November 2024 arXiv papers — page 66

Qiuyu Ren

We show that if there exists a knot in $S^3$ that admits purely cosmetic surgeries, then there exists a hyperbolic one with this property.

Chaitanya Rahalkar, Anushka Virgaonkar

Secure, reliable, and fast transfer of files across the Internet is a problem attempted to be solved through many application-layer protocols. In this paper, we aim to design a secure, reliable, opendesign, and performant file transfer protocol that is inspired by the WebRTC protocol stack. Traditionally, transferring files involves a publicly exposed (avail

Anthony Z. Liu, Xinhe Wang, Jacob Sansom, Yao Fu

Large Language Models (LLMs) demonstrate strong abilities in common-sense reasoning and interactive decision-making, but often struggle with complex, long-horizon planning tasks. Recent techniques have sought to structure LLM outputs using control flow and other code-adjacent techniques to improve planning performance. These techniques include using variable

Cheaheon Lim

We introduce resampled mutual information (ResMI), a novel measure of clustering similarity that combines insights from information theoretic and pair counting approaches to clustering and community detection. Similar to chance-corrected measures, ResMI satisfies the constant baseline property, but it has the advantages of not requiring adjustment terms and

Qinghui Sun, Sharon Xuesong Wang, Tianjun Gan, Chenyang Ji

The Sun is depleted in refractory elements compared to nearby solar twins, which may be linked to the formation of giant or terrestrial planets. Here we present high-resolution, high signal-to-noise spectroscopic data for 17 solar-like stars hosting planets, obtained with Magellan II/MIKE, to investigate whether this depletion is related to planet formation.

Arash Arabi Ardehali, Hare Krishna

In the standard $\mathcal{N}=(4,4)$ AdS$_3$/CFT$_2$ with $\mathrm{sym}^N(T^4)$, as well as the $\mathcal{N}=(2,2)$ Datta-Eberhardt-Gaberdiel variant with $\mathrm{sym}^N(T^4/\mathbb{Z}_2)$, supersymmetric index techniques have not been applied so far to the CFT states with target-space momentum or winding. We clarify that the difficulty lies in a central ext

Edward Honda, Keh-Kuan Sun

We provide and axiomatize a representation for preferences over lotteries that generalizes the expected utility model. Since the representation uses different utility functions to evaluate different lotteries, the preferences can be interpreted as coming from individuals that have context-dependent attitudes toward risks. The model enables generating various

Yiwei Tang, Judy Huixia Wang, Deyuan Li

The estimation of conditional quantiles at extreme tails is of great interest in numerous applications. Various methods that integrate regression analysis with an extrapolation strategy derived from extreme value theory have been proposed to estimate extreme conditional quantiles in scenarios with a fixed number of covariates. However, these methods prove in

Botao Wang, Jia Li, Heng Chang, Keli Zhang

In this work, we discover that causal inference provides a promising approach to capture heterophilic message-passing in Graph Neural Network (GNN). By leveraging cause-effect analysis, we can discern heterophilic edges based on asymmetric node dependency. The learned causal structure offers more accurate relationships among nodes. To reduce the computationa

Jingtao Ding, Yunke Zhang, Yu Shang, Jie Feng

The concept of world models has garnered significant attention due to advancements in multimodal large language models such as GPT-4 and video generation models such as Sora, which are central to the pursuit of artificial general intelligence. This survey offers a comprehensive review of the literature on world models. Generally, world models are regarded as

Artem Lopatin, Alexander N. Rybalov

Working over the split octonions over an algebraically closed field, we solve all polynomial equations in which all the coefficients but the constant term are scalar. As a consequence, we calculate the n-th roots of an octonion.

Qian Yu, Zhen Xu, Zong Ke

In the context of globalization and the rapid expansion of the digital economy, anti-money laundering (AML) has become a crucial aspect of financial oversight, particularly in cross-border transactions. The rising complexity and scale of international financial flows necessitate more intelligent and adaptive AML systems to combat increasingly sophisticated m

Longwei Zou, Yan Liu, Jiamu Kang, Tingfeng Liu

The revolutionary capabilities of Large Language Models (LLMs) are attracting rapidly growing popularity and leading to soaring user requests to inference serving systems. Caching techniques, which leverage data reuse to reduce computation, offer opportunities to optimize the performance of LLM inference engines. On the one hand, the low-level key-value (KV)

