August 2024 arXiv papers

Md Sadman Sakib Rahman, Tianyi Gan, Mona Jarrahi, Aydogan Ozcan

Snell's law dictates the phenomenon of light refraction at the interface between two media. Here, we demonstrate arbitrary programming of light refraction through an engineered material where the direction of the output wave can be set independently for different directions of the input wave, covering arbitrarily selected permutations of light refraction

P. Curvo, D. R. Ferreira, R. Jorge

The design of fusion devices is typically based on computationally expensive simulations. This can be alleviated using high aspect ratio models that employ a reduced number of free parameters, especially in the case of stellarator optimization where non-axisymmetric magnetic fields with a large parameter space are optimized to satisfy certain performance cri

Emadeldeen Hamdan, Hongyi Pan, Ahmet Enis Cetin

Structured state space models' (SSMs) development in recent studies, such as Mamba and Mamba2, outperformed and solved the computational inefficiency of transformers and large language models at small to medium scale. In this work, we introduce the concept of controllability and observability to the original Mamba SSM's architecture in our Sparse-Mam

Aref Farhadipour, Masoumeh Chapariniya, Teodora Vukovic, Volker Dellwo

Multimodal learning involves integrating information from various modalities to enhance learning and comprehension. We compare three modality fusion strategies in person identification and verification by processing two modalities: voice and face. In this paper, a one-dimensional convolutional neural network is employed for x-vector extraction from voice, wh

Wenxuan Wang, Juluan Shi, Zixuan Ling, Yuk-Kit Chan

Equipped with the capability to call functions, modern large language models (LLMs) can leverage external tools for addressing a range of tasks unattainable through language skills alone. However, the effective execution of these tools relies heavily not just on the advanced capabilities of LLMs but also on precise user instructions, which often cannot be en

Kailun Chen

We consider the second class particle in half-line open TASEP under two different initial conditions with shock discontinuities. The exact formulas for the distribution of the second class particle can be derived by using the color-position symmetry theorem of colored half-space TASEP. We study the asymptotic distribution of second class particles under the

Gang Li, Qihang Lin, Ayush Ghosh, Tianbao Yang

The post-processing approaches are becoming prominent techniques to enhance machine learning models' fairness because of their intuitiveness, low computational cost, and excellent scalability. However, most existing post-processing methods are designed for task-specific fairness measures and are limited to single-output models. In this paper, we introduc

Mehdi Bouzid, Cesar Valencia Gallardo, Magdalena Kopec, Lara Koehler

Branched actin networks exert pushing forces in eukaryotic cells, and adapt their stiffness to their environment. The physical basis for their mechanics and adaptability is however not understood. Indeed, here we show that their high density and low connectivity place them outside the scope of standard elastic network models for actin. We combine high-precis

Noah Apthorpe, Boen Beavers, Yan Shvartzshnaider, Brett Frischmann

Technical standards are a longstanding method of communicating best practice recommendations based on expert consensus. Cybersecurity standards are particularly important for informing policies that protect critical systems and sensitive data. Measuring standards compliance is therefore essential to identify vulnerabilities arising from outdated policies and

Sicheng Wang, Che Liu, Rossella Arcucci

Recent advancements in medical vision-language pre-training (MedVLP) have significantly enhanced zero-shot medical vision tasks such as image classification by leveraging large-scale medical image-text pair pre-training. However, the performance of these tasks can be heavily influenced by the variability in textual prompts describing the categories, necessit

Jong-Seo Kim, Hendrik Mueller, Aleksei S. Nikonov, Ru-Sen Lu

The galaxy M87 is one of the prime targets for high resolution radio imaging to investigate the supermassive black hole, accretion flow, and relativistic jet. However, it remains challenging to observe them jointly. In 2018, GMVA+ALMA observations at 86 GHz enabled the simultaneous reconstruction of a ring structure and the extended jet emission. In order to

Lars Lindemann, Yiqi Zhao, Xinyi Yu, George J. Pappas

We present recent advances in formal verification and control for autonomous systems with practical safety guarantees enabled by conformal prediction (CP), a statistical tool for uncertainty quantification. This survey is particularly motivated by learning-enabled autonomous systems (LEASs), where the complexity of learning-enabled components (LECs) poses a

Michael K. -H. Kiessling, Boris L. Altshuler, Emil A. Yuzbashyan

The dispersionless limit of the standard Eliashberg theory of superconductivity is studied. The effective electron-electron interactions are mediated by Einstein phonons of frequency $Ω>0$, equipped with electron-phonon coupling strength $λ$. This allows for a detailed evaluation of the general results on $T_c$ for phonons with non-trivial dispersion relatio

