March 2026 arXiv papers — page 69

Siwei Wang, Guangming Liu, Hsing-Ta Chen

Exciton transport in molecular aggregates is a fundamental process governing the performance of organic optoelectronics and light-harvesting systems. While most theoretical studies have emphasized long-time transport behavior, recent advances in ultrafast spectroscopy have brought into focus the short-time regime, in which exciton motion remains ballistic on

Song Son Ha, Kunal Singh, Florian Foerster, Henry Beuster

Industrial deployments increasingly rely on Open Platform Communications Unified Architecture (OPC UA) as a secure and platform-independent communication protocol, while private Fifth Generation (5G) networks provide low-latency and high-reliability connectivity for modern automation systems. However, their combination introduces new attack surfaces and traf

Serafim Teknowijoyo, Domenico Napoletani, Vahan Nikoghosyan, Armen Gulian

We report reproducible magnetization anomalies appearing below room temperature in copper-doped apatite materials belonging to the LK-99 family synthesized via hydrothermal methods. These anomalies are observed consistently across samples prepared under comparable conditions. Although the extracted Mydosh parameter lies within the range often associated with

Vittorio Todisco, Alessandro Bazzi

In the context of 5G, 3GPP introduced New Radio vehicle to everything (NR-V2X) for direct vehicle-to-vehicle communication. However, starting from Release 18 the focus of the standard has been expanded from vehicles to any device and use case that can benefit from direct communication. In 3GPP terminology, the standard is now referred to simply as Sidelink c

Q. Moysan, F. Sarron, N. Clerc, G. Soucail

Properties of the hot intracluster and intragroup medium are mostly set by the underlying gravitational potential well, although complex astrophysical processes at play during their buildup may leave a significant imprint. Observational constraints on the degree and scales of such non-gravitational processes require well-selected samples of objects and deep

Yong-Bin Choi, Chang-Won Choi, Luke Holtzman, Hoil Kim

Phase-coherent superconducting proximity in topological materials requires clean superconductor-topological material (SC-TM) interfaces, yet conventional top-contact fabrication often degrades them through oxidation, polymer residue, and process-induced disorder. Here we introduce a pre-patterned superconducting bottom-contact architecture in which MoRe/Au e

Dharma P. Permana, Mažena Mackoit Sinkevičienė, Julius Ruseckas, Hamid R. Hamedi

We investigate the propagation of optical vector vortices of slow light in a coherently prepared four-level tripod atomic system. The vector vortex consists of superposed pulse pairs with opposite circular polarizations and orbital angular momentum (OAM) charges $\pm l$, weakly interacting with an atomic medium initially prepared in a coherent superposition

Mustafa Sarisaman, Murat Taş, Enes Talha Kırca

In this study, motivated by recent advancements in non-Hermitian physics, we explore new characteristics of Dirac semimetals (DSMs) using the spectral singularities by means of scattering techniques, with the goal of uncovering additional unique properties. To achieve this, we investigate how the axion texture of a DSM affects its topological properties by a

Nankun Wei, Xiaojin Xiong, Qin Li, Minyu Feng

The evolution of cooperation is a central enigma in evolutionary game theory. Traditionally, the combination of pairwise networks and repeated Public Goods Games with a single state fails to adequately describe realistic group interaction scenarios. On the one hand, pairwise networks lack clear group definitions. On the other hand, a participant's decisi

A. G. Melkonyan, G. A. Mantashian, D. B. Hayrapetyan

In this study, we investigate the electronic structure, charge transport dynamics, and optical properties of a quantum dot light-emitting diode (QD-LED) featuring a double nanorod (NR) emission layer composed of CdSe-ZnS core-shell structures. Utilizing a rigorous self-consistent numerical approach, we solve the coupled Schrodinger-Poisson equations iterativ

Hyunwoo Oh, Hanning Chen, Sanggeon Yun, Yang Ni

Multimodal stacks that mix ViTs, CNNs, GNNs, and transformer NLP strain embedded platforms because their compute/memory patterns diverge and hard real-time targets leave little slack. TRINE is a single-bitstream FPGA accelerator and compiler that executes end-to-end multimodal inference without reconfiguration. Layers are unified as DDMM/SDDMM/SpMM and mappe

Darij Starko, Tom Kirchner

The electron removal and excitation channels in argon dimer target and helium ion projectile collision systems that facilitate interatomic Coulombic decay (ICD) are investigated. We implement an independent-atom and independent-electron model of the collision system with the dimer target fixed at its equilibrium bond length and the He$^{2+}$ and He$^+$ ion p