Yu Cheng, Zhenlin Luo, Zhaoxia Yin

With the rapid evolution of the Internet, the vast amount of data has created opportunities for fostering the development of steganographic techniques. However, traditional steganographic techniques encounter challenges due to distortions in online social networks, such as JPEG recompression. Presently, research into the lossy operations of spatial truncatio

Xiangyu Ding, Lisa Hui Sun

In the study of theta series and partition functions, Andrews and Merca, Guo and Zeng independently conjectured that a truncated Jacobi triple product series has nonnegative coefficients. This conjecture was proved analytically by Mao and combinatorially by Yee. In 2021, Merca proposed a stronger version of the conjecture, that is, for positive integers $1\l

Zhuowei Zhao, Junhao Gan, Boyu Ruan, Zhifeng Bao

We study structural clustering on graphs in dynamic scenarios, where the graphs can be updated by arbitrary insertions or deletions of edges/vertices. The goal is to efficiently compute structural clustering results for any clustering parameters $\epsilon$ and $\mu$ given on the fly, for arbitrary graph update patterns, and for all typical similarity measure

Hiroki Kawai, Masamune Oguri

Icarus is an individual star observed near the macro-critical curve of the MACS J1149 cluster, with the magnification factor estimated to be an order of thousands. Since microlenses near the macro-critical curve influence the number of such high-magnification events, the observed occurrence of Icarus-like events is expected to provide a useful constraint on

Phong C. H. Nguyen, Joseph B. Choi, Quang-Trung Luu

Many applications in computational and experimental fluid mechanics require effective methods for reconstructing the flow fields from limited sensor data. However, this task remains a significant challenge because the measurement operator, which provides the punctual sensor measurement for a given state of the flow field, is often ill-conditioned and non-inv

Changhai Zhou, Shiyang Zhang, Yuhua Zhou, Zekai Liu

Fine-tuning large language models (LLMs) under resource constraints is a significant challenge in deep learning. Low-Rank Adaptation (LoRA), pruning, and quantization are all effective methods for improving resource efficiency. However, combining them directly often results in suboptimal performance, especially with uniform quantization across all model laye

Jing Chen, Masaru Nagaso, Mijian Xu, Ping Tong

TomoATT is an open-source software package, aiming at determining seismic velocity and azimuthal anisotropy based on adjoint-state traveltime tomography methods. Key features of TomoATT include Eikonal equation modeling, adjoint-state method, sensitivity kernel regularization, and multi-level parallelization. Through several toy experiments, we demonstrate T

Linying Lv

I examine the value of information from sell-side analysts by analyzing a large corpus of their written reports. Using embeddings from state-of-the-art large language models, I show that qualitative information in analyst reports explains above 10% of contemporaneous stock returns out-of-sample, a value that is more economically significant than quantitative

David Conlon, Jacob Fox, Benjamin Gunby, Xiaoyu He

A natural open problem in Ramsey theory is to determine those $3$-graphs $H$ for which the off-diagonal Ramsey number $r(H, K_n^{(3)})$ grows polynomially with $n$. We make substantial progress on this question by showing that if $H$ is tightly connected or has at most two tight components, then $r(H, K_n^{(3)})$ grows polynomially if and only if $H$ is cont

Chang Sun, Bo Qin

Target speaker extraction (TSE) is a technique for isolating a target speaker's voice from mixed speech using auxiliary features associated with the target speaker. It is another attempt at addressing the cocktail party problem and is generally considered to have more practical application prospects than traditional speech separation methods. Although academ

Xiaowei Xi, Song Leng, Yuqing Gong, Dalin Li

Advertising click-through rate (CTR) prediction aims to forecast the probability that a user will click on an advertisement in a given context, thus providing enterprises with decision support for product ranking and ad placement. However, CTR prediction faces challenges such as data sparsity and class imbalance, which adversely affect model training effecti

Hanbat Jeong

This paper introduces a novel spatial interaction model to explore the decision-making processes of a resource allocator and local agents, with central and local governments serving as empirical representations. The model captures two key features: (i) resource allocations from the allocator to local agents and the resulting strategic interactions, and (ii)

Jinlong Hu, Zhizhe Rao, Xingchen Liu, Lihao Deng

The increasing prevalence of cloud-native technologies, particularly containers, has led to the widespread adoption of containerized deployments in data centers. The advancement of deep neural network models has increased the demand for container-based distributed model training and inference, where frequent data transmission among nodes has emerged as a sig

