February 2025 arXiv papers — page 10

Sourav Mondal, Elaine Wong

One of the primary research interests adhering to next-generation fiber-wireless access networks is human-to-machine/robot (H2M/R) collaborative communications facilitating Industry 5.0. This paper discusses scalable H2M/R communications across large geographical distances that also allow rapid onboarding of new machines/robots as $\sim72\%$ training time is

Ali Hamad

We show a result inspired by a conjecture by Shulman claiming that ultracategories as defined by Lurie are normal colax algebras for a certain pseudo-monad on the category of categories CAT. Such definition allows us to regard left and right ultrafunctors as defined by Lurie as instances of lax/colax algebras morphisms.

Vishnu Kabir Chhabra, Ding Zhu, Mohammad Mahdi Khalili

Previous research has shown that fine-tuning language models on general tasks enhance their underlying mechanisms. However, the impact of fine-tuning on poisoned data and the resulting changes in these mechanisms are poorly understood. This study investigates the changes in a model's mechanisms during toxic fine-tuning and identifies the primary corruption m

Nguyen Xuan Thanh, Anh Duc Le, Quyen Tran, Thanh-Thien Le

Few-shot Continual Relation Extraction is a crucial challenge for enabling AI systems to identify and adapt to evolving relationships in dynamic real-world domains. Traditional memory-based approaches often overfit to limited samples, failing to reinforce old knowledge, with the scarcity of data in few-shot scenarios further exacerbating these issues by hind

Markus Klintborg

We model generalized harmonic functions on rings of differential operators and complex function spaces. The differential operators in the second Weyl-algebra that commute with rotations are described and leads to a natural notion for such functions. We also investigate how such functions are related, and retrieve the cellular decomposition for polyharmonic f

Ivanna Escala, Douglas Grion Filho, Puragra Guhathakurta, Karoline Gilbert

As the only compact elliptical close enough to resolve into individual stars, the satellite dwarf galaxy M32 provides a unique opportunity for exploring the origins of such rare galaxies. In this work, we combined archival and novel Keck/DEIMOS spectroscopy from a southern extension of the Spectroscopic and Photometric Landscape of Andromeda's Stellar Halo (

F. Z. Yang, X. Huang, Hengxin Tan, A. Kundu

The charge density wave (CDW), a translational symmetry breaking electronic liquid, plays a pivotal role in correlated quantum materials, such as high-T$_c$ superconductors and topological semimetals. Recently, CDWs that possibly intertwine with superconductivity and magnetism are observed in various kagome metals. However, the nature of CDWs and the role of

Juntai Cao, Xiang Zhang, Raymond Li, Chuyuan Li

Recent advances in test-time scaling have shown promising results in improving Large Language Model (LLM) performance through strategic computation allocation during inference. While this approach has demonstrated strong improvements in logical and mathematical reasoning tasks, its application to natural language generation (NLG), particularly summarization,

Maite Arcos, Harriet Apel, Toby Cubitt

Simulating complex systems remains an ongoing challenge for classical computers, while being recognised as a task where a quantum computer has a natural advantage. In both digital and analogue quantum simulations the system description is first mapped onto qubits or the physical system of the analogue simulator by an encoding. Previously mathematical definit

Xingjian Gu, Barbara J. Ericson

Even though AI literacy has emerged as a prominent education topic in the wake of generative AI, its definition remains vague. There is little consensus among researchers and practitioners on how to discuss and design AI literacy interventions. The term has been used to describe both learning activities that train undergraduate students to use ChatGPT effect

Aram Apyan, Christopher Cosby, Yongbin Feng, Alp Gelgen

This paper presents performance measurements of a new readout electronics system based on silicon photomultipliers for the PHENIX electromagnetic calorimeter. Installation of the lead-scintillator Shashlik style calorimeter into the SeaQuest/SpinQuest spectrometer has been proposed to broaden the experiment's dark sector search program, an upgrade known as D

Haoxin Liu, Zhiyuan Zhao, Shiduo Li, B. Aditya Prakash

Reasoning ability is crucial for solving challenging tasks. With the advancement of foundation models, such as the emergence of large language models (LLMs), a wide range of reasoning strategies has been proposed, including test-time enhancements, such as Chain-ofThought, and post-training optimizations, as used in DeepSeek-R1. While these reasoning strategi

Yi Zhang, Sanjiv Kapoor

In this paper we consider non-atomic games in populations that are provided with a choice of preventive policies to act against a contagion spreading amongst interacting populations, be it biological organisms or connected computing devices. The spreading model of the contagion is the standard SIR model. Each participant of the population has a choice from a