Bijay Shakya, Catherine Hoier, Khandaker Mamun Ahmed

Rapid and accurate structural damage assessment following natural disasters is critical for effective emergency response and recovery. However, remote sensing imagery often suffers from low spatial resolution, contextual ambiguity, and limited semantic interpretability, reducing the reliability of traditional detection pipelines. In this work, we propose a n

Chen Shang, Dinh Thai Hoang, Diep N. Nguyen, Jiadong Yu

This work proposes a novel immersive communication framework that leverages brain-computer interface (BCI) to acquire brain signals for inferring user-centric states (e.g., intention and perception-related discomfort), thereby enabling more personalized and robust immersive adaptation under strong individual variability. Specifically, we develop a personaliz

Matthew Stewart

Algorithmic accountability scholarship has focused heavily on explanation, helping affected parties understand why decisions were made. We argue this focus is insufficient. Explanation without evidentiary access does not enable meaningful contestation. A person told "your risk score was 0.73" understands the decision but cannot verify the score, test

Fatih Berkay Sarpkaya, Andrea Francini, Bilgehan Erman, Shivendra Panwar

Practitioners of a growing number of scientific and artificial-intelligence (AI) applications use High-Performance Wide-Area Networks (HP-WANs) for moving massive data sets between remote facilities. Accurate prediction of the flow completion time (FCT) is essential in these data-transfer workflows because compute and storage resources are tightly scheduled

Jared Z. Dans, Prathum Saraf, Lillian Jirousek, Carsyn L. Mueller

The topological semimetal YPtBi has attracted considerable attention, owing to its novel superconducting and normal state properties. A strong band inversion from spin-orbit coupling allows the existence of $j=3/2$ quasiparticles near the Fermi level, which form Cooper pairs with angular momentum potentially higher than single or triplet states. In this repo

Chueng-Ryong Ji, Hariprashad Ravikumar

We present the interpolating conformal algebra between the instant form dynamics (IFD) and the light-front dynamics (LFD) in $(1+1)$ dimensions, along with a $4\times4$ interpolating projective spacetime matrix representation. While there are six generators in the $(1+1)$ dimensional conformal algebra, the number of kinematic and dynamic generators dramatica

Jorge Sarrato-Alós, James Bullock, Arianna Di Cintio, Christopher Brook

Aims. We aim to investigate the connection between star formation histories (SFHs) and the inner dark matter density profiles of simulated galaxies. In particular, we test whether the burstiness and temporal distribution of star formation influence the formation of cored versus cuspy dark matter profiles. Methods. We homogeneously analysed simulated galaxies

Radman Rakhshandehroo, Daniel Coombs

We present ContagionRL, a Gymnasium-compatible reinforcement learning platform specifically designed for systematic reward engineering in spatial epidemic simulations. Unlike traditional agent-based models that rely on fixed behavioral rules, our platform enables rigorous evaluation of how reward function design affects learned survival strategies across div

Apoorva Khare

We present an overview of a classical theme in analysis and matrix positivity: the question of which functions preserve positive semidefiniteness when applied entrywise. In addition to drawing the attention of experts such as Schoenberg, Rudin, and Loewner, the subject has attracted renewed attention owing to its connections to various applied fields and tec

Juan Pimienta, Jean-Luc Aider

Rare and extreme events in turbulent flows play a critical role in transport, mixing and transition, yet are notoriously difficult to capture experimentally. Here we report, to our knowledge, the first direct experimental detection of an upstream-directed jet burst in a backward-facing step (BFS) flow at $Re_h=2100$, using long-duration Live Optical Flow Vel

Pavla Krotka, Martin Posch, Marta Bofill Roig

The analysis of platform trials can be enhanced by utilizing non-concurrent controls. Since including this data might also introduce bias in the treatment effect estimators if time trends are present, methods for incorporating non-concurrent controls adjusting for time have been proposed. However, so far their behavior has not been systematically investigate

Guoqiang Lei, D. Exposito, Xuerui Mao

Physics-informed neural networks (PINNs) have proven to be a promising method for the rapid solving of partial differential equations (PDEs) in both forward and inverse problems. However, due to the smoothness assumption of functions approximated by general neural networks, PINNs are prone to spectral bias and numerical instability and suffer from reduced ac

Gerhard Schindl

We introduce and study new transformations between two functions satisfying some basic growth properties and generalize the known lower and upper Legendre conjugate (or envelope). We also investigate how these transformations modify recently defined growth indices for weight functions. A special but important and useful situation, to which the knowledge is t