Patricia Paskov, Lukas Berglund, Everett Smith, Lisa Soder

General-purpose AI evaluations have been proposed as a promising way of identifying and mitigating systemic risks posed by AI development and deployment. While GPAI evaluations play an increasingly central role in institutional decision- and policy-making -- including by way of the European Union AI Act's mandate to conduct evaluations on GPAI models present

Ruiyuan Gao, Kai Chen, Bo Xiao, Lanqing Hong

The rapid advancement of diffusion models has greatly improved video synthesis, especially in controllable video generation, which is vital for applications like autonomous driving. Although DiT with 3D VAE has become a standard framework for video generation, it introduces challenges in controllable driving video generation, especially for geometry control,

Anton A. Stoorvogel, Ali Saberi, Zhenwei Liu

In this paper, we propose a new framework for synchronization of heterogeneous multi agent system which we refer to as weak synchronization. This new framework of synchronization is based on achieving the network stability in the absence of any information on communication network including the connectivity. Here by network stability, we mean that in the bas

Chenyang Wu, Qian Chen, Akang Wang, Tian Ding

Convex quadratically constrained quadratic programs (QCQPs) involve finding a solution within a convex feasible region defined by quadratic constraints while minimizing a convex quadratic objective function. These problems arise in various industrial applications, including power systems and signal processing. Traditional methods for solving convex QCQPs pri

Max Sun Zhou

We compute the Brown measure of the non-normal operators $X = p + i q$, where $p$ and $q$ are Hermitian, freely independent, and have spectra consisting of $2$ atoms. The computation relies on the model of the non-trivial part of the von Neumann algebra generated by 2 projections as $2 \times 2$ random matrices. We observe that these measures are supported o

Moisés H. Ibarra Miranda, Lars W. Osterberg, Dev H. Shah, Kartik Regulagadda

Structural coloration, a color-generation mechanism often found in nature, arises from light-matter interactions such as diffraction, interference and scattering, with micro- and nanostructured elements. Herein, we systematically study anisotropic, 3D-architected grating structures with polarization-tunable optical properties, inspired by the vivid blue of M

Christopher Nguyen, William Nguyen, Atsushi Suzuki, Daisuke Oku

Large Language Models (LLMs) have demonstrated the potential to address some issues within the semiconductor industry. However, they are often general-purpose models that lack the specialized knowledge needed to tackle the unique challenges of this sector, such as the intricate physics and chemistry of semiconductor devices and processes. SemiKong, the first

Hao Wang, Yuan-Chuan Zou, Qing Wen Wu

We analyze 192 sets of binary black hole merger data in eccentric orbits obtained from RIT, decomposing the radiation energy into three distinct phases through time: inspiral, late inspiral to merger, and ringdown. Our investigation reveals a universal oscillatory behavior in radiation energy across these phases, influenced by varying initial eccentricities.

Adithya V Ganesan, Vasudha Varadarajan, Yash Kumar Lal, Veerle C. Eijsbroek

Use of large language models such as ChatGPT (GPT-4/GPT-5) for mental health support has grown rapidly, emerging as a promising route to assess and help people with mood disorders like depression. However, we have a limited understanding of these language models' schema of mental disorders, that is, how they internally associate and interpret symptoms of suc

Markus Dahlmanns, Felix Heidenreich, Johannes Lohmöller, Jan Pennekamp

Internet-wide studies provide extremely valuable insight into how operators manage their Internet of Things (IoT) deployments in reality and often reveal grievances, e.g., significant security issues. However, while IoT devices often use IPv6, past studies resorted to comprehensively scan the IPv4 address space. To fully understand how the IoT and all its se

Pak-Lok Poon, Santoso Wibowo, Sau-Fun Tang

Nowadays, the global booming of FinTech can be seen everywhere. FinTech has created innovative disruptions to traditional, long-established financial institutions (e.g., banks and insurance companies) in financial services markets. Despite of its popularity, there are many different definitions of FinTech. This problem occurs because many existing studies on

Dongyi Wei

We study the asymptotic behavior of small data solutions to the screened Vlasov Poisson(i.e. Vlasov-Yukawa) equation on ${\mathbb R}\times{\mathbb R}$ near vacuum. We show that for initial data small in Gevrey-2 regularity, the derivative of the density of order $n$ decays like $(t+1)^{-n-1}$.