Saeif Alhazbi, Ahmed Mohamed Hussain, Gabriele Oligeri, Panos Papadimitratos

As Large Language Models (LLMs) become increasingly integrated into many technological ecosystems across various domains and industries, identifying which model is deployed or being interacted with is critical for the security and trustworthiness of the systems. Current verification methods typically rely on analyzing the generated output to determine the so

Mingyuan Wu, Jize Jiang, Haozhen Zheng, Meitang Li

Vision Language Models (VLMs) have achieved remarkable success in a wide range of vision applications of increasing complexity and scales, yet choosing the right VLM model size involves a trade-off between response quality and cost. While smaller VLMs are cheaper to run, they typically produce responses only marginally better than random guessing on benchmar

Albert Tseng, Tao Yu, Youngsuk Park

Low precision (LP) datatypes such as MXFP4 can accelerate matrix multiplications (GEMMs) and reduce training costs. However, directly using MXFP4 instead of BF16 during training significantly degrades model quality. In this work, we present the first near-lossless training recipe that uses MXFP4 GEMMs, which are $2\times$ faster than FP8 on supported hardwar

Aaron Collavini, Stefano Ansoldi

In physics, all dynamical equations that describe fundamental interactions are second order ordinary differential equations in the time derivatives. In the literature, this property is traced back to a result obtained by Ostrogradski in the mid 19th century, which is the technical basis of a 'no-go' theorem for higher order theories. In this work, we review

Nils Deppe, Lavinia Heisenberg, Lawrence E. Kidder, David Maibach

We study the impact of quantum corrections to gravitational waveforms on the gravitational wave memory effect. In certain quantum gravity theories and semi-classical frameworks, black holes (or other exotic compact objects) exhibit reflective properties that cause quasi-normal modes of a binary merger waveform to partially reflect off the horizon. If these r

Keisuke Kamahori, Jungo Kasai, Noriyuki Kojima, Baris Kasikci

Modern automatic speech recognition (ASR) models, such as OpenAI's Whisper, rely on deep encoder-decoder architectures, and their encoders are a critical bottleneck for efficient deployment due to high computational intensity. We introduce LiteASR, a low-rank compression scheme for ASR encoders that significantly reduces inference costs while maintaining tra

Javin Liu, Aryan Vats, Zihao He

The rapid expansion of scientific literature in computer science presents challenges in tracking research trends and extracting key insights. Existing datasets provide metadata but lack structured summaries that capture core contributions and methodologies. We introduce CS-PaperSum, a large-scale dataset of 91,919 papers from 31 top-tier computer science con

Gabriel Kenji Godoy Shimanuki, Alexandre Moreira Nascimento, Lucio Flavio Vismari, Joao Batista Camargo Junior

In recent years, there has been significant development of autonomous vehicle (AV) technologies. However, despite the notable achievements of some industry players, a strong and appealing body of evidence that demonstrate AVs are actually safe is lacky, which could foster public distrust in this technology and further compromise the entire development of thi

Hong Chen, Misha Teplitskiy, David Jurgens

Academic citations are widely used for evaluating research and tracing knowledge flows. Such uses typically rely on raw citation counts and neglect variability in citation types. In particular, citations can vary in their fidelity as original knowledge from cited studies may be paraphrased, summarized, or reinterpreted, possibly wrongly, leading to variation

Maher Hanut, Jonathan Kadmon

Training deep neural networks typically relies on backpropagating high dimensional error signals a computationally intensive process with little evidence supporting its implementation in the brain. However, since most tasks involve low-dimensional outputs, we propose that low-dimensional error signals may suffice for effective learning. To test this hypothes

Isaac Gibbs, Emmanuel J. Candès

We study the coverage properties of full conformal regression in the proportional asymptotic regime where the ratio of the dimension and the sample size converges to a constant. In this setting, existing theory tells us only that full conformal inference is unbiased, in the sense that its average coverage lies at the desired level when marginalized over both

Rahul Karmakar, Srikanth Sastry, Sanat K. Kumar, Tarak K. Patra

Polymer melts with chains undergoing reversible crosslinking have distinctively favorable dynamic properties, e.g., self healing and reprocessability. In these situations there are two relevant elementary time scales: the segmental and the sticker association times. A convenient framework to model these situations is the sticky Rouse model and here we perfor

Vladimir Zaigrajew, Hubert Baniecki, Przemyslaw Biecek

Sparse autoencoders (SAEs) are useful for detecting and steering interpretable features in neural networks, with particular potential for understanding complex multimodal representations. Given their ability to uncover interpretable features, SAEs are particularly valuable for analyzing large-scale vision-language models (e.g., CLIP and SigLIP), which are fu