Jaehyun Kim, Hyungbin Park

This study proposes a BSDE approach to the long-term decomposition of pricing kernels under the G-expectation framework. We establish the existence, uniqueness, and regularity of solutions to three types of quadratic G-BSDEs: finite-horizon G-BSDEs, infinite-horizon G-BSDEs, and ergodic G-BSDEs. Moreover, we explore the Feynman--Kac formula associated with t

D. V. V. Narayana, D. Mattiolo, Kalyani Gohokar, Nishad Kothari

Recently, Goedgebeur, Mazzuoccolo, Renders, Wolf and the second author [Cubic graphs with edges in exactly one perfect matching, J. Graph Theory 112 (2026), 276-289] proved that every $3$-connected $3$-regular graph has at most six solitary edges; an edge is solitary if it participates in precisely one perfect matching. They also gave complete characterizati

Michael K. -H. Kiessling, Boris L. Altshuler, Emil A. Yuzbashyan

Using the recent reformulation for the Eliashberg theory of superconductivity in terms of a classical interacting Bloch spin chain model, rigorous upper and lower bounds on the critical temperature $T_c$ are obtained for the $γ$ model -- a version of Eliashberg theory in which the effective electron-electron interaction is proportional to $(g/|ω_n-ω_m|)^γ$,

Michael K. -H. Kiessling, Boris L. Altshuler, Emil A. Yuzbashyan

The standard Eliashberg theory of superconductivity is studied, in which the effective electron-electron interactions are mediated by generally dispersive phonons, with Eliashberg spectral function $α^2 F(ω)\geq 0$ that is $\proptoω^2$ for small $ω>0$ and vanishes for large $ω$. The Eliashberg function also defines the electron-phonon coupling strength $λ:=

Tumpa Biswas, Dibakar Dhar, Azharuddin Ahmed, Prabir Kumar Haldar

The fractal and phase transitional properties of each type of pions (i.e. $π^{\pm,0}$) through one-dimensional $η-$space, at an energy of $\sqrt{s}=13~$TeV, have been studied with the help of the Scaled Factorial Moment (SFM) framework. To generate simulated data sets for $pp$ collisions under the minimum bias (MB) condition at $\sqrt{s}=13~$TeV, we have emp

Alper Canberk, Maksym Bondarenko, Ege Ozguroglu, Ruoshi Liu

Creative processes such as painting often involve creating different components of an image one by one. Can we build a computational model to perform this task? Prior works often fail by making global changes to the image, inserting objects in unrealistic spatial locations, and generating inaccurate lighting details. We observe that while state-of-the-art mo

Mohameden Ahmedou, Thomas Bartsch, Zhengni Hu

We study the following Neumann boundary problem related to the stationary solutions of the Keller-Segel system, a basic model of chemotaxis phenomena: \[ \left\{\begin{array}{ll} -Δ_g u +βu =λ\left(\frac{Ve^u}{\int_Σ Ve^u d v_g}-1\right), &\text { in } \mathringΣ\\ \partial_{ ν_g} u=0, &\text { on } \partial Σ\end{array} \right.,\] on a compact Riemann surfa

William Heyden, Habib Ullah, M. Salman Siddiqui, Fadi Al Machot

In Generalized Zero-Shot Learning (GZSL), we aim to recognize both seen and unseen categories using a model trained only on seen categories. In computer vision, this translates into a classification problem, where knowledge from seen categories is transferred to unseen categories by exploiting the relationships between visual features and available semantic

Zhiyuan Hu, Yuliang Liu, Jinman Zhao, Suyuchen Wang

Large language models (LLMs) face significant challenges in handling long-context tasks because of their limited effective context window size during pretraining, which restricts their ability to generalize over extended sequences. Meanwhile, extending the context window in LLMs through post-pretraining is highly resource-intensive. To address this, we intro

Moreshwar Tayde, P. K. Sahoo

This paper discusses the possibility of traversable wormholes in the galactic region supported by dark matter (DM) models and global monopole charge in the context of $f(Q)$ gravity. To understand the features of the wormholes, we comprehensively studied wormhole solutions with various redshift functions under different $f(Q)$ models. We obtained wormhole sh

Tao Fu, Yue Wang

A significant proportion of exoplanets have been detected with highly tilted or even polar orbits relative to their host stars' equatorial planes. These unusual orbital configurations are often linked to post-disk secular interactions among multiple bodies. However, many aspects remain elusive. In this study, we investigate the role of disk-induced spin-