Yanfeng Ji, Shutong Wang, Ruyi Xu, Jingying Chen

Children with Autism Spectrum Disorder (ASD) often exhibit atypical facial expressions. However, the specific objective facial features that underlie this subjective perception remain unclear. In this paper, we introduce a novel dataset, Hugging Rain Man (HRM), which includes facial action units (AUs) manually annotated by FACS experts for both children with

R. McVinish

The Tallis-Leyton model is a simple model of parasite acquisition where there is no interaction between the host and the acquired parasites. We examine the effect of model parameters on the distribution of the host's parasite burden in the sense of the Lorenz order. This fits with an alternate view of parasite aggregation that has become widely used in empir

San-Dong Guo

Hidden spin polarization (HSP) with zero net spin polarization in total but non-zero local spin polarization has been proposed in certain nonmagnetic centrosymmetric compounds, where the individual sectors forming the inversion partners are all inversion asymmetry. Here, we extend this idea to antiferromagnetic materials with $PT$ symmetry (the joint symmetr

Aniruddha Bala, Rohan Jaiswal, Siddharth Roheda, Rohit Chowdhury

Training of large-scale text-to-image and image-to-image models requires a huge amount of annotated data. While text-to-image datasets are abundant, data available for instruction-based image-to-image tasks like object addition and removal is limited. This is because of the several challenges associated with the data generation process, such as, significant

Ke Zhao, Huayang Huang, Miao Li, Yu Wu

Language-conditioned robotic learning has significantly enhanced robot adaptability by enabling a single model to execute diverse tasks in response to verbal commands. Despite these advancements, security vulnerabilities within this domain remain largely unexplored. This paper addresses this gap by proposing a novel adversarial prompt attack tailored to lang

Arjun Sridhar, Yiran Chen

Neural Architecture Search (NAS) continues to serve a key roll in the design and development of neural networks for task specific deployment. Modern NAS techniques struggle to deal with ever increasing search space complexity and compute cost constraints. Existing approaches can be categorized into two buckets: fine-grained computational expensive NAS and co

Huihai He, Hengying Zhang, Qinyi Cheng, Lingling Ma

The knee-like structure around 4 PeV is the most striking feature in the cosmic ray energy spectrum, whose origin remains enigmatic. We propose a novel concept of the total logarithmic mass energy spectrum to characterize the knee, taking into account LHAASO measurements of the all-particle energy spectrum and the mean logarithmic mass. The predominant role

Revant Nayar, Raphael Douady

Traditional Markowitz portfolio optimization constrains daily portfolio variance to a target value, optimising returns, Sharpe or variance within this constraint. However, this approach overlooks the relationship between variance at different time scales, typically described by $\sigma(\Delta t) \propto (\Delta t)^{H}$ where $H$ is the Hurst exponent, most o

Hang Zhou, Yehui Tang, Haochen Qin, Yujie Yang

The efficacy of large language models (LLMs) on downstream tasks usually hinges on instruction tuning, which relies critically on the quality of training data. Unfortunately, collecting high-quality and diverse data is both expensive and time-consuming. To mitigate this issue, we propose a novel Star-Agents framework, which automates the enhancement of data

Daniel R. Johnston

We demonstrate the impact of a generic zero-free region and zero-density estimate on the error term in the prime number theorem. Consequently, we are able to improve upon previous work of Pintz and provide an essentially optimal error term for some choices of the zero-free region. As an example, we show that if there are no zeros $\rho=\beta+it$ of $\zeta(s)

ChangSheng Shi

We consider the Compton scattering in the optically thick uniform spherical corona around a neutron star in an X-ray binary. In the scattering, the low energy seed photons (0.1 - 2.5 keV) are scattered in low energy electrons (2.5 - 10 keV) in the corona in two conditions, i.e. initial seed photons are scattered in a whole corona and scattered in every layer

Fengxin Li, Yi Li, Yue Liu, Chao Zhou

Display advertising provides significant value to advertisers, publishers, and users. Traditional display advertising systems utilize a multi-stage architecture consisting of retrieval, coarse ranking, and final ranking. However, conventional retrieval methods rely on ID-based learning to rank mechanisms and fail to adequately utilize the content information

Bin Qian, Beibei Zhang

In this paper, we obtain the reverse Bakry-\'Emery type estimates for a class of hypoelliptic diffusion operator by coupling method. The (right and reverse) Poincar\'e inequalities and the (right and reverse) logarithmic Sobolev inequalities are presented as consequences of such estimates. Wang-Harnack inequality, Hamilton's gradient estimate and Liouville p