MD Wahiduzzaman Khan, Mingshan Jia, Xiaolin Zhang, En Yu

Facial appearance editing is crucial for digital avatars, AR/VR, and personalized content creation, driving realistic user experiences. However, preserving identity with generative models is challenging, especially in scenarios with limited data availability. Traditional methods often require multiple images and still struggle with unnatural face shifts, inc

Kai Mei, Wujiang Xu, Minghao Guo, Shuhang Lin

Large language models (LLMs) deliver superior performance but require substantial computational resources and operate with relatively low efficiency, while smaller models can efficiently handle simpler tasks with fewer resources. LLM routing is a crucial paradigm that dynamically selects the most suitable large language models from a pool of candidates to pr

Duván Cardona, Manuel Alejandro Martínez

In this paper we prove $L^p$-estimates for H\"ormander classes of pseudo-differential operators on the torus $\mathbb{T}^n$. The results are presented in the context of the global symbolic calculus of Ruzhansky and Turunen on $\mathbb{T}^n\times\mathbb{Z}^n$ by using the discrete Fourier analysis on the torus which extends the usual ($\rho,\delta$)-H\"ormand

Alberto Villois, Giovanni Dematteis, Yuri V. Lvov, Miguel Onorato

We investigate a generic non-phase invariant Hamiltonian model that governs the dynamics of nonlinear dispersive waves. We give evidence that initial data characterized by random phases naturally evolve into phase correlations between positive and negative wavenumbers, leading to the emergence of non-zero anomalous correlators and negative frequencies. Using

Sari Masri, Huthaifa I. Ashqar, Mohammed Elhenawy

Traffic control in unsignalized urban intersections presents significant challenges due to the complexity, frequent conflicts, and blind spots. This study explores the capability of leveraging Multimodal Large Language Models (MLLMs), such as GPT-4o, to provide logical and visual reasoning by directly using birds-eye-view videos of four-legged intersections.

Mohammad Abu Tami, Mohammed Elhenawy, Huthaifa I. Ashqar

Traffic safety remains a vital concern in contemporary urban settings, intensified by the increase of vehicles and the complicated nature of road networks. Traditional safety-critical event detection systems predominantly rely on sensor-based approaches and conventional machine learning algorithms, necessitating extensive data collection and complex training

Yanhong Li, David C. Anastasiu

Multivariate time series (MTS) forecasting is vital in fields like weather, energy, and finance. However, despite deep learning advancements, traditional Transformer-based models often diminish the effect of crucial inter-variable relationships by singular token embedding and struggle to effectively capture complex dependencies among variables, especially in

Sajjad Saleem, Muhammad Imran Sharif

The lungs are the essential organs of respiration, and this system is significant in the carbon dioxide and exchange between oxygen that occurs in human life. However, several lung diseases, which include pneumonia, tuberculosis, COVID-19, and lung cancer, are serious healthiness challenges and demand early and precise diagnostics. The methodological study h

Asha Ramanujam, Can Li

Systems across different industries consist of interrelated processes and decisions in different time scales including long-time decisions and short-term decisions. To optimize such systems, the most effective approach is to formulate and solve multi-time scale optimization models that integrate various decision layers. In this tutorial, we provide an overvi

Richard F. Lebed, Steven R. Martinez

Using the diabatic formalism, a rigorous generalization of the Born-Oppenheimer approximation, we study the effects of introducing simple meson-meson molecular potentials to an established diquark model for tetraquark states, and calculate mixed bound states composed of both diquark-antidiquark and meson-meson molecular components. We examine the behavior of

Kaan Ozkara, Tao Yu, Youngsuk Park

As the parameters of Large Language Models (LLMs) have scaled to hundreds of billions, the demand for efficient training methods -- balancing faster computation and reduced memory usage without sacrificing accuracy -- has become more critical than ever. In recent years, various mixed precision strategies, which involve different precision levels for optimiza

Jianing Zhang, Evan Chen, Dong-Jun Han, Chaoyue Liu

Vertical Federated Learning (VFL) enables collaborative model training across feature-partitioned devices, yet its reliance on device-server information exchange introduces significant communication overhead and privacy risks. Downlink communication from the server to devices in VFL exposes gradient-related signals of the global loss that can be leveraged in

Lisa-Marie Koll, Simon Vendelbo Bylling Jensen, Pieter J. van Essen, Brian de Keijzer

Interferometry is a fundamental technique in physics, enabling precise measurements through the interference of waves. High-harmonic generation (HHG) in solids has emerged as a powerful method for probing ultrafast electronic dynamics within crystalline structures. In this study, we employed extreme ultraviolet (XUV) high-harmonic interferometry with phase-l