Evan Berkowitz, Seth Buesing, Shi Chen, Aleksey Cherman

The BKT transition in low-dimensional systems with a $U(1)$ global symmetry separates a gapless conformal phase from a trivially gapped, disordered phase, and is driven by vortex proliferation. Recent developments in modified Villain discretizations provide a class of lattice models which have a $\mathbb{Z}_W$ global symmetry that counts vortices mod W, mixe

Onel L. A. López, Zhu Han, Ashutosh Sabharwal

Accurate orientation estimation of objects can aid in scene understanding in many applications. In this paper, we consider use cases where passive tags could be deployed to assist radar systems in estimating object orientation. Towards that end, we propose the concept of passive iridescent reflective tags that selectively reflect different wavelengths in dif

Yike Zhang, Jack Noble

Cochlear Implant (CI) procedures involve performing an invasive mastoidectomy to insert an electrode array into the cochlea. In this paper, we introduce a novel pipeline that is capable of generating synthetic multi-view videos from a single CI microscope image. In our approach, we use a patient's pre-operative CT scan to predict the post-mastoidectomy s

Maeesha Binte Hashem, Benjamin Parpillon, Divake Kumar, Dinithi Jayasuria

In this work, we propose "TimeFloats," an efficient train-in-memory architecture that performs 8-bit floating-point scalar product operations in the time domain. While building on the compute-in-memory paradigm's integrated storage and inferential computations, TimeFloats additionally enables floating-point computations, thus facilitating DNN tra

Haowen Xu, Jinghui Yuan, Anye Zhou, Guanhao Xu

Leveraging recent advances in generative AI, multi-agent systems are increasingly being developed to enhance the functionality and efficiency of smart city applications. This paper explores the transformative potential of large language models (LLMs) and emerging Retrieval-Augmented Generation (RAG) technologies in Intelligent Transportation Systems (ITS), p

David Futer, Rose Kaplan-Kelly

The family of right-angled tiling links consists of links built from regular 4-valent tilings of constant-curvature surfaces that contain one or two types of tiles. The complements of these links admit complete hyperbolic structures and contain two totally geodesic checkerboard surfaces that meet at right angles. In this paper, we give a complete characteriz

Yair Stolero, Itzik Klein

Low-cost gyroscope calibration is essential for ensuring the accuracy and reliability of gyroscope measurements. Stationary calibration estimates the deterministic parts of measurement errors. To this end, a common practice is to average the gyroscope readings during a predefined period and estimate the gyroscope bias. Calibration duration plays a crucial ro

Bin Hu, Run Luo, Zelin Liu, Cheng Wang

Temporal motion modeling has always been a key component in multiple object tracking (MOT) which can ensure smooth trajectory movement and provide accurate positional information to enhance association precision. However, current motion models struggle to be both efficient and effective across different application scenarios. To this end, we propose TrackSSM

Francescantonio Oliva, Francesco Petitta

In this survey we provide an overview of nonlinear elliptic homogeneous boundary value problems featuring singular zero-order terms with respect to the unknown variable whose prototype equation is $$ -Δu = {u^{-γ}} \ \text{in}\ Ω$$ where $Ω$ is a bounded subset of $\mathbb{R}^N$ ($N\geq 2$), and $γ>0$. We start by outlining the basic concepts and the mathema

Xinyu Wang, Haotian Jiang, Haolin Huang, Yu Fang

Speech recognition is the technology that enables machines to interpret and process human speech, converting spoken language into text or commands. This technology is essential for applications such as virtual assistants, transcription services, and communication tools. The Audio-Visual Speech Recognition (AVSR) model enhances traditional speech recognition,

Mohit Apte, Yashodhara Haribhakta

In the rapidly evolving field of financial forecasting, the application of neural networks presents a compelling advancement over traditional statistical models. This research paper explores the effectiveness of two specific neural forecasting models, N-HiTS and N-BEATS, in predicting financial market trends. Through a systematic comparison with conventional

Reggie C. Pantig

In this paper, an analytic generalization of the weak field deflection angle (WDA) is derived by utilizing the current non-asymptotically flat generalization of the Gauss-Bonnet theorem. The derived formula is valid for any Schwarzschild-like spacetime, which deviates from the classical Schwarzschild case through some constant parameters. This work provided

Abbas Ali, Mohsin Ilahi, P. P. Abdul Salih, Shafeeq Rahman Thottoli

We clarify the supersymmetry structure of ADHM instanton linear sigma models, $N=4$ superconformal algebras and superconformal field theories dual to superstrings moving in $AdS_3$ backgrounds in view of some of our recent findings in various investigations. First of all we collect information about the (0, 4) supersymmetries of Witten's original, Ali-Il