Ting-Yang Hsiao, Yun-Feng Lo, Chengbin Zhu

We present a rigorous mathematical framework establishing the equivalence of four classical notions of synchronization full phase-locking, phase-locking, frequency synchronization, and order parameter synchronization in generalized Kuramoto models, via a non-perturbative, finite-dimensional analysis. Our approach avoids linearization, mean-field limits, and

Koji Yamaguchi, Yosuke Mitsuhashi, Tomohiro Shitara, Hiroyasu Tajima

Quantifying physical concepts in terms of the ultimate performance of a given task has been central to theoretical progress, as illustrated by thermodynamic entropy and entanglement entropy, which respectively quantify irreversibility and quantum correlations. Symmetry breaking is equally universal, yet lacks such an operational quantification. While an oper

Christopher Hoffman, Tobias Johnson, Matthew Junge

We prove a conjecture of Levine and Silvestri that the driven-dissipative activated random walk model on an interval drives itself directly to and then sustains a critical density. This marks the first rigorous confirmation of a sandpile model behaving as in Bak, Tang, and Wiesenfeld's original vision of self-organized criticality.

Yuanfang Liu, Guanghong Xie, Junya Zhi, Wenrui Zuo

Intangible Cultural Heritage (ICH) faces critical challenges in the digital age, including reduced public engagement, restricted accessibility, and difficulties in communicating complex cultural practices to modern audiences. Virtual Reality (VR) games present promising opportunities for ICH preservation and transmission, yet little is known about factors sh

Takuya Kanazawa

We propose a novel random matrix model that describes the QCD Kondo phase. The model correctly implements both the chiral symmetry of light quarks and the SU(2) spin symmetry of heavy quarks. We analytically take the large-N limit with N the matrix size and show that the model has three phases: the pure Kondo phase with no chiral condensate, the pure chirall

Shiyao Li, Antoine Guédon, Shizhe Chen, Vincent Lepetit

Active mapping aims to determine how an agent should move to efficiently reconstruct unknown environments. Most existing approaches rely on greedy next-best-view prediction, resulting in inefficient exploration and incomplete reconstruction. To address this, we introduce MAGICIAN, a novel long-term planning framework that maximizes accumulated surface covera

Vedrana Ivezić, Mara Pleasure, Ashwath Radhachandran, Saarang Panchavati

Though self-supervised learning (SSL) has demonstrated incredible ability to learn robust representations from unlabeled data, the choice of optimal SSL strategy can lead to vastly different performance outcomes in specialized domains. Joint embedding architectures (JEAs) and joint embedding predictive architectures (JEPAs) have shown robustness to noise and

Zefei Xie, Yuhan Guo, Kai Xu

There are different goals for literature research, from understanding an unfamiliar topic to generate hypothesis for the next research project. The nature of literature research also varies according to user's familiarity level of the topic. For inexperienced researchers, identifying gaps in the existing literature and generating feasible hypothesis are cruc

Valentina Danieli, Paola C. M. Delgado, Federico R. Urban

Levitated sensors have emerged as a new frontier to detect ultra-light dark matter such as axion-like particles and dark photons. In this work we study how a magnetically levitated superconductor responds to a spin-2 dark matter field, the dark graviton, in the dHz to kHz frequency range. To do so, we compute the forces that the dark graviton exerts on the s

Steven R. White

Gausslets are one of the few examples of basis sets for electronic structure which allow for two-index/diagonal electron-electron interaction terms. A weakness of gausslets is that, because of their 1D origin, they have been tied to Cartesian coordinates. Here we generalize the gausslet construction for the radial coordinate in three dimensions for atomic ba

Chethan Sanjeevappa, Anirudh Chandrasekaran, Joseph J. Betouras

We study a four-fold symmetric dispersion relation of a quantum material, which exhibits a single high-order Van Hove singularity of X$_9$ type at the Fermi energy. First, we analyze in detail its form, type and density of states when the energy dispersion is in its canonical form. Subsequently, we study the possibility of a superconducting state when Hubbar

Xiaohan Zhu, Mesrob I. Ohannessian, Nathan Srebro

We consider a PAC-Bayes type learning rule for binary classification, balancing the training error of a randomized ''posterior'' predictor with its KL divergence to a pre-specified ''prior''. This can be seen as an extension of a modified two-part-code Minimum Description Length (MDL) learning rule, to continuous priors and randomized predictions. With a bal