Adam Lipowski, Antonio Luis Ferreira, Dorota Lipowska, Aleksandra Napierala-Batygolska

It is known that on directed graphs, the correlations between neighbours of a given site vanish and thus simple mean-field-like arguments can be used to describe exactly the behaviour of Ising-like systems. We analyse heterogeneous modifications of such models where a fraction of agents is driven by the voter or the antivoter dynamics. It turns out that vote

Joana C. Costa, Tiago Roxo, Hugo Proença, Pedro R. M. Inácio

State-of-the-art defense mechanisms are typically evaluated in the context of white-box attacks, which is not realistic, as it assumes the attacker can access the gradients of the target network. To protect against this scenario, Adversarial Training (AT) and Adversarial Distillation (AD) include adversarial examples during the training phase, and Adversaria

William Thompson, Eric Nielsen, Jean-Baptiste Ruffio, Sarah Blunt

The mature Jovian planet $\varepsilon$ Eridani b orbits one of the closest sun-like stars at a moderate separation of 3.5 AU, presenting one of the best opportunities to image a true analog to a solar system planet. We perform a thorough joint reanalysis and cross-validation of all available archival radial velocity and astrometry data, combining data from e

Zhuohang Li, Chao Yan, Nicholas J. Jackson, Wendi Cui

Advancements in Large Vision-Language Models (LVLMs) have demonstrated promising performance in a variety of vision-language tasks involving image-conditioned free-form text generation. However, growing concerns about hallucinations in LVLMs, where the generated text is inconsistent with the visual context, are becoming a major impediment to deploying these

Felipe Rivera-Mesas

In this article we establish some results that allow to deduce the continuity of homomorphisms of (topological) abelian groups from commutative diagrams. In particular, we present a new topological version of the classical Five-Lemma. These results aim to be applied in duality results between cohomology groups in arithmetical contexts. In such a topological-

Gefen Baranes, Madelyn Cain, J. Pablo Bonilla Ataides, Dolev Bluvstein

Qubit loss errors constitute a dominant source of noise in many quantum hardware systems, particularly in neutral atom quantum computers. We develop a theoretical framework to effectively detect and correct loss errors in logical algorithms and leverage such loss information in decoding. Considering general quantum error correction codes and logical circuits

José Antonio García-Hernández, Victor Muñoz-Vitelly, Wolfgang Bietenholz

In the Standard Model, the difference between the baryon number $B$ and the lepton number $L$ is conserved, which represents a symmetry that is global and exact, and therefore unnatural. We turn it into a naturally exact, local symmetry by coupling the quantum number $B-L$ to an Abelian gauge field. Gauge anomalies are cancelled by adding right-handed neutri

Zijian Zhang, Bin Luo, Linhua Jiang, W. N. Brandt

We present a systematic investigation of extremely X-ray variable active galactic nuclei (AGNs) in the $\approx 5.3~{\rm deg}^2$ XMM-SERVS XMM-LSS region. Eight variable AGNs are identified with rest-frame 2 keV flux density variability amplitudes around 6-12. We comprehensively analyze the X-ray and multiwavelength data to probe the origin of their extreme

Gianluca Cena, Lucia Seno, Stefano Scanzio

Having everything interconnected through the Internet, including vehicle onboard systems, is making security a primary concern in the automotive domain as well. Although Ethernet and CAN XL provide link-level security based on symmetric cryptography, they do not support origin authentication for multicast transmissions. Asymmetric cryptography is unsuitable

Henry Lei, Joshua Aurand, Zachary S. Lippay, Sean Phillips

With the increasingly congested and contested space environment, safe and effective satellite operation has become increasingly challenging. As a result, there is growing interest in autonomous satellite capabilities, with common machine learning techniques gaining attention for their potential to address complex decision-making in the space domain. However,

Valeri V. Makarov

The orbital solutions for astrometric (unresolved) binary stars provided in the Gaia mission Data Release 3 reveal an obvious deficit of face-on orbits with line-of-sight inclinations close to 0 or $\pi$. This is shown to be an intrinsic mathematical feature of the orbit estimation technique involving the intermediate Thiele-Innes parameters, which are trans

Botond Barta, Endre Hamerlik, Milán Konor Nyist, Judit Ács

We present HuAMR, the first Abstract Meaning Representation (AMR) dataset and a suite of large language model-based AMR parsers for Hungarian, targeting the scarcity of semantic resources for non-English languages. To create HuAMR, we employed Llama-3.1-70B to automatically generate silver-standard AMR annotations, which we then refined manually to ensure qu