Junping Chen, Rong-Feng Shen, Wen-Jun Tan, Chen-Wei Wang

The progenitors of gamma-ray bursts (GRBs) have long been an unresolved issue. GRB 230307A stands out as an exceptionally bright event, belonging to the long-duration GRBs but also exhibiting a late emission component reminiscent of a kilonova. Together with the similar events GRBs 060614 and 211211A, they make up a new sub-group of GRBs with intriguing prog

Po-Feng Wu

The confirmation of massive quiescent galaxies emerging within the first billion years of the universe poses intriguing questions about the mechanisms of galaxy formation. There must be highly efficient processes at work to shut down star formation in galaxies at cosmic dawn. I present the detection of neutral outflowing gas in a massive recently quenched ga

Vincent Brault, Frédérique Letué, Marie-José Martinez

When entering French university, the students' foreign language level is assessed through a placement test. In this work, we model the placement test results using binary latent block models which allow to simultaneously form homogeneous groups of students and of items. However, a major difficulty in latent block models is to select correctly the number

Xavier Carvajal, Mahendra Panthee

Considered in this work is the initial value problem (IVP) associated to a higher order water wave model \begin{equation*} \begin{cases} η_t+η_x-γ_1 η_{xxt}+γ_2η_{xxx}+δ_1 η_{xxxxt}+δ_2η_{xxxxx}+\frac{3}{2}ηη_x+γ(η^2)_{xxx}-\frac{7}{48}(η_x^2)_x-\frac{1}{8}(η^3)_x=0,\\ η(x,0) = η_0(x). \end{cases} \end{equation*} The main interest is in addressing the well-p

Zhida Liang, Xiang Xu, Fengxian Liu, Xi Zhang

Controlling planar fault shearing mechanisms is key for improving the high-temperature creep performance of gamma prime-strengthened high-temperature superalloys. This work examines how the Ti concentration in L12-strengthened CoNi-based alloys affects planar fault formation during creep. Interrupted compressive creep tests were conducted at 1223 K under air

Shi-Yuan Wu, Jian-Hua Gao

We derive self-consistent constraint conditions for collision terms in quantum kinetic theory using the Wigner function formalism. We present specific solutions for these collision terms that align with the constraints. we develop quantum kinetic theory at relaxation-time approximation. With this framework, we discuss spin polarization and electric charge se

Shi-Zheng Yang, Jian-Hua Gao, Shi Pu

We have derived the Wigner equations at global equilibrium with constant vorticity but space-time dependent electromagnetic fields up to second order in semiclassical expansion. We obtain the new second-order contributions to the charge currents and energy-momentum tensor from the varying electromagnetic fields. We also compute the new corrections to the spi

Satori Tsuzuki

This study examines the effects of an external gravitational field on highly rarefied gases in the transitional-flow regime near the free-molecular-flow regime. In our theoretical study, we rederive the classical kinetic theory for an ideal gas in terms of the kinetics of the constituent particles to account for the effect of particle acceleration by an exte

Siya Chen, Chee Wei Tan, Xiangping Zhai, H. Vincent Poor

The next-generation radio access network (RAN), known as Open RAN, is poised to feature an AI-native interface for wireless cellular networks, including emerging satellite-terrestrial systems, making deep learning integral to its operation. In this paper, we address the nonconvex optimization challenge of joint subcarrier and power allocation in Open RAN, wi

Longyun Liao, Rong Zheng

2D-to-3D human pose lifting is an ill-posed problem due to depth ambiguity and occlusion. Existing methods relying on spatial and temporal consistency alone are insufficient to resolve these problems especially in the presence of significant occlusions or high dynamic actions. Semantic information, however, offers a complementary signal that can help disambi

Naiara V. de Paulo, Seongchan Kim, Pedro A. S. Salomão, Alexsandro Schneider

We investigate the dynamics of a two-degree-of-freedom mechanical system for energies slightly above a critical value. The critical set of the potential function is assumed to contain a finite number of saddle points. As the energy increases across the critical value, a disk-like component of the Hill region gets connected to other components precisely at th

Seyedeh Fahimeh Hosseini, Faezeh Shalbafzadeh, Behzad Amanpour-Gharaei

Radiological images, such as magnetic resonance imaging (MRI) and computed tomography (CT) images, typically consist of a body part and a dark background. For many analyses, it is necessary to separate the body part from the background. In this article, we present a Python code designed to separate body and background regions in 2D and 3D radiological images

Daiki Saito, Tomohiro Harada, Yasutaka Koga, Chul-Moon Yoo

We estimate the probability distribution for the spins of the primordial black holes (PBHs) that formed during an early matter-dominated era in the Universe. We employ the Zel'dovich approximation and focus on the linear-order effect of cosmological perturbations which causes the tidal torque. Assuming that the fluctuations obey Gaussian statistics, we a