Bao Nguyen

The thesis proposes a generalized charging framework for multiple mobile chargers to maximize the network lifetime and ensure target coverage and connectivity in large scale WRSNs. Moreover, a multi-point charging model is leveraged to enhance charging efficiency, where the MC can charge multiple sensors simultaneously at each charging location. The thesis p

Zewei Xin, Qinya Li, Chaoyue Niu, Fan Wu

Large text-to-image models demonstrate impressive generation capabilities; however, their substantial size necessitates expensive cloud servers for deployment. Conversely, light-weight models can be deployed on edge devices at lower cost but often with inferior generation quality for complex user prompts. To strike a balance between performance and cost, we

Stan Loosmore, Alexander Titus

Modern day Language Models see extensive use in text classification, yet this comes at significant computational cost. Compute-effective classification models are needed for low-resource environments, most notably on edge devices. We introduce Adaptable Embeddings Networks (AEN), a novel dual-encoder architecture using Kernel Density Estimation (KDE). This a

Honghao Wang, Qingqing Wu, Ying Gao, Wen Chen

In this paper, we model the minimum achievable throughput within a transmission block of restricted duration and aim to maximize it in movable antenna (MA)-enabled multiuser downlink communications. Particularly, we account for the antenna moving delay caused by mechanical movement, which has not been fully considered in previous studies, and reveal the trad

Hassan Jameel Asghar, Robin Carpentier, Benjamin Zi Hao Zhao, Dali Kaafar

A widely used method to ensure privacy of unstructured text data is the multidimensional Laplace mechanism for $d_X$-privacy, which is a relaxation of differential privacy for metric spaces. We identify an intriguing peculiarity of this mechanism. When applied on a word-by-word basis, the mechanism either outputs the original word, or completely dissimilar w

Greg Schivley, Aurora Barone, Michael Blackhurst, Patricia Hidalgo-Gonzalez

This study performs a detailed intercomparison of four open-source electricity capacity expansion models - Temoa, Switch, GenX, and USENSYS - to evaluate 1) how closely the results of these models align when inputs and configurations are harmonized, and 2) the degree to which varying model configurations affect outputs. We harmonize the inputs to each model

Hiromasa Takaura, Robert Harlander, Fabian Lange

We propose a new method to determine the quark mass by using bilinear operators of the flowed quark field defined within the gradient-flow formalism. This method enables the quark mass determination through a comparison of perturbative calculations with lattice data. The gauge-invariant nature of the observable should allow clear control over perturbative er

Hui Bao, Hongjun Guo

This paper is concerned with the asymptotic spreading behavior of solutions of the Lotka-Volterra system with strong competition in $\mathbb{R}^{N}$. Two types of initial conditions are proposed: (C1) two species initially occupy bounded domains; (C2) two species initially occupy the whole space separately. The spreading dynamics for (C1) (C2) is strongly de

Loredana Fattorini, Nestor Maslej, Raymond Perrault, Vanessa Parli

This paper presents the latest version of the Global AI Vibrancy Tool (GVT), an interactive suite of visualizations designed to facilitate the comparison of AI vibrancy across 36 countries, using 42 indicators organized into 8 pillars. The tool offers customizable features that allow users to conduct in-depth country-level comparisons and longitudinal analys

Andrea Davini, Panrui Ni, Jun Yan, Maxime Zavidovique

We study the asymptotic behavior of solutions of an equation of the form \begin{equation}\label{abs}\tag{*} G\big(x, D_x u,\lambda u(x)\big) = c_0\qquad\hbox{in $M$} \end{equation} on a closed Riemannian manifold $M$, where $G\in C(T^*M\times\mathbb{R})$ is convex and superlinear in the gradient variable, is globally Lipschitz but not monotone in the last ar

Alexander Spangher, Michael Lu, Sriya Jeslyn Kalyan, Hyundong Justin Cho

Large Language Models (LLMs) have demonstrated impressive capabilities in generating coherent text but often struggle with grounding language and strategic dialogue. To address this gap, we focus on journalistic interviews, a domain rich in grounding communication and abundant in data. We curate a dataset of 40,000 two-person informational interviews from NP

Junae Kim, Amardeep Kaur

In autonomous driving, the combination of AI and vehicular technology offers great potential. However, this amalgamation comes with vulnerabilities to adversarial attacks. This survey focuses on the intersection of Adversarial Machine Learning (AML) and autonomous systems, with a specific focus on LiDAR-based systems. We comprehensively explore the threat la