Ramon Guerrero-Suarez, Adithya Suresh, Tanmay Maiti, Shuang Liang

The edge modes of fractional quantum Hall liquids are described by chiral Luttinger liquid theory. Despite many years of experimental investigation fractional quantum Hall edge modes remain enigmatic with significant discrepancies between experimental observations and detailed predictions of chiral Luttinger liquid theory. Here we report measurements of tunn

Madeline A. Marshall, Rogier A. Windhorst, Giovanni Ferrami, S. P. Willner

We present JWST NIRSpec integral field spectroscopy observations of the z=5.89 quasar NDWFS J1425+3254 from 0.6-5.3 microns, covering the rest-frame ultraviolet and optical at a spectral resolution of R~100. The quasar has a black hole mass of $M_{\rm{BH}}=(1.4\substack{+3.1\\-1.0})\times10^9 M_\odot$ and an Eddington ratio of $L_{\rm{Bol}}/L_{\rm{Edd}}=0.3\

Marios-Nektarios Stamatopoulos, Jakub Haluska, Elias Small, Jude Marroush

A novel autonomous chunk-based aerial additive manufacturing framework is presented, supported with experimental demonstration advancing aerial 3D printing. An optimization-based decomposition algorithm transforms structures into sub-components, or chunks, treated as individual tasks coordinated via a dependency graph, ensuring sequential assignment to UAVs

Jin Peng Zhou, Kaiwen Wang, Jonathan Chang, Zhaolin Gao

Reinforcement learning (RL) post-training is crucial for LLM alignment and reasoning, but existing policy-based methods, such as PPO and DPO, can fall short of fixing shortcuts inherited from pre-training. In this work, we introduce $Q\sharp$, a value-based algorithm for KL-regularized RL that guides the reference policy using the optimal regularized $Q$ fun

Aurore Poirier, Erven Rohou, Manuel Serrano

Context: Just-in-Time (JIT) compilers are able to specialize the code they generate according to a continuous profiling of the running programs. This gives them an advantage when compared to Ahead-of-Time (AoT) compilers that must choose the code to generate once for all. Inquiry: Is it possible to improve the performance of AoT compilers by adding Dynamic B

Dimi Racordon, Eugene Flesselle, Cao Nguyen Pham

Type classes are a popular tool for implementing generic algorithms and data structures without loss of efficiency, bridging the gap between parametric and ad-hoc polymorphism. Since their initial development in Haskell, they now feature prominently in numerous other industry-ready programming languages, notably including Swift, Rust, and Scala. The success

Kechen Li, Wenqi Zhu, Coralia Cartis, Tianbo Ji

Large Language Models (LLMs) have achieved human-level proficiency across diverse tasks, but their ability to perform rigorous mathematical problem solving remains an open challenge. In this work, we investigate a fundamental yet computationally intractable problem: determining whether a given multivariate polynomial is nonnegative. This problem, closely rel

Neil Epstein

The Fundamental Theorem of Algebra can be thought of as a statement about the real numbers as a space, considered as an algebraic set over the real numbers as a field. This paper introduces what it means for an algebraic set or affine variety over a field to be fundamental, in a way that encompasses the Fundamental Theorem of Algebra as a special case. The r

Nahuel Palumbo, Guillermo Polito, Stéphane Ducasse, Pablo Tesone

Virtual Machines (VMs) combine interpreters and just-in-time (JIT) compiled code to achieve good performance. However, implementing different execution engines increases the cost of developing and maintaining such solutions. JIT compilers based on meta-compilation cope with these issues by automatically generating optimizing JIT compilers. This leaves open t

Sam Caldwell, Tony Garnock-Jones, Matthias Felleisen

Context: Developers have come to appreciate the simplicity of message-passing actors for concurrent programming tasks. The actor model of computation is easy to grasp; it is just a conversation among actors with a common goal. Importantly, it eliminates some basic pitfalls of the dominant shared-memory model, most critically data races. Inquiry: A close look

Achuth Chandrasekhar, Omid Barati Farimani, Olabode T. Ajenifujah, Janghoon Ock

This paper presents the development and application of a Large Language Model Retrieval-Augmented Generation (LLM-RAG) system tailored for nanotechnology research. The system leverages the capabilities of a sophisticated language model to serve as an intelligent research assistant, enhancing the efficiency and comprehensiveness of literature reviews in the n

Anton Risberg Alaküla, Niklas Fors, Emma Söderberg

Context: Developing compilers and static analysis tools ("language tools") is a difficult and time-consuming task. We have previously presented *property probes*, a technique to help the language tool developer build understanding of their tool. A probe presents a live view into the internals of the compiler, enabling the developer to see all the intermediat