Chukwuebuka Anyaegbuna, Eduardo Juan Perez Guerrero, Jerry Liu, Timothy Keyes

Language barriers affect 27.3 million U.S. residents with non-English language preference, yet professional medical translation remains costly and often unavailable. We evaluated four frontier large language models (GPT-5.1, Claude Opus 4.5, Gemini 3 Pro, Kimi K2) translating 22 medical documents into 8 languages spanning high-resource (Spanish, Chinese, Rus

Yuxuan Jiang, Yixuan Li, Hanwei Zhu, Siyue Teng

Vision-Language Model (VLM)-based image quality assessment (IQA) has been significantly advanced by incorporating Chain-of-Thought (CoT) reasoning. Recent work has refined image quality reasoning by applying reinforcement learning (RL) and leveraging active visual tools. However, such strategies are typically language-centric, with visual information being t

Heiko Dietrich, Melissa Lee, Andre Nies, Marc Vinyals

We report on some computational experiments related to the trivial units property and unique product property for group rings of torsion-free groups. These properties are related to Kaplansky's unit and zero-divisor conjectures. Our investigations include a classification of certain symmetric non-trivial units in the binary group ring of the Hantzsche-Wendt

Ingrid Torres, Raquel Rodriguez, Robert W. Laird, Angela R. Laird

Magnetic resonance imaging (MRI) can see deep inside the body without ionizing radiation, but image quality depends strongly on how well the radio-frequency field is controlled. Passive resonant pads and metasurfaces can help, yet they often lose their tuning when they are placed next to water-rich tissue or tissue-like materials. Here we show a simple way t

S. P. Glasby, Alice C. Niemeyer, Cheryl E. Praeger

With high probability, among $O(\log n)$ independent randomly selected elements from a finite $n$-dimensional classical group, some pair of elements power to a $2$-element generating set for a naturally embedded classical subgroup of dimension $O(\log n)$. The $2$-element generating set produced consists of certain elements with large $1$-eigenspaces, called

Pratyasha Saha, Anita Say Chan, Sharifa Sultana

Rapid digitization across government services, financial platforms, and telecommunications has intensified the collection and processing of large scale personal data in Bangladesh. In response, the state has introduced multiple regulatory instruments, including the Personal Data Protection Ordinance, the Cyber Security Ordinance, and the National Data Govern

Rob J Hyndman, Sevvandi Kandanaarachchi, Katharine Turner

We present an updated version of lookout -- an algorithm for detecting anomalies using kernel density estimates with bandwidth based on Rips death diameters -- with theoretical guarantees. The kernel density estimator for updated lookout is shown to be consistent, and the proposed multivariate scaling is robust and efficient. We show our updated algorithm pe

Caio C. Quaglio-Gomes, Stefan Marinković, Elijah A. Abbey, Davi A. D. Chaves

Control of oxygen vacancies by electrical currents in complex oxides such as YBa$_2$Cu$_3$O$_{7-\delta}$ (YBCO) has attracted considerable interest due to the relative simplicity of its implementation and its potential for both fundamental studies and the tuning of superconducting device properties. However, the structural evolution and depth-dependent effec

ZhaoBin Li, Mark Steyvers

Productive human-AI collaboration requires appropriate reliance, yet contemporary AI systems are often miscalibrated, exhibiting systematic overconfidence or underconfidence. We investigate whether humans can learn to mentally recalibrate AI confidence signals through repeated experience. In a behavioral experiment (N = 200), participants predicted the AI's

Pouria Mortezaagha, Arya Rahgozar

Retrieval-Augmented Generation (RAG) systems for biomedical literature are typically evaluated using ranking metrics like Mean Reciprocal Rank (MRR), which measure how well the system identifies the single most relevant chunk. We argue that for full-text scientific documents, this paradigm is incomplete: it rewards retrieval precision while ignoring retrieva

Sheng Qu, Jiyong Kim, Jaco J. Geuchies, Sergey Kovalev

Driven-dissipative dynamics underlie a wide range of nonequilibrium phenomena in quantum materials, yet reduced descriptions beyond the quasi-equilibrium picture remain difficult to establish. Here, we experimentally demonstrate that a resonantly driven phonon mode admits a generalized thermodynamic description in which coherence and energy jointly organize

Namitha Guruprasad, Abhay Yadav, Cheng Peng, Rama Chellappa

Recovering dense 3D geometry from unposed images remains a foundational challenge in computer vision. Current state-of-the-art models are predominantly trained on perspective datasets, which implicitly constrains them to a standard pinhole camera geometry. As a result, these models suffer from significant geometric degradation when applied to wide-angle imag