Shaiful Chowdhury, Hisham Kidwai, Muhammad Asaduzzaman

Self-Admitted Technical Debt (SATD) refers to the phenomenon where developers explicitly acknowledge technical debt through comments in the source code. While considerable research has focused on detecting and addressing SATD, its true impact on software maintenance remains underexplored. The few studies that have examined this critical aspect have not provi

Chao-Lin Kuo, Chelsea L. Bartram, Aaron S. Chou, Taj A. Dyson

We provide a comprehensive comparison of linear amplifiers and microwave photon-counters in axion dark matter experiments. The study is done assuming a range of realistic operating conditions and detector parameters, over the frequency range between 1--30 GHz. As expected, photon counters are found to be advantageous under low background, at high frequencies

Jianhao Yan, Pingchuan Yan, Yulong Chen, Jing Li

This study presents a comprehensive evaluation of GPT-4's translation capabilities compared to human translators of varying expertise levels. Through systematic human evaluation using the MQM schema, we assess translations across three language pairs (Chinese$\longleftrightarrow$English, Russian$\longleftrightarrow$English, and Chinese$\longleftrightarrow$Hi

Hussni Mohd Zakir, Eric Tatt Wei Ho

The Segment-Anything Model (SAM) is a vision foundation model for segmentation with a prompt-driven framework. SAM generates class-agnostic masks based on user-specified instance-referring prompts. However, adapting SAM for automated segmentation -- where manual input is absent -- of specific object classes often requires additional model training. We presen

Jiancheng An, Mérouane Debbah, Tie Jun Cui, Zhi Ning Chen

Intelligent metasurfaces have demonstrated great promise in revolutionizing wireless communications. One notable example is the two-dimensional (2D) programmable metasurface, which is also known as reconfigurable intelligent surfaces (RIS) to manipulate the wireless propagation environment to enhance network coverage. More recently, three-dimensional (3D) st

Amar Abane, Anis Bekri, Abdella Battou, Saddek Bensalem

Efficiently processing and interpreting network data is critical for the operation of increasingly complex networks. Recent advances in Large Language Models (LLM) and Retrieval-Augmented Generation (RAG) techniques have improved data processing in network management. However, existing RAG methods like VectorRAG and GraphRAG struggle with the complexity and

Xi-Yuan Yin, Philipp Krah, Jean-Christophe Nave, Kai Schneider

This work introduces a generalized characteristic mapping method designed to handle non-linear advection with source terms. The semi-Lagrangian approach advances the flow map, incorporating the source term via the Duhamel integral. We derive a recursive formula for the time decomposition of the map and the source term integral, enhancing computational effici

Vini Netto, Caio Cacholas, Dries Daems, Fabiano Ribeiro

Cities emerged independently across different world regions and historical periods, raising fundamental questions: How did the first urban settlements develop? What social and spatial conditions enabled their emergence? Are these processes universal or context-dependent? Moreover, what distinguishes cities from other human settlements? This paper investigate

Jin Tian, Haiqi Zhu, Changjia Lu, Chifu Yang

Objective: Overhead tasks are a primary inducement to work-related musculoskeletal disorders. Aiming to reduce shoulder physical loads, passive shoulder exoskeletons are increasingly prevalent in the industry due to their lightweight, affordability, and effectiveness. However, they can only accommodate a specific task and cannot effectively balance between c

Ben Welsh, Naitian Zhou, Arda Kaz, Michael Vu

Information prioritization plays an important role in how humans perceive and understand the world. Homepage layouts serve as a tangible proxy for this prioritization. In this work, we present NewsHomepages, a large dataset of over 3,000 new website homepages (including local, national and topic-specific outlets) captured twice daily over a three-year period

Yongqiang Li, Feng Shu, Maolin Li, Ke Yang

Reconfigurable intelligent surface (RIS), as an efficient tool to improve receive signal-to-noise ratio, extend coverage and create more spatial diversity, is viewed as a most promising technique for the future wireless networks like 6G. As you know, RIS is very suitable for a special wireless scenario with wireless link between BS and users being completely

Mubashir ul Islam, Humza Sami, Pierre-Emmanuel Gaillardon, Valerio Tenace

Large Language Models (LLMs) have become increasingly popular for generating RTL code. However, producing error-free RTL code in a zero-shot setting remains highly challenging for even state-of-the-art LLMs, often leading to issues that require manual, iterative refinement. This additional debugging process can dramatically increase the verification workload

