March 2024 arXiv papers — page 80

Zixuan Huang, Yating Lin, Fan Yang, Dmitry Berenson

Manipulation of articulated and deformable objects can be difficult due to their compliant and under-actuated nature. Unexpected disturbances can cause the object to deviate from a predicted state, making it necessary to use Model-Predictive Control (MPC) methods to plan motion. However, these methods need a short planning horizon to be practical. Thus, MPC

Anand Natarajan, Chinmay Nirkhe

In classical complexity theory, the two definitions of probabilistically checkable proofs -- the constraint satisfaction and the nonlocal games version -- are computationally equal in power. In the quantum setting, the situation is far less clear. The result MIP* = RE of Ji et. al. (arXiv:2001.04383) and refinements by Natarajan and Zhang (arXiv:2302.04322)

Rhea Acharya, Jessica Chen, Helen Xiao

Peer-to-peer ride-sharing platforms like Uber, Lyft, and DiDi have revolutionized the transportation industry and labor market. At its essence, these systems tackle the bipartite matching problem between two populations: riders and drivers. This research paper comprises two main components: an initial literature review of existing ride-sharing platforms and

Timur Ibrayev, Isha Garg, Indranil Chakraborty, Kaushik Roy

Deep learning has proved successful in many applications but suffers from high computational demands and requires custom accelerators for deployment. Crossbar-based analog in-memory architectures are attractive for acceleration of deep neural networks (DNN), due to their high data reuse and high efficiency enabled by combining storage and computation in memo

Kevin Leder, Ruping Sun, Zicheng Wang, Xuanming Zhang

In this study, we develop consistent estimators for key parameters that govern the dynamics of tumor cell populations when subjected to pharmacological treatments. While these treatments often lead to an initial reduction in the abundance of drug-sensitive cells, a population of drug-resistant cells frequently emerges over time, resulting in cancer recurrenc

Siddharth Suri, Scott Counts, Leijie Wang, Chacha Chen

Until recently, search engines were the predominant method for people to access online information. The recent emergence of large language models (LLMs) has given machines new capabilities such as the ability to generate new digital artifacts like text, images, code etc., resulting in a new tool, a generative search engine, which combines the capabilities of

Adam Chapman

We prove that the maximal dimension of a subspace $V$ of the generic tensor product of $m$ symbol algebras of prime degree $p$ with $\operatorname{Tr}(v^{p-1})=0$ for all $v\in V$ is $\frac{p^{2m}-1}{p-1}$. The same upper bound is thus obtained for $V$ with $\operatorname{Tr}(v)=\operatorname{Tr}(v^2)=\dots=\operatorname{Tr}(v^{p-1})=0$ for all $v \in V$. We

Jelmer de Wolde, Luzia Knoedler, Gianluca Garofalo, Javier Alonso-Mora

As robots shift from industrial to human-centered spaces, adopting mobile manipulators, which expand workspace capabilities, becomes crucial. In these settings, seamless interaction with humans necessitates compliant control. Two common methods for safe interaction, admittance, and impedance control, require force or torque sensors, often absent in lower-cos

Muhammad Ridzuan, Mai Kassem, Numan Saeed, Ikboljon Sobirov

This paper introduces HuLP, a Human-in-the-Loop for Prognosis model designed to enhance the reliability and interpretability of prognostic models in clinical contexts, especially when faced with the complexities of missing covariates and outcomes. HuLP offers an innovative approach that enables human expert intervention, empowering clinicians to interact wit

Sudeb Ranjan Datta, Susmita Chakravorty, Jonathan Ferreira, Pierre-Olivier Petrucci

Observation of blue-shifted X-ray absorption lines indicates the presence of wind from the accretion disk in X-ray binaries. Magnetohydrodynamic (MHD) driving is one of the possible wind launching mechanisms. Recent theoretical development makes magnetic accretion-ejection self-similar solutions much more generalized, and wind can be launched even at much lo

Teo Nguyen, Sarat Moka, Kerrie Mengersen, Benoit Liquet

Compositional data find broad application across diverse fields due to their efficacy in representing proportions or percentages of various components within a whole. Spatial dependencies often exist in compositional data, particularly when the data represents different land uses or ecological variables. Ignoring the spatial autocorrelations in modelling of

Shirshendu Chowdhury, Rajib Dutta, Debanjit Mondal

In this paper, we consider the Camassa-Holm equation posed on the periodic domain $\mathbb{T}$. We show that Camassa-Holm equation is globally approximately controllable by three dimensional external force in $H^s(\mathbb{T})$ for $ s > \frac{3}{2}$ . The proof is based on Agrachev-Sarychev approach in geometric control theory.