Ruican Zhong, Jiachen Li, Gary Hsieh, David W. McDonald

Electronic health records (EHRs) have improved data accessibility but have also introduced cognitive burden for physicians, given the sheer volume and complexity of the data involved. Advances in large language models (LLMs) create new opportunities to rethink how clinicians interact with medical data through dynamic, adaptive interfaces. In this position pa

L. T. Scamfer, E. A. Silber, M. D. Fries, D. Vida

On 24 April 2025 at 18:30:57 UTC, a bright daytime fireball over Southcentral Alaska was detected by 37 seismic stations, 16 single infrasound sensors, and four infrasound arrays, yielding 30 ballistic and multiple fragmentation arrivals. The unprecedented density of seismoacoustic coverage enabled detailed reconstruction of the event using acoustic signals,

Hailay Teklehaymanot, Dren Fazlija, Wolfgang Nejdl

Adapting pretrained language models to low-resource, morphologically rich languages remains a significant challenge. Existing vocabulary expansion methods typically rely on arbitrarily segmented subword units, resulting in fragmented lexical representations and loss of critical morphological information. To address this limitation, we propose the Lexically G

Tabia Tanzin Pramaa, Christopher M. Danfortha, Peter Sheridan Dodds

The mobility of high-potential individuals, particularly graduates from elite academic institutions, serves as a critical driver of global innovation and economic development. Despite its importance, granular data on the specific trajectories and demographic drivers of these flows remain scarce in traditional administrative sources. In this study, we leverag

Heejong Kim, Abhishek Thanki, Roel van Herten, Daniel Margolis

Clinical MRI frequently acquires anisotropic volumes with high in-plane resolution and low through-plane resolution to reduce acquisition time. Multiple orientations are therefore acquired to provide complementary anatomical information. Conventional integration of these views relies on registration followed by interpolation, which can degrade fine structura

Dinglun He, Baoming Zhang, Xu Wang, Yao Hao

Abdominal CT data are limited by high annotation costs and privacy constraints, which hinder the development of robust segmentation and diagnostic models. We present a Prior-Integrated Variation Modeling (PIVM) framework, a diffusion-based method for anatomically accurate CT image synthesis. Instead of generating full images from noise, PIVM predicts voxel-w

Tuan-Anh Vu, Sébastien Destercke, Frédéric Pichon

Uncertainty quantification is a key aspect in many tasks such as model selection/regularization, or quantifying prediction uncertainties to perform active learning or OOD detection. Within credal approaches that consider modeling uncertainty as probability sets, upper entropy plays a central role as an uncertainty measure. This paper is devoted to the comput

Abu Noman Md Sakib, OFM Riaz Rahman Aranya, Kevin Desai, Zijie Zhang

Attribution maps for semantic segmentation are almost always judged by visual plausibility. Yet looking convincing does not guarantee that the highlighted pixels actually drive the model's prediction, nor that attribution credit stays within the target region. These questions require a dedicated evaluation protocol. We introduce a reproducible benchmark that

OFM Riaz Rahman Aranya, Kevin Desai

Vision-language models (VLMs) adapted to the medical domain have shown strong performance on visual question answering benchmarks, yet their robustness against two critical failure modes, hallucination and sycophancy, remains poorly understood, particularly in combination. We evaluate six VLMs (three general-purpose, three medical-specialist) on three medica

Heesup Yun, Isaac Kazuo Uyehara, Ioannis Droutsas, Earl Ranario

Three-dimensional (3D) procedural plant architecture models have emerged as an important tool for simulation-based studies of plant structure and function, extracting plant architectural parameters from field measurements, and for generating realistic plants in computer graphics. However, measuring the architectural parameters and nested structures for these

T. A. Dardeno, A. J. Hughes, L. A. Bull, R. S. Mills

Despite recent advances in population-based structural health monitoring (PBSHM), knowledge transfer between highly-disparate structures (i.e., heterogeneous populations) remains a challenge. The current work proposes that heterogeneous transfer may be accomplished via intermediate structures that bridge the gap in information between the structures of inter

Panayiotis Panayiotou, Özgür Şimşek

Causal discovery is challenging in general dynamical systems because, without strong structural assumptions, the underlying causal graph may not be identifiable even from interventional data. However, many real-world systems exhibit directional, cascade-like structure, in which components activate sequentially and upstream failures suppress downstream effect

Jihyun Janice Ahn, Ryo Kamoi, Berk Atil, Renze Lou

LLMs often generate seemingly valid answers to flawed or ill-posed inputs. This is not due to missing knowledge: under discriminative prompting, the same models can mostly identify such issues, yet fail to reflect this in standard generative responses. This reveals a fundamental know-act gap between discriminative recognition and generative behavior. Prior w