Boming Xia, Qinghua Lu, Liming Zhu, Zhenchang Xing

Large Language Models (LLMs) have enabled the emergence of LLM agents, systems capable of pursuing under-specified goals and adapting after deployment. Evaluating such agents is challenging because their behavior is open ended, probabilistic, and shaped by system-level interactions over time. Traditional evaluation methods, built around fixed benchmarks and

Tristram Bogart, Santiago Morales

De Loera, O'Neill and Wilburne introduced a general model for random numerical semigroups in which each positive integer is chosen independently with some probability p to be a generator, and proved upper and lower bounds on the expected Frobenius number and expected embedding dimensions. We use a range of probabilistic methods to improve the upper bounds to

Ruiyang Qin, Dancheng Liu, Gelei Xu, Zheyu Yan

The combination of Large Language Models (LLM) and Automatic Speech Recognition (ASR), when deployed on edge devices (called edge ASR-LLM), can serve as a powerful personalized assistant to enable audio-based interaction for users. Compared to text-based interaction, edge ASR-LLM allows accessible and natural audio interactions. Unfortunately, existing ASR-L

Andrei Zlotchevski, Linan Chen

The Schr\"odinger bridge problem (SBP) seeks to find the measure $\hat{\mathbf{P}}$ on a certain path space which interpolates between state-space distributions $\rho_0$ at time $0$ and $\rho_T$ at time $T$ while minimizing the KL divergence (relative entropy) to a reference path measure $\mathbf{R}$. In this work, we tackle the SBP in the case when $\mathbf

Anav Sood

Selective inference is a subfield of statistics that enables valid inference after selection of a data-dependent question. In this paper, we introduce selectively dominant p-values, a class of p-values that allow practitioners to easily perform inference after arbitrary selection procedures. Unlike a traditional p-value, whose distribution must stochasticall

Yuval Boneh, Ethan Jones

This paper delves into the spectrum of credit risks associated with decentralized stablecoin issuance, ranging from overcollateralized lending to business-to-business credit. It examines the mechanisms, risks, and mitigation strategies at each layer, highlighting the potential for scaling decentralized stablecoins while ensuring systemic health.

Gaspar Gonzalez, Andrés M. Kowalski

We study the behavior of a nonlinear semiclassical system using Shannon entropy and two approaches to statistical complexity. These systems involve the interaction between classical variables (representing the environment) and quantum ones. Both conservative and dissipative regimes are explored. To calculate the information metrics, probability distributions

Luke Guerdan, Hanna Wallach, Solon Barocas, Alexandra Chouldechova

Large language model (LLM) evaluations often assume there is a single correct response -- a gold label -- for each item in the evaluation corpus. However, some tasks can be ambiguous -- i.e., they provide insufficient information to identify a unique interpretation -- or vague -- i.e., they do not clearly indicate where to draw the line when making a determi

Juliane T. Moraes, Silvio C. Ferreira

We analyze critical time series of the order parameter generated with active to inactive phase transitions of spreading dynamics running on the top of heterogeneous networks. Different activation mechanisms that govern the dynamics near the critical point were investigated. The time series were analyzed using the visibility graph (VG) method where a disassor

Christopher Tyler Cox, Jakob Haynes, Christopher Duffey, Christopher Bennett

Understanding of the formation and evolution of the Solar System requires understanding key and common materials found on and in planetary bodies. Mineral mixing and its implications on planetary body formation is a topic of high interest to the planetary science community. Previous work establishes a case for the use of Optical PhotoThermal InfraRed (O-PTIR

Hamidreza Dastmalchi, Aijun An, Ali Cheraghian, Shafin Rahman

Test-time adaptation (TTA) of 3D point clouds is crucial for mitigating discrepancies between training and testing samples in real-world scenarios, particularly when handling corrupted point clouds. LiDAR data, for instance, can be affected by sensor failures or environmental factors, causing domain gaps. Adapting models to these distribution shifts online i

Gustavo Angulo, Diego Moran

The traveling salesman problem is a widely studied classical combinatorial problem for which there are several integer linear formulations. In this work, we consider the Miller-Tucker-Zemlin (MTZ), Desrochers-Laporte (DL) and Single Commodity Flow (SCF) formulations. We argue that the choice of some parameters of these formulations is arbitrary and, therefor

Sanjay Das, Swastik Bhattacharya, Souvik Kundu, Shamik Kundu

Large Language Models (LLMs) have revolutionized natural language processing (NLP), excelling in tasks like text generation and summarization. However, their increasing adoption in mission-critical applications raises concerns about hardware-based threats, particularly bit-flip attacks (BFAs). BFAs, enabled by fault injection methods such as Rowhammer, targe