Mathias Weiden, Justin Kalloor, John Kubiatowicz, Ed Younis

Resource-efficient and high-precision approximate synthesis of quantum circuits expressed in the Clifford+T gate set is vital for Fault-Tolerant quantum computing. Efficient optimal methods are known for single-qubit RZ unitaries, otherwise the problem is generally intractable. Search-based methods, like simulated annealing, empirically generate low resource

T. M. J. T. Baltussen, A. Katriniok, E. Lefeber, R. Tóth

The control of a single agent in complex and uncertain multi-agent environments requires careful consideration of the interactions between the agents. In this context, this paper proposes a dual model predictive control (MPC) method using Gaussian process (GP) models for multi-agent systems. While Gaussian process MPC (GP-MPC) has been shown to be effective

Tomos Parry

A deep conjecture of Montgomery and Soundararajan on the distribution of prime numbers in short intervals of length $h$ says that the third moment is bounded by $\ll h^{\frac {3}{2}-c}$ for some $c>0$. There is in the literature some conditional evidence towards this conjecture whilst in the first article to this series we gave the first instance of uncondit

Piero Olla

The behavior of lattice models in which time reversibility is enforced at the level of trajectories (microscopic reversibility) is studied analytically. Conditions for ergodicity breaking are explored, and a few examples of systems characterized by an additional conserved quantity besides energy are presented. All the systems are characterized by ergodicity

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $e^+e^-$ collision data collected by the BESIII detector at BEPCII corresponding to an integrated luminosity of 30 $\rm fb^{-1}$, we measure Born cross sections and effective form factors for the process $e^+e^-\toΞ^0\barΞ^0$ at forty-five center-of-mass energies between 3.51 and 4.95 GeV. The dressed cross section is fitted, assuming a power-law funct

Yu He, Boheng Li, Yao Wang, Mengda Yang

The vulnerability of machine learning models to Membership Inference Attacks (MIAs) has garnered considerable attention in recent years. These attacks determine whether a data sample belongs to the model's training set or not. Recent research has focused on reference-based attacks, which leverage difficulty calibration with independently trained referenc

Lu Chen, Baopi Liu, Ning Liu

In this study, we investigate the behaviors and dynamics of self-propelled particles with active reorientation (AR) in a double-well potential. We explore the competition between AR and external potentials, revealing that self-propelled particles exhibit flocking and clustering behaviors in an asymmetric potential trap. Through molecular dynamics simulations

Kazuki Kudomi, Kiyoshi Takeuchi

Based on the recent progress in the irregular Riemann-Hilbert correspondence, we study the monodromies at infinity of the holomorphic solutions of Fourier transforms of holonomic D-modules in some situations. Formulas for their eigenvalues are obtained by applying the theory of monodromy zeta functions to our previous results on the enhanced solution complex

Fabio Lischka

Any choice of a spherical fusion category defines an invariant of oriented closed 3-manifolds, which is computed by choosing a triangulation of the manifold and considering a state sum model that assigns a 6j symbol to every tetrahedron in this triangulation. This approach has been generalized to oriented closed 3-manifolds with defect data by Meusburger. In

Subhojit Pal, John F. Dobson, Mathias Boström

Filamentary objects such as nano-wires, nanotubes and DNA are of current interest in physics, nanoscience, chemistry, biology and medicine. They can interact via strong, exceptionally long-ranged many-object van der Waals (vdW, dispersion) forces, causing them to cluster into multi-object bundles. We analyse their vdW interactions perturbatively, predicting

Vahid Garousi, Nithin Joy, Zafar Jafarov, Alper Buğra Keleş

Context: The rise of Artificial Intelligence (AI) in software engineering has led to the development of AI-powered test automation tools, promising improved efficiency, reduced maintenance effort, and enhanced defect-detection. However, a systematic evaluation of these tools is needed to understand their capabilities, benefits, and limitations. Objective: Th

Shigeo Koshitani, İpek Tuvay

It is proven that if a finite group $G$ has a normal subgroup $H$ with $p'$-index (where $p$ is a prime) and $G/H$ is solvable, then for a $p$-subgroup $P$ of $H$, if the Scott $kH$-module with vertex $P$ is Brauer indecomposable, then so is the Scott $kG$-module with vertex $P$, where $k$ is a field of characteristic $p>0$. This has several applications

