and disordered structures. Herein, we employ a deep neural network to train a machine learned (ML) interatomic potential fo

Oliver Dürr

We present AutoStan, a framework in which a command-line interface (CLI) coding agent autonomously builds and iteratively improves Bayesian models written in Stan. The agent operates in a loop, writing a Stan model file, executing MCMC sampling, then deciding whether to keep or revert each change based on two complementary feedback signals: the negative log

Yin Cheng, Liao Zhou, Xiyu Liang, Dihao Luo

Recommendation ranking is fundamentally an influence allocation problem: a sorting formula distributes ranking influence among competing factors, and the business outcome depends on finding the optimal "exchange rates" among them. However, offline proxy metrics systematically misjudge how influence reallocation translates to online impact, with asymmetric bi

Y. T. Feng

We present an exact phase-space analytical treatment of the power-law damped contact oscillator governed by $m\ddot{\delta} + \alpha\sqrt{mk_H}\,\delta^{(p-1)/2}\dot{\delta} + k_H\delta^p = 0$, valid for all force-law exponents $p \geq 1$ and all initial impact velocities $v_0$. The central result is the transformation $\delta = Ax^{2/(p+1)}$, where $A = [(p

Amir Weiss

We revisit the recently proposed ``self-Wiener" (SW) filtering method for robust deconvolution, and generalize it to the classical denoising problem. The resulting estimator, termed generalized SW (GSW) filtering, retains the nonlinear shrinkage structure of SW but introduces a tunable threshold parameter. This tunability enables GSW to flexibly adapt to var

Wayne Gao

Normalization is ubiquitous in economics, and a growing literature shows that ``normalizations'' can matter for interpretation, counterfactual analysis, misspecification, and inference. This paper provides a general framework for these issues, based on the formalized notion of modeling equivalence that partitions the space of unknowns into equivalence classe

Jovan Markov, Yotam Shapira, Ayelet Hasson, Meir Alon

High-fidelity quantum gates require precise classical control signals, yet the analog hardware delivering these signals introduces nonlinear distortions that degrade gate performance. We demonstrate digital predistortion of an acousto-optic modulator used to generate multi-tone entangling-gate waveforms in a trapped-ion processor based on $^{88}$Sr$^+$. By m

Sergio Gonzalez-Casal, Simon Pascal, Olivier Siri, Dominique Vuillaume

We report the thermal conductances of molecular junctions made of self-assembled monolayers of benzo-bis(imidazole) molecules, without side groups or functionalized with two phenylamine side groups. In the two cases, when the molecules are connected to the electrodes by thiol anchoring groups in the meta-position, the thermal conductance is decreased compare

Chengyin Hu, Xuemeng Sun, Jiaju Han, Qike Zhang

Visual-Language Models (VLMs) have demonstrated exceptional cross-modal understanding across various tasks, including zero-shot classification, image captioning, and visual question answering. However, their robustness to physically plausible non-rigid deformations-such as wrinkles on flexible surfaces-remains poorly understood. In this work, we propose a pa

Zelin Tao, Zeran Su, Peiran Liu, Jingkai Sun

Achieving general-purpose humanoid control requires a delicate balance between the precise execution of commanded motions and the flexible, anthropomorphic adaptability needed to recover from unpredictable environmental perturbations. Current general controllers predominantly formulate motion control as a rigid reference-tracking problem. While effective in

Michel Takken, Robert Wille

Hydrogen fuel cells are a key technology in the transition toward carbon-neutral energy systems, offering clean power with water as the only byproduct. Microfluidic fuel cells, which operate at the microliter scale, are an emerging variant that offer fine control over fluid and thermal dynamics, along with compact, efficient designs. However, scaling these s

Manuel González, Antonio Martínez-Abejón

We introduce the notions of tauberian, cotauberian and weakly compact pair of closed subspaces of a Banach space. The theory produced by these notions is richer than that of the corresponding operators since an operator can be regarded as a suitable pair of closed subspaces. We investigate into these classes of pairs of subspaces and describe several applica