Daniel Evans, Ahmad K. Omar

The crystallization of hard spheres at equilibrium is perhaps the most familiar example of an entropically-driven phase transition. In recent years, it has become clear that activity can dramatically alter this order-disorder transition in unexpected ways. The theoretical description of active crystallization has remained elusive as the traditional thermodyn

Priya J. Nadkarni, Serge Adonsou, Guillaume Dauphinais, David W. Kribs

We introduce a framework for entanglement-assisted quantum error correcting codes that unifies the three original frameworks for such codes called EAQEC, EAOQEC, and EACQ under a single umbrella. The unification is arrived at by viewing entanglement-assisted codes from the operator algebra quantum error correction perspective, and it is built upon a recently

Vladimir Dotsenko, Paul Laubie

We study a coloured operad involving rooted trees and directed cycles of rooted trees that generalizes the operad of rooted trees of Chapoton and Livernet. We describe all the relations between the generators of a certain suboperad of that operad, and compute the Chevalley-Eilenberg homology of two naturally arising differential graded Lie algebras. This all

A. A. Mazanik, A. N. Rubtsov

Achieving a quantum computational advantage regime, and thus providing evidence against the extended Church-Turing thesis, remains one of the key challenges of modern science. Boson sampling seems to be a very promising platform in this regard, but to be confident of attaining the advantage regime, one must provide evidence of operating with a correct boson

Gleb Tselikov, Anton Minnekhanov, Georgy Ermolaev, Gleb Tikhonowski

Van der Waals (vdW) materials are becoming increasingly popular in scientific and industrial applications because of their unique mixture of record electronic, optical, and mechanical properties. However, nanostructuring of vdW materials is still in its infancy and strongly depends on the specific vdW crystal. As a result, the universal self-assembled techno

Anwesh Ray

Let $n$ be a cubefree natural number and $p\geq 5$ be a prime number. Assume that $n$ is not expressible as a sum of the form $x^3+y^3$, where $x,y\in \mathbb{Q}$. In this note, we study the solutions (or lack thereof) to the equation $n=x^3+y^3$, where $x$ and $y$ belong to the cyclotomic $\mathbb{Z}_p$-extension of $\mathbb{Q}$. As an application, consider

Alireza Kianimoqadam, Justin L. Lapp

A novel method, the Gaussian Integral Method (GIM), is presented for calculating void fractions in Computational Fluid Dynamics-Discrete Element Method (CFD-DEM) simulations. GIM is versatile and applicable to various grid types, including structured and unstructured polyhedral meshes, without requiring special boundary treatments. An optimization technique

Mar Ferri-Cortés, Jose A. Almanza-Marrero, Rosa López, Roberta Zambrini

The thermodynamic behavior of Markovian open quantum systems can be described at the level of fluctuations by using continuous monitoring approaches. However, practical applications require assessing imperfect detection schemes, where the definition of main thermodynamic quantities becomes subtle and universal fluctuation relations are unknown. Here, we fill

Xiachong Lin, Arian Prabowo, Imran Razzak, Hao Xue

Incorporating AI technologies into digital infrastructure offers transformative potential for energy management, particularly in enhancing energy efficiency and supporting net-zero objectives. However, the complexity of IoT-generated datasets often poses a significant challenge, hindering the translation of research insights into practical, real-world applic

Alexander Rom

This paper investigates the impact of banking competition on interest rates for household consumption loans in the Euro Area from 2014 to 2020. Utilizing a panel data regression approach, we analyze how various factors, including local banking competition, influence the interest rates set by banks across 13 Euro-area countries. Our key independent variable,

Hannah Attar

This paper investigates the determinants of home prices in Dana Point, California to analyze various factors influencing the real estate market. The results are based on a cross-sectional dataset that incorporates year and month-time dummies to account for temporal trends, as well as spatial variables that capture effects within and between clusters. To addr

Yadir Garnica, América Morales, Carlos A. Vaquera-Araujo

We propose a $U(1)_{B-L}$ gauge extension to the SM, in which the dark sector is stabilized through a matter parity symmetry preserved after spontaneous symmetry breaking. The fermion spectrum includes three neutral right-handed fields with $B-L$ charges $(-4,-4, 5)$, that make the model free of gauge anomalies. Two of these neutral fermion fields serve as m