Jun Yan, Wenjie Jacky Mo, Xiang Ren, Robin Jia

Backdoor attacks, in which a model behaves maliciously when given an attacker-specified trigger, pose a major security risk for practitioners who depend on publicly released language models. As a countermeasure, backdoor detection methods aim to detect whether a released model contains a backdoor. While existing backdoor detection methods have high accuracy

Norbert Bodendorfer, Onur Oktay, Vaibhav Gautam, Masanori Hanada

We apply the variational Monte Carlo method based on neural network quantum states, using a neural autoregressive flow architecture as our ansatz, to determine the ground state wave function of the bosonic SU($N$) Yang-Mills-type two-matrix model at strong coupling. Previous literature hinted at the inaccuracy of such an approach at strong coupling. In this

Munish Monga, Sachin Kumar Giroh, Ankit Jha, Mainak Singha

Multi-Target Domain Adaptation (MTDA) entails learning domain-invariant information from a single source domain and applying it to multiple unlabeled target domains. Yet, existing MTDA methods predominantly focus on addressing domain shifts within visual features, often overlooking semantic features and struggling to handle unknown classes, resulting in what

Joshua Hang Sai Ip, Georgios Makrygiorgos, Ali Mesbah

Deep neural networks are increasingly used as an effective parameterization of control policies in various learning-based control paradigms. For continuous-time optimal control problems (OCPs), which are central to many decision-making tasks, control policy learning can be cast as a neural ordinary differential equation (NODE) problem wherein state and contr

Elisabete Barreiro, Saïd Benayadi, Carla Rizzo

We develop the bialgebra theory for two classes of non-associative algebras: nearly associative algebras and $LR$-algebras. In particular, building on recent studies that reveal connections between these algebraic structures, we establish that nearly associative bialgebras and $LR$-bialgebras are, in fact, equivalent concepts. We also provide a characterizat

Giacomo Tendas

Working within enriched category theory, we further develop the use of soundness, introduced by Adámek, Borceux, Lack, and Rosický for ordinary categories. In particular we investigate: (1) the theory of locally $Φ$-presentable $\mathcal V$-categories for a sound class $Φ$, (2) the problem of whether every $Φ$-accessible $\mathcal V$-category is $Ψ$-accessib

YuanZheng Wu, Jin Liu, Shunping Ji

Recently, 3D Gaussian Splatting (3DGS) has demonstrated excellent ability in small-scale 3D surface reconstruction. However, extending 3DGS to large-scale scenes remains a significant challenge. To address this gap, we propose a novel 3DGS-based method for large-scale surface reconstruction using aerial multi-view stereo (MVS) images, named Aerial Gaussian S

Yukiko Konishi, Satoshi Minabe

This is a sequel to our previous article arXiv:2307.07897. We describe a certain reduction process of Satake's good basic invariants. We show that if the largest degree $d_1$ of a finite complex reflection group $G$ is regular and if $δ$ is a divisor of $d_1$, a set of good basic invariants of $G$ induces that of the reflection subquotient $G_δ$. We also

H. P. Zhang, Z. Song

We study the dynamical behavior of the non-Hermitian Wannier-Stark ladder system, which is a non-Hermitian Su-Schrieffer-Heeger chain with a position-dependent real potential. In the presence of a linear external field, we employ the non-Hermitian Floquet method and find that the energy levels are sensitive to the field. The system exhibits two distinct dyna

Tathagata Banerjee, Diganta Mukherjee

This paper examines two different variants of the Ludo game, involving multiple dice and a fixed number of total turns. Within each variant, multiple game lengths (total no. of turns) are considered. To compare the two variants, a set of intuitive, rule-based strategies is designed, representing different broad methods of strategic play. Game play is simulat

Ridong Han, Chaohao Yang, Tao Peng, Prayag Tiwari

Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (NLP) related tasks. Therefore, various attempts have been made to apply LLMs to information extraction (IE), which is a fundamental NLP task that involves extracting informatio

Amir Noori, Babak Tavassoli, Alireza Fereidunian

Integrating Distributed Energy Resources (DERs) with peer-to-peer (P2P) energy trading offers promising solutions for grid modernization by incentivizing prosumers to participate in mitigating peak demand. However, this integration also introduces operational uncertainties and computational challenges. This paper aims to address these challenges with a novel

Cheng Qian, Hainan Zhang, Lei Sha, Zhiming Zheng

With the growing deployment of LLMs in daily applications like chatbots and content generation, efforts to ensure outputs align with human values and avoid harmful content have intensified. However, increasingly sophisticated jailbreak attacks threaten this alignment, aiming to induce unsafe outputs. Current defense efforts either focus on prompt rewriting o