Asif Al Suny, Tazrian Noor, Md. Hasibul Hossain, A. F. M. Afnan Uzzaman Sheikh

Composite light-trapping structures offer a promising approach to achieving broadband absorption and high efficiency in thin-film solar cells (TFSCs) in order to accelerate sustainable energy solutions. As the leading material in thin-film solar technology, cadmium telluride (CdTe) faces challenges from surface reflective losses across the solar spectrum and

Mathijs Saey, Joeri De Koster, Wolfgang De Meuter

Context: Distributed Stream Processing Frameworks (DSPFs) are popular tools for expressing real-time Big Data applications that have to handle enormous volumes of data in real time. These frameworks distribute their applications over a cluster in order to scale horizontally along with the amount of incoming data. Inquiry: Crucial for the performance of such

Philémon Houdaille, Djamel Eddine Khelladi, Benoit Combemale, Gunter Mussbacher

As software grows increasingly complex, the quantity and diversity of concerns to be addressed also rises. To answer this diversity of concerns, developers may end up using multiple programming languages in a single software project, a practice known as polyglot programming. This practice has gained momentum with the rise of execution platforms capable of su

Lukas Makor, Sebastian Kloibhofer, Peter Hofer, David Leopoldseder

Data structures are a cornerstone of most modern programming languages. Whether they are provided via separate libraries, built into the language specification, or as part of the language's standard library -- data structures such as lists, maps, sets, or arrays provide programmers with a large repertoire of tools to deal with data. Moreover, each kind of da

Tom Beckmann, Joana Bergsiek, Eva Krebs, Toni Mattis

Exploratory programming involves open-ended tasks. To evaluate their progress on these, programmers require frequent feedback and means to tell if the feedback they observe is bringing them in the right direction. Collecting, comparing, and sharing feedback is typically done through ad-hoc means: relying on memory to compare outputs, code comments, or manual

Tetsuo Kamina, Tomoyuki Aotani, Hidehiko Masuhara

Context: Many systems require receiving data from multiple information sources, which act as distributed network devices that asynchronously send the latest data at their own pace to generalize various kinds of devices and connections, known as the Internet of Things (IoT). These systems often perform computations both **reactively** and **retroactively** on

Felipe Bañados Schwerter, Ronald Garcia, Reid Holmes, Karim Ali

A gradual type system allows developers to declare certain types to be enforced by the compiler (i.e., statically typed), while leaving other types to be enforced via runtime checks (i.e., dynamically typed). When runtime checks fail, debugging gradually typed programs becomes cumbersome, because these failures may arise far from the original point where an

Ji-Hun Oh, Kianoush Falahkheirkhah, Rohit Bhargava

Label-free chemical imaging holds significant promise for improving digital pathology workflows, but data acquisition speed remains a limiting factor. To address this gap, we propose an adaptive strategy-initially scan the low information (LI) content of the entire tissue quickly, identify regions with high aleatoric uncertainty (AU), and selectively re-imag

Avrajit Ghosh, Soo Min Kwon, Rongrong Wang, Saiprasad Ravishankar

Deep neural networks trained using gradient descent with a fixed learning rate $\eta$ often operate in the regime of "edge of stability" (EOS), where the largest eigenvalue of the Hessian equilibrates about the stability threshold $2/\eta$. In this work, we present a fine-grained analysis of the learning dynamics of (deep) linear networks (DLNs) within the d

Tetsuo Kamina, Tomoyuki Aotani, Hidehiko Masuhara

Context: Multi-schema-version data management (MSVDM) is the database technology that simultaneously supports multiple schema versions of one database. With the technology, multiple versions of one software system can co-exist and exchange data even when the system's data structure evolves along with versions. Inquiry: While there have been developed MSVDM t

Zachary S. Rowland, Saverio Perugini

Human-computer dialog plays a prominent role in interactions conducted at kiosks (e.g., withdrawing money from an atm or filling your car with gas), on smartphones (e.g., installing and configuring apps), and on the web (e.g., booking a flight). Some human-computer dialogs involve an exchange of system-initiated and user-initiated actions. These dialogs are

Dmitri E. Kharzeev, Jacob Levitt, Carlos Trallero-Herrero

The surface of metal nanoparticles can support plasmonic excitations. These excitations dramatically amplify the electric field of incident light (by several orders of magnitude), potentially ionizing the irradiated nanoparticles in a strong field regime. Under specific conditions, a resonant enhancement of the electric field \textit{inside} a hollow nanoshe