Wolfgang Altmannshofer, Samuel G. Christensen, Peter Stangl

Recent results from LHCb have confirmed the long-standing $P_5^\prime$ anomaly, an intriguing discrepancy in the angular distribution of the $B \to K^* \mu^+\mu^-$ decay that might be a sign of new physics. In addition, the new results hint at a non-zero value for $S_7$, another observable that characterizes the $B \to K^* \mu^+\mu^-$ angular distribution. W

Iver H. Brevik, Moshe M. Chaichian, Tiberiu Harko, Yuri N. Obukhov

We study observable manifestations of an axion field, focusing on possible polarizational effects for electromagnetic wave propagating in such a special magnetoelectric medium. The corresponding analysis is based on a geometric model of the Casimir type, in the framework of which the rotation angle of the polarization plane is derived to the lowest order. Th

Adam Haile

In 2019, Google DeepMind released MuZero, a model-based reinforcement learning method that achieves strong results in perfect-information games by combining learned dynamics models with Monte Carlo Tree Search (MCTS). However, comparatively little work has extended MuZero to partially observable, stochastic, multi-player environments, where agents must act u

Daniele Bartoli, Alessandro Giannoni, Giuseppe Marino, Alessandro Neri

In the realm of rank-metric codes, Maximum Rank Distance (MRD) codes are optimal algebraic structures attaining the Singleton-like bound. A major open problem in this field is determining whether an MRD code can be extended to a longer one while preserving its optimality. This work investigates $\mathbb{F}_{q^m}$-linear MRD codes that are non-extendable but

Douglas Daniel de Carvalho, Erick de Moraes Franklin

We investigate the roles of spin and packing fraction on the dynamics of cratering when a solid projectile impacts a granular bed at different incident angles. For that, we carried out DEM (discrete element method) computations in which we varied the magnitude and direction of the projectile spin, the impact velocity, the bed packing fraction, and the incide

Haichao Zhu, Qian Zhang, Jiyuan Wang, Zhaorui Yang

AI coding agents can now complete complex programming tasks, but existing evaluations largely emphasize behavioral correctness and often overlook maintainability risks such as weak modularity or testability. We present Needle in the Repo (NITR), a diagnostic probe-and-oracle framework for evaluating whether behaviorally correct repository edits preserve main

Guowei Tang

Recent multimodal large language models (MLLMs) perform strongly on general visual understanding, diagram and chart reasoning, and document-centric perception. However, these abilities are learned from heterogeneous supervision sources with very different task structures and learning demands, and the effect of their temporal organization during training rema

Alexander S. Petty

For a prime p and base b, the digit function delta(r) = floor(br/p) partitions the residues {1, ..., p-1} into b contiguous bins. The collision count C(g) records how many residues share a bin with their image under multiplication by g. We prove four results about this function. First, the gate width theorem: exactly b-1 multipliers satisfy C(g) = 0, given b

Hongseok Namkoong

Empirical likelihood is an attractive inferential framework that respects natural parameter boundaries, but existing approaches typically require smoothness of the functional and miscalibrate substantially when these assumptions are violated. For the optimal-value functional central to policy evaluation, smoothness holds only when the optimum is unique -- a

Jing-Wen Chen, Alex S. Hill, Anna Ordog, Rebecca A. Booth

We developed a computer vision-based methodology to achieve precise 3D segmentation and tracking of superbubbles within magnetohydrodynamic simulations of the supernova-driven interstellar medium. Leveraging advanced 3D transformer models, our approach effectively captures the complex morphology and dynamic evolution of these astrophysical structures. To dem

Xiao Liu, Tianxiang Zhao, Ting Wang, Junsheng Xu

High-performance infrared photodetection underpins various applications spanning surveillance, environmental monitoring, optical communications and biomedical imaging. However, conventional bulk detectors remain limited by poor spectral tunability, mechanical rigidity, and high dark currents, motivating the pursuit of low-dimensional material platforms such

Dennis Beck, Leonel Morgado

As online higher education expands, sustaining student engagement remains a critical challenge. This paper approaches immersive learning by investigating how custom GPTs foster immersion (as a state of deep mental involvement) for students and instructors. While large language models (LLMs) offer potential for enhancing feedback, little research has examined