Jun Seok Oh

Let $G$ be a finite group. By a sequence over $G$, we mean a finite unordered string of terms from $G$ with repetition allowed, and we say that it is a product-one sequence if its terms can be ordered so that their product is the identity element of $G$. Then, the Davenport constant $\mathsf D (G)$ is the maximal length of a minimal product-one sequence, tha

Mostafa Mansour, Ahmed Abdelsalam, Ari Happonen, Jari Porras

Recent advancements in monocular neural depth estimation, particularly those achieved by the UniDepth network, have prompted the investigation of integrating UniDepth within a Gaussian splatting framework for monocular SLAM. This study presents UDGS-SLAM, a novel approach that eliminates the necessity of RGB-D sensors for depth estimation within Gaussian spl

Anwesha Chattopadhyay

For a Markov and stationary stochastic process described by the well-known classical master equation, we introduce complex transition rates instead of real transition rates to study the pre-thermal oscillatory behaviour in complex probabilities. Further, for purely imaginary transition rates we obtain persistent infinitely long lived oscillations in complex

Dipankar Srirag, Aditya Joshi, Jacob Eisenstein

Dialect adapters that improve the performance of LLMs for NLU tasks on certain sociolects/dialects/national varieties ('dialects' for the sake of brevity) have been reported for encoder models. In this paper, we extend the idea of dialect adapters to decoder models in our architecture called LoRDD. Using MD-3, a publicly available dataset of word gam

Bae Jun Park

In this work, we establish $L^{p_1}\times \cdots\times L^{p_m}\to L^p$ bounds for maximal multi-(sub)linear singular integrals associated with homogeneous kernels $\frac{Ω(\vec{\boldsymbol{y}}')}{|\vec{\boldsymbol{y}}|^{mn}}$ where $Ω$ is an $L^q$ function on the unit sphere $\mathbb{S}^{mn-1}$ with vanishing moment condition and $q>1$. As an application

Kunming Su, Qiuxia Wu, Panpan Cai, Xiaogang Zhu

Masked point modeling methods have recently achieved great success in self-supervised learning for point cloud data. However, these methods are sensitive to rotations and often exhibit sharp performance drops when encountering rotational variations. In this paper, we propose a novel Rotation-Invariant Masked AutoEncoders (RI-MAE) to address two major challen

Hongseok Oh, Wonseok Hwang

Large Language Models (LLMs) have shown remarkable progress, but their real-world application necessitates reliable calibration. This study conducts a comprehensive analysis of calibration degradation of LLMs across four dimensions: models, calibration metrics, tasks, and confidence extraction methods. Initial analysis showed that the relationship between al

Tapas Das, Florent Foucaud, Clara Marcille, PD Pavan

Monitoring edge-geodetic sets in a graph are subsets of vertices such that every edge of the graph must lie on all the shortest paths between two vertices of the monitoring set. These objects were introduced in a work by Foucaud, Krishna and Ramasubramony Sulochana with relation to several prior notions in the area of network monitoring like distance edge-mo

Peilun He, Gareth W. Peters, Nino Kordzakhia, Pavel V. Shevchenko

The Nelson-Siegel model is widely used in fixed income markets to produce yield curve dynamics. The multiple time-dependent parameter model conveniently addresses the level, slope, and curvature dynamics of the yield curves. In this study, we present a novel state-space functional regression model that incorporates a dynamic Nelson-Siegel model and functiona

Bonan Liu, Handi Yin, Manuel Kaufmann, Jinhao He

We present EgoHDM, an online egocentric-inertial human motion capture (mocap), localization, and dense mapping system. Our system uses 6 inertial measurement units (IMUs) and a commodity head-mounted RGB camera. EgoHDM is the first human mocap system that offers dense scene mapping in near real-time. Further, it is fast and robust to initialize and fully clo

Zanlin Ni, Yulin Wang, Renping Zhou, Rui Lu

Recent studies have demonstrated the effectiveness of token-based methods for visual content generation. As a representative work, non-autoregressive Transformers (NATs) are able to synthesize images with decent quality in a small number of steps. However, NATs usually necessitate configuring a complicated generation policy comprising multiple manually-desig

Jeremy G. Baier, Jeffrey S. Hazboun, Joseph D. Romano

As pulsar timing arrays (PTAs) transition into the detection era of the stochastic gravitational wave background (GWB), it is important for PTA collaborations to review and possibly revise their observing campaigns. The detection of a ''single source'' would be a boon for gravitational astrophysics, as such a source would emit gravitational w

Muhammad Waseem, Reza Bayani, Saeed D. Manshadi

The utilities consider public safety power shut-offs imperative for the mitigation of wildfire risk. This paper presents expansion planning of power system under fire hazard weather conditions. The power lines are quantified based on the risk of fire ignition. A 10-year expansion planning scenario is discussed to supply power to customers by considering thre