Wenxin Jiang, Berk Çakar, Mikola Lysenko, James C. Davis

Package confusion attacks such as typosquatting threaten software supply chains. Attackers make packages with names that syntactically or semantically resemble legitimate ones, tricking engineers into installing malware. While prior work has developed defenses against package confusions in some software package registries, notably NPM, PyPI, and RubyGems, ga

Emily Ross, Yuval Kansal, Jake Renzella, Alexandra Vassar

Large language models (LLMs) are increasingly being explored in higher education, yet their effectiveness as teaching agents remains underexamined. In this paper, we present the development of GuideLM, a fine-tuned LLM designed for programming education. GuideLM has been integrated into the Debugging C Compiler (DCC), an educational C compiler that leverages

Luca Chiodini, Juha Sorva, Arto Hellas, Otto Seppälä

Context: Graphics is a popular domain for teaching introductory programming in a motivating way, even in text-based programming languages. Over the last few decades, a large number of libraries using different approaches have been developed for this purpose. Inquiry: Prior work in introductory programming that uses graphics as input and output has shown posi

Long Minh Bui, Tho Tran Huu, Duy Dinh, Tan Minh Nguyen

Transformers have increasingly become the de facto method to model sequential data with state-of-the-art performance. Due to its widespread use, being able to estimate and calibrate its modeling uncertainty is important to understand and design robust transformer models. To achieve this, previous works have used Gaussian processes (GPs) to perform uncertaint

Mirko Mizzoni, Pieter van Goor, Antonio Franchi

Systems with a high number of inputs compared to the degrees of freedom (e.g. a mobile robot with Mecanum wheels) often have a minimal set of energy-efficient inputs needed to achieve a main task (e.g. position tracking) and a set of energy-intense inputs needed to achieve an additional auxiliary task (e.g. orientation tracking). This letter presents a unifi

A. A. Herasymchuk, E. V. Gorbar, P. O. Sukhachov

We calculate the viscoelasticity tensor for altermagnets and formulate the corresponding hydrodynamic equations. The anisotropy of altermagnetic Fermi surfaces allows for additional terms in the viscoelasticity tensor and is manifested in transport properties, including electron and spin flows in a channel and nonlocal responses. In the channel geometry, the

Marina Shimchenko, Erik Österlund, Tobias Wrigstad

In modern server computing, efficient CPU resource usage is often traded for latency. Garbage collection is a key aspect of memory management in programming languages like Java, but it often competes with application threads for CPU time, leading to delays in processing requests and consequent increases in latency. This work explores if opportunistic schedul

Nils Leber, Luis Adrián Alanís Rodríguez, Alessandro Ferreri, Andreas Wolfgang Schell

We analyze the domain of validity of a quantum optical model that describes the effects of gravitational redshift on the quantum state of photons that propagate in curved spacetime. This model assumes that the modes defining the initial state of the photon are mixed with an auxiliary environment mode via an effective multimode mixer. We find that the model,

Flavio Rossetti, Alex Vañó-Viñuales

In this numerical work, we deal with two distinct problems concerning the propagation of waves in cosmological backgrounds. In both cases, we employ a spacetime foliation given in terms of compactified hyperboloidal slices. These slices intersect future null infinity, so our method is well-suited to study the long-time behaviour of waves. Moreover, our const

Eva Brucherseifer, Marco Marquard, Martin Hellmann, Andrea Tundis

The Digital Twin (DT) offers a novel approach to the management of critical infrastructures, including energy, water, traffic, public health, and communication systems, which are indispensable for the functioning of modern societies. The increasing complexity and interconnectedness of these infrastructures necessitate the development of robust disaster respo

F. Blaschke, T. Romanczukiewicz, K. Slawinska, A. Wereszczynski

We show that in the complex $\phi^6$ theory the oscillon, together with its spectral structure and the amplitude modulation, arises from the exited Q-ball carrying the bound and the quasi-normal modes.

Li-Wei Chen, Ombretta Strafforello, Anne-Sofie Maerten, Tinne Tuytelaars

Image aesthetic assessment (IAA) evaluates image aesthetics, a task complicated by image diversity and user subjectivity. Current approaches address this in two stages: Generic IAA (GIAA) models estimate mean aesthetic scores, while Personal IAA (PIAA) models adapt GIAA using transfer learning to incorporate user subjectivity. However, a theoretical understa

Hu Wang, Ibrahim Almakky, Congbo Ma, Numan Saeed

Model merging is an effective strategy to merge multiple models for enhancing model performances, and more efficient than ensemble learning as it will not introduce extra computation into inference. However, limited research explores if the merging process can occur within one model and enhance the model's robustness, which is particularly critical in the me