Olivia Yan Huang, Monika Stodolska, Sharifa Sultana

AI companion chatbots are increasingly used for emotional support, with prior work in the domain predominantly documenting their mixed psychosocial impacts, including both increased emotional expression and heightened loneliness. However, most existing research primarily focuses on outcome-level effects, offering limited insight into how emotional support is

Greg Nyilasy, Abraham Ryan Ade Putra Hito, Jennifer Overbeck, Brock Bastian

Consumers are generally resistant to Artificial Intelligence (AI) involvement in moral decision-making, perceiving moral agency as requiring uniquely human traits. This research investigates whether consumers might instead accept AIs in the role of moral compliance, where AI upholds pre-existing moral norms without exercising subjective discretion. Across fi

Naman Ahuja, Saniya Mulla, Muhammad Ali Khan, Zaryab Bin Riaz

We present EviSearch, a multi-agent extraction system that automates the creation of ontology-aligned clinical evidence tables directly from native trial PDFs while guaranteeing per-cell provenance for audit and human verification. EviSearch pairs a PDF-query agent (which preserves rendered layout and figures) with a retrieval-guided search agent and a recon

Steven Heilman

We show that Grothendieck's real constant $K_{G}$ satisfies $K_G\geq c+10^{-26}$, improving on the lower bound of $c=1.676956674215576\ldots$ of Davie and Reeds from 1984 and 1991, respectively.

Maria Tsampazi, Paolo Testolina, Michele Polese, Tommaso Melodia

Frequency Range 3 (FR3), encompassing frequencies between 7.125 and 24.25 GHz, is an emerging frequency band for 6th generation (6G) applications. The upper mid-band, as it is frequently referred to, represents the sweet spot between coverage and capacity, providing better range than mmWaves and higher bandwidth than the sub-6 GHz band. Despite these advanta

Tymoteusz Chmiel

We investigate the operation of shifting local exponents and study its effects on the monodromy representation of a one-parameter family of Calabi-Yau threefolds. The main result is a characterization of shifts of geometric operators which are also geometric. We use this description to construct some Picard-Fuchs operators with interesting properties.

Daniel Fadrique Barbero

In this study, we introduce a physical framework to analyse and classify the thermal regimes governed by tidal heating and stellar irradiation. Although all planetary systems are exposed to stellar radiation, this source is not always the dominant energy mechanism. This study is motivated by the lack of a physical framework that examines tidal heating in cas

Nicolás Villarroel-Sepúlveda, Daniel Verscharen, Pablo S. Moya, Rodrigo A. López

Space plasmas are weakly collisional since characteristic time scales related to Coulomb collisions are much larger than those of Larmor gyration or wave--particle interactions. Thus, wave activity is likely to drive some of the non-thermal features that are observed in space plasma velocity distributions, such as temperature anisotropy, beams, and skewness.

Protiva Das, Sovon Chakraborty, Sidhant Narula, Lucas Potter

The rapid advancement of Large Language Models (LLMs) in biological research has significantly lowered the barrier to accessing complex bioinformatics knowledge, ex perimental design strategies, and analytical workflows. While these capabilities accelerate innovation, they also introduce serious dual-use risks, as Bio-LLMs can be exploited to generate harmfu

Reda Chhaibi, Fabrice Gamboa, Clément Pellegrini

Given a bivariate random pair $(X,Y)$, a natural problem is to estimate, from a single sample $(X_i,Y_i)_{1\le i\le n}$, quantities such as $\mathbb{E}\left[ \mathbb{E}[ Y\mid X ]^2 \right]$. More broadly, sensitivity indices are designed to quantify the possibly nonlinear influence of an input variable $X$ on an output variable $Y$. A classical example is t

Sean Howe, Christian Klevdal

We extend the relative theory of admissible pairs and $p$-adic Hodge structures introduced in Part II to allow variation in the underlying local systems of $\mathbb{Q}_p$-vector spaces and isocrystals. This extension accommodates, in particular, the families of $p$-adic Hodge structures that arise from the cohomology of certain smooth proper families. Such a

Tanya Rudberg Selin, Danielle Unéus, Søren Knudsen

We examine how neurodivergent individuals experience creating, interacting with, and reflecting on personal data about masking. Although self-tracking is often framed as enabling self-insight, this is rarely our experience as neurodivergent individuals and researchers. To better understand this disconnect, we conducted a two-phase qualitative study. First, a