Jiachen Guo, Chanwook Park, Xiaoyu Xie, Zhongsheng Sang

A common trend in simulation-driven engineering applications is the ever-increasing size and complexity of the problem, where classical numerical methods typically suffer from significant computational time and huge memory cost. Methods based on artificial intelligence have been extensively investigated to accelerate partial differential equations (PDE) solv

Paula Mellado, Mauricio Sturla

We present the magnetic excitation spectrum of the quantum magnet $\rm NiPS_3$ near the zig-zag ground state of a minimal honeycomb spin Hamiltonian that includes bilinear and biquadratic spin interactions. Our analysis, using a multi-boson generalized spin wave theory suited for spin S=1 systems, revealed two normal modes at the linear level. The one at low

Ghalib Ahmed Tahir

This paper aims to shed light on the ethical problems of creating and deploying computer vision tech, particularly in using publicly available datasets. Due to the rapid growth of machine learning and artificial intelligence, computer vision has become a vital tool in many industries, including medical care, security systems, and trade. However, extensive us

Gursimran Singh, Tianxi Hu, Mohammad Akbari, Qiang Tang

3D models, particularly AI-generated ones, have witnessed a recent surge across various industries such as entertainment. Hence, there is an alarming need to protect the intellectual property and avoid the misuse of these valuable assets. As a viable solution to address these concerns, we rigorously define the novel task of automated 3D visible watermarking

Sandra Zhang Ding, Jiafeng Mao, Kiyoharu Aizawa

Based on recent advanced diffusion models, Text-to-image (T2I) generation models have demonstrated their capabilities to generate diverse and high-quality images. However, leveraging their potential for real-world content creation, particularly in providing users with precise control over the image generation result, poses a significant challenge. In this pa

Haoran Cui, Theodore Maranets, Tengfei Ma, Yan Wang

In nonmetallic crystals, heat is transported by phonons of different frequencies, each contributing differently to the overall heat flux spectrum. In this study, we demonstrate a significant redistribution of heat flux among phonon frequencies when phonons transmit across the interface between dissimilar solids. This redistribution arises from the natural te

Renjun Duan, Shuangqian Liu, Robert M. Strain, Anita Yang

In the paper we study the Boltzmann equation in the diffusive limit in a channel domain $\mathbb{T}^2\times (-1,1)$ for the 3D kinetic Couette flow. Our results demonstrate that the first-order approximation of the solutions is governed by the perturbed incompressible Navier-Stokes-Fourier system around the fluid Couette flow. Moverover, in the absence of ex

Mikhail Borisenkov, Maksim Belyaev, Nithya Rekha Sivakumar, Murugappan Murugappan

Wearable sensors and IoT/IoMT platforms enable continuous, real-time monitoring, but objective digital markers for eating disorders are limited. In this study, we examined whether actimetry and machine learning (ML) could provide objective criteria for food addiction (FA) and symptom counts (SC). In 78 participants (mean age 22.1 +/- 9.5 y; 73.1% women), one

Erin Coleman, Keerthi Vasan G. C., Yuguang Chen, Tucker Jones

The baryon cycle is crucial for understanding galaxy formation, as gas inflows and outflows vary throughout a galaxy's lifetime and affect its star formation rate. Despite the necessity of accretion for galaxy growth at high redshifts, direct observations of inflowing gas have proven elusive especially at $z\gtrsim2$. We present spectroscopic analysis of

Denis Antipov, Benjamin Doerr

Randomized search heuristics (RSHs) are known to have a certain robustness to noise. Mathematical analyses trying to quantify rigorously how robust RSHs are to a noisy access to the objective function typically assume that each solution is re-evaluated whenever it is compared to others. This aims at preventing that a single noisy evaluation has a lasting neg

Don N. Page

The total number of gravitons emitted during nonrelativistic inspiral of two black holes or other effectively point masses is calculated approximately and found to be remarkably close to (well within 1% of, perhaps within about 0.2% of) the initial orbital angular momentum divided by the spin angular momentum of each graviton ($2\hbar$), although at unit ini

Jonathan Wellington Morris, Vishrut Shah, Alex Besanceney, Daksh Shah

Sim-to real gap in Reinforcement Learning is when a model trained in a simulator does not translate to the real world. This is a problem for Autonomous Vehicles (AVs) as vehicle dynamics can vary from simulation to reality, and also from vehicle to vehicle. Slug Mobile is a one tenth scale autonomous vehicle created to help address the sim-to-real gap for AV