Chenjing Bu, Andrés Ibáñez Núñez, Tasuki Kinjo

This is the second paper in a series on intrinsic Donaldson-Thomas theory, a framework for studying the enumerative geometry of general algebraic stacks. In this paper, we present the construction of Donaldson-Thomas invariants for general $(-1)$-shifted symplectic derived Artin stacks, generalizing the constructions of Joyce-Song and Kontsevich-Soibelman fo

B. Hamil, B. C. Lütfüoğlu

We analyze the effects of noncommutativity on phantom Reissner-Nordstr\"om-Anti-de Sitter black holes by modeling mass and charge distributions with Lorentzian profiles. The modified metric function exhibits significant deviations from the classical case, leading to changes in the horizon structure and the suppression of singularities. Through a comparative

Smit Desai, Mateusz Dubiel, Nima Zargham, Thomas Mildner

The emergence of Large Language Models (LLMs) has revolutionized Conversational User Interfaces (CUIs), enabling more dynamic, context-aware, and human-like interactions across diverse domains, from social sciences to healthcare. However, the rapid adoption of LLM-based personas raises critical ethical and practical concerns, including bias, manipulation, an

T. M. Koskamp, M. I. Katsnelson, K. J. A. Reijnders

Plasmons are likely to play an important role in integrated photonic ciruits, because they strongly interact with light and can be confined to subwavelength scales. These plasmons can be guided and controlled by plasmonic waveguides, which can be created by patterning different materials or by structuring the dielectric environment. We have constructed a sem

Kyle Fogarty, Jing Yang, Chayan Kumar Patodi, Jack Foster

Accurate 3D foot reconstruction is crucial for personalized orthotics, digital healthcare, and virtual fittings. However, existing methods struggle with incomplete scans and anatomical variations, particularly in self-scanning scenarios where user mobility is limited, making it difficult to capture areas like the arch and heel. We present a novel end-to-end

Paul B. Larson, Grigor Sargsyan, Trevor Wilson

The consistency of the theory $\mathsf{ZF} + \mathsf{AD}_{\mathbb{R}} + {}$``every set of reals is universally Baire'' is proved relative to $\mathsf{ZFC} + {}$``there is a cardinal that is a limit of Woodin cardinals and of strong cardinals.'' The proof is based on the derived model construction, which was used by Woodin to show that the theory $\mathsf{ZF}

Yixiong Chen, Shawn Xu, Andrew Sellergren, Yossi Matias

Vision-language models have proven to be of great benefit for medical image analysis since they learn rich semantics from both images and reports. Prior efforts have focused on better alignment of image and text representations to enhance image understanding. However, though explicit reference to a prior image is common in Chest X-Ray (CXR) reports, aligning

Soumyabrata Chaudhuri, Pranav Purkar, Ritwik Raghav, Shubhojit Mallick

Recent advancements in probing Large Language Models (LLMs) have explored their latent potential as personalized travel planning agents, yet existing benchmarks remain limited in real world applicability. Existing datasets, such as TravelPlanner and TravelPlanner+, suffer from semi synthetic data reliance, spatial inconsistencies, and a lack of key travel co

João-Vitor Zacchi, Edoardo Clementi, Núria Mata

Automated driving technologies promise substantial improvements in transportation safety, efficiency, and accessibility. However, ensuring the reliability and safety of Autonomous Vehicles in complex, real-world environments remains a significant challenge, particularly during the early stages of software development. Existing software development environmen

James M. De Buizer, Wanggi Lim, James T. Radomski, Nicole Karnath

This study examines the mid-infrared properties of Giant HII (GHII) regions in the Milky Way's Central Molecular Zone (CMZ) -- Sgr B1, Sgr B2, and Sgr C -- using SOFIA-FORCAST imaging at 25 and 37 microns. It compares these mid-infrared data with previous multi-wavelength observations to explore their present star formation activity and global properties. Th

Natalia Jonard-Pérez, Ananda López-Poo

An $n$-mean (also called a ''topological social choice rule'') on a topological space $X$ is a continuous function $p:X^n\to X$ satisfying $p(x,\dots, x)=x$ for every $x\in X$ and $p(x_1,\dots, x_n)=p(x_{\sigma(1)},\dots x_{\sigma(n)})$ for any permutation $\sigma$ of $\{1,\dots, n\}$. If, in addition, $X$ is a $G$-space and $p$ is equivariant with respect t

Julius Broomfield, Kartik Sharma, Srijan Kumar

Large language models (LLMs) have recently demonstrated remarkable advancements in embodying diverse personas, enhancing their effectiveness as conversational agents and virtual assistants. Consequently, LLMs have made significant strides in processing and integrating multimodal information. However, even though human personas can be expressed in both text a