Jingxuan Chen, Mohammad Taher Pilehvar, Jose Camacho-Collados

Users often rely on Large Language Models (LLMs) for processing multiple documents or performing analysis over a number of instances. For example, analysing the overall sentiment of a number of movie reviews requires an LLM to process the sentiment of each review individually in order to provide a final aggregated answer. While LLM performance on such indivi

Zewei Zhang, Jia Jun Cheng Xian, Kaiwen Liu, Ming Liang

Predicting future motion is crucial in video understanding and controllable video generation. Dense point trajectories are a compact, expressive motion representation, but modeling their future evolution from observed video remains challenging. We propose a framework that predicts future trajectories and visibility from past trajectories and video context. O

Magnus Ekman

Simulation remains a cornerstone of computer architecture research, yet full end-to-end application execution is prohibitively time-consuming. The industry-standard solution, SimPoint, mitigates this cost by selecting a small number of representative code regions that capture program phase behavior. In this work, we take a fresh look at phase behavior in the

Beibei Liu, Akua K. Dickson, Ran Jing, Andrew P. Sabelhaus

Soft robots are well suited for contact-rich tasks due to their compliance, yet this property makes accurate and tractable modeling challenging. Planning motions with dynamically-feasible trajectories requires models that capture arbitrary deformations, remain computationally efficient, and are compatible with underactuation. However, existing approaches bal

Zixian Huang, Kaichen Yang, Xu Huang, Feiyang Hao

A widely adopted strategy for model enhancement is to use synthetic data generated by a stronger model for supervised fine-tuning (SFT). However, for emerging reasoning models like Qwen3-8B, this approach often fails to improve reasoning capabilities and can even lead to a substantial drop in performance. In this work, we identify substantial stylistic diver

Nicholas Pecka, Lotfi Ben Othmane, Bharat Bhargava, Renee Bryce

Traditional threat modeling occurs during design, but cloud deployments introduce unanticipated threats, especially multi-stage attacks chaining vulnerabilities across trust boundaries. Existing security tools analyze components in isolation, cannot detect architectural threats from system composition, and cannot validate runtime behavior against configured

Wanying Kang, Yixiao Zhang

The habitability of Enceladus' subsurface ocean and the detectability of potential biosignatures depend on efficient ocean circulation and suitable ocean conditions. Directly probing the ocean is challenging because it lies beneath a thick ice shell; however, the ice thickness distribution is relatively well constrained and provides indirect insight into the

Edwin R. van Dam, Giusy Monzillo, Safet Penjić

Let $\Gamma$ be a connected regular graph with an eigenvalue $\lambda$ and corresponding idempotent $E_{\lambda}$. Let ${\cal E}_{\lambda}=\langle J,E_{\lambda}\rangle^\circ$ be the algebra generated by $J$ and $E_\lambda$ with respect to the entrywise-Hadamard product, where $J$ is the all-$1$ matrix. We study the combinatorial structure of a graph $\Gamma$

Magnus Ekman

Computer system simulation studies routinely rely on executing a limited number of short application regions, since full end-to-end simulation is prohibitively time-consuming. To preserve representativeness, existing methods employ either random sampling or phase-based characterization to identify representative regions. In this work, we revisit random sampl

M. Lafarga, D. J. Armstrong, K. Cui, A. Hadjigeorghiou

Space-based missions such as TESS are identifying a wealth of short-period ($\lesssim30$ d) transiting planets. Despite the growing number of confirmed and candidate planets, the sample is still incomplete and highly biased, challenging demographic studies. Moreover, there are still a large number of unconfirmed candidates that can end up being false positiv

F. D. Amaro, R. Antonietti, E. Baracchini, L. Benussi

The CYGNO collaboration is developing a novel strategy for directional Dark Matter searches based on a gaseous Time Projection Chamber (TPC). The detector is optimized for the exploration of light (0.5-50 GeV) WIMPs-like particles and employs a He/CF4 gas mixture at atmospheric pressure, sensitive to both spin-dependent and spin-independent interactions. A k

Aswini Kumar Patra

Statistical inference has undergone a profound transformation over the past decade, evolving from a significance-testing paradigm toward a comprehensive, transparency-driven framework embedded within the broader open science ecosystem. While traditional approaches such as null hypothesis significance testing (NHST) remain widely used, they have been increasi

Mahdi Kooshkbaghi

Far-from-equilibrium kinetic systems collapse onto a hydrodynamic attractor, traditionally approximated by a gradient expansion. While temporal gradient series are non-Borel summable and require transseries completions, the analytic structure of the spatial expansion has remained elusive. Here, we derive exact closed-form Chapman--Enskog coefficients at all

Javier Ferrando, Enrique Lopez-Cuena, Pablo Agustin Martin-Torres, Daniel Hinjos

Sparse Autoencoders uncover thousands of features in vision models, yet explaining these features without requiring human intervention remains an open challenge. While previous work has proposed generating correlation-based explanations based on top activating input examples, we present a fundamentally different alternative based on causal interventions. We

Saumyajit Das, Susovan Pramanik

In this article, we study the inverse scattering problem for the nonlinear fractional Helmholtz equation with cubic nonlinearity in three dimensions, where we recover a compactly supported potential from scattering amplitude.

Surabhi Bhardwaj

Current AI-enabled female sex robots, or "fembots," are primarily designed to simulate female sexual responses through a lens of male-centric bias and pornographic stereotypes. This paper analyses fembot development as a failure in equitable robotics, arguing that these machines perpetuate "epistemic injustice" by prioritizing male hedonistic fantasies over

Braeden Sopp, Adiesha Liyanage, Mingyang Gong, Binhai Zhu

Given \(k\) strings each of length at most $n$, computing the shortest common supersequence of them is a well-known NP-hard problem (when \(k\) is unbounded). On the other hand, when \(k=2\), such a shortest common supersequence can be computed in \(O(n^2)\) time using dynamic programming as a textbook example. In this paper, we consider the problem of compu

Yoshiki Masuyama, Francois G. Germain, Gordon Wichern, Chiori Hori

First-order Ambisonics (FOA) is a standard spatial audio format based on spherical harmonic decomposition. Its zeroth- and first-order components capture the sound pressure and particle velocity, respectively. Recently, physics-informed neural networks have been applied to the spatial interpolation of FOA signals, regularizing the network outputs based on so

Dorottya Demszky, Christopher Mah, Helen Higgins

Teachers face growing pressure to integrate AI tools into their classrooms, yet are rarely positioned as agentic decision-makers in this process. Understanding the criteria teachers use to evaluate AI tools, and the conditions that support such reasoning, is essential for responsible AI integration. We address this gap through a two-day national summit in wh

Damian Delmas

As AI agents become the primary consumers of retrieval APIs, there is an opportunity to expose more of the retrieval pipeline to the caller. flexvec is a retrieval kernel that exposes the embedding matrix and score array as a programmable surface, allowing arithmetic operations on both before selection. We refer to composing operations on this surface at que

Leon Schuermann, Brad Campbell, Branden Ghena, Philip Levis

Tock began 10 years ago as a research operating system developed by academics to help other academics build urban sensing applications. By leveraging a new language (Rust) and new hardware protection mechanisms, Tock enabled Multiprogramming a 64 kB Computer Safely and Efficiently. Today, it is an open source project with a vibrant community of users and con

Parviz Gulshani, Alaaeddine Lahbas

Previously, Nilsson-Ragnarsson solved numerically the conventional cranking model (CCRM3) with deformed oscillator potential and spin-orbit interaction (refer to as Nilsson CCRM3) and predicted the 20Ne ground-state rotational-band yrast energies at the angular momenta I=2,4,6, and 8. However, CCRM3 is semi-classical and phenomenological and breaks a number

Dani Kiyasseh

Mapping surgery is fundamental to developing operative guidelines and enabling autonomous robotic surgery. Recent advances in artificial intelligence (AI) have shown promise in mapping the behaviour of surgeons from videos, yet current models remain narrow in scope, capturing limited behavioural components within single procedures, and offer limited translat

Richard J. Young

Chain-of-thought (CoT) reasoning has been proposed as a transparency mechanism for large language models in safety-critical deployments, yet its effectiveness depends on faithfulness (whether models accurately verbalize the factors that actually influence their outputs), a property that prior evaluations have examined in only two proprietary models, finding

Brendan T. Reed, C. J. Horowitz

Parity-violating electron-scattering provides a largely model independent way of measuring neutron densities in nuclei that has important implications for the structure of nuclei and neutron stars. In this paper we calculate radiative corrections to the parity-violating asymmetry $A_{\rm pv}$ in electron-nucleus scattering including vertex and vacuum polariz

Jiefu Zhang, Nikhil V. Divekar, Chandramouli Krishnan, Robert D. Gregg

Age-related mobility decline is frequently accompanied by a redistribution of joint kinetics, where older adults compensate for reduced ankle function by increasing demand on the hip. Paradoxically, this compensatory shift typically coincides with age-related reductions in maximal hip power. Although robotic exoskeletons can provide immediate energetic benef