Hejie Cui, Zhuocheng Shen, Jieyu Zhang, Hui Shao

Electronic health records (EHRs) contain valuable patient data for health-related prediction tasks, such as disease prediction. Traditional approaches rely on supervised learning methods that require large labeled datasets, which can be expensive and challenging to obtain. In this study, we investigate the feasibility of applying Large Language Models (LLMs)

Ramin G. Daghigh, Michael D. Green, Jodin C. Morey

We use the numerical continued fraction method to investigate quasinormal mode spectra of extremal and non-extremal Reissner-Nordstr\"om black holes in the low and intermediate damping regions. In the extremal case, we develop techniques that significantly expand the calculated spectrum from what had previously appeared in the literature. This allows us to d

Heila Precel, Allison McDonald, Brent Hecht, Nicholas Vincent

Systemic property dispossession from minority groups has often been carried out in the name of technological progress. In this paper, we identify evidence that the current paradigm of large language models (LLMs) likely continues this long history. Examining common LLM training datasets, we find that a disproportionate amount of content authored by Jewish Am

Djuna Croon, Sergio Sevillano Muñoz

Primordially formed extended dark objects would accrete baryonic matter and impact the ionisation history of the Universe. Insisting on consistency with the anisotropies of the cosmic microwave background, we derive constraints on the dark matter fraction for various classes of objects, of different sizes. We introduce a novel scaling technique to speed up n

Aviv Karnieli, Charles Roques-Carmes, Nicholas Rivera, Shanhui Fan

The observation that free electrons can interact coherently with quantized electromagnetic fields and matter systems has led to a plethora of proposals leveraging the unique quantum properties of free electrons. At the heart of these proposals lies the assumption of a strong quantum interaction between a flying free electron and a photonic mode. However, exi

Lennart Klebl, Arne Schobert, Martin Eckstein, Giorgio Sangiovanni

Recent experiments demonstrate precise control over coherently excited circular phonon modes using high-intensity terahertz lasers, opening new pathways towards dynamical, ultrafast design of magnetism in functional materials. While the phonon Zeeman effect enables a theoretical description of phonon-induced magnetism, it lacks efficient angular momentum tra

Silvaneo V. dos Santos, Mariane Branco Alves, Helio S. Migon

This paper introduces kDGLM, an R package designed for Bayesian analysis of Generalized Dynamic Linear Models (GDLM), with a primary focus on both uni- and multivariate exponential families. Emphasizing sequential inference for time series data, the kDGLM package provides comprehensive support for fitting, smoothing, monitoring, and feed-forward intervention

Fabio Iocco, Luca Visinelli

The James Webb Space Telescope (JWST) is unveiling astounding results about the first few hundred million years of life of the Universe, delivering images of galaxies at very high redshifts. Here, we develop a UV luminosity function model for high-redshift galaxies, considering parameters such as the stellar formation rate, dust extinction, and halo mass fun

Lassi Paunonen, Nicolas Vanspranghe, Ruoyu P. T. Wang

We prove that weakly elliptic damping gives sharp energy decay for the abstract damped wave semigroup, where the damping is not in the functional calculus. In this case, there is no overdamping. We show applications in linearised water waves and Kelvin--Voigt damping.

Jingwei Zhang, Lauren Swinnen, Christos Chatzichristos, Victoria Broux

Objective: Most current wearable tonic-clonic seizure (TCS) detection systems are based on extra-cerebral signals, such as electromyography (EMG) or accelerometry (ACC). Although many of these devices show good sensitivity in seizure detection, their false positive rates (FPR) are still relatively high. Wearable EEG may improve performance; however, studies

Quentin Bonnefoy, Jonathan Kley, Di Liu, Alejo N. Rossia

We study a non-universal flavor scenario at the level of the Standard Model Effective Field Theory, according to which the matrix of Wilson coefficients $c_{uW}$ of an up-type electroweak quark dipole operator is aligned with the up-type Yukawa coupling. Such an alignment usually follows from the assumption of Minimal Flavor Violation (MFV), away from which

David McCune, Jennifer Wilson

In this paper, we provide theoretical and empirical estimates for the likelihood of a negative participation paradox under instant runoff voting in three-candidate elections. We determine the probability of the paradox and related conditional probabilities based on the impartial anonymous culture and impartial culture models for both complete and partial bal

Armen Avetisyan, Christopher Xie, Henry Howard-Jenkins, Tsun-Yi Yang

We introduce SceneScript, a method that directly produces full scene models as a sequence of structured language commands using an autoregressive, token-based approach. Our proposed scene representation is inspired by recent successes in transformers & LLMs, and departs from more traditional methods which commonly describe scenes as meshes, voxel grids, poin

Seyed Ali Hosseini Mansoori, Juan F. Pedraza, Morteza Rafiee

Within the framework of extended black hole thermodynamics, where the cosmological constant acts as the thermodynamic pressure and its conjugate as the thermodynamic volume, we analyze the phase structure and thermodynamic geometry of the three-dimensional quantum-corrected BTZ (qBTZ) black hole. Our results uncover two-phase transitions in the $T-S$ plane a

Benito Rodríguez, Javier Chagoya, C. Ortiz

We revisit and extend the study of null geodesics around a slowly rotating black hole in Chern-Simons modified gravity. We employ the Hamilton-Jacobi formalism to derive the equations for the shadow profile and determine its shape. We compare our results with numerical ray tracing, finding good agreement within the validity of our approximations for slow rot

Paula D. López, Cecilia Scannapieco, Sofía A. Cora, Ignacio D. Gargiulo

A significant fraction of local galaxies exhibit stellar bars, non-axisymmetric structures composed of stars, gas, and dust. Identifying key differences between the properties of barred and unbarred galaxies can uncover clues about the conditions for triggering bar formation. We explore the early stages of bar formation in a small sample of disc barred galax

Terese T. Hansen, Joshua D. Simon, Ting S. Li, Domani Sharkey

The growing number of Milky Way satellites detected in recent years has introduced a new focus for stellar abundance analysis. Abundances of stars in satellites have been used to probe the nature of these systems and their chemical evolution. However, for most satellites, only centrally located stars have been examined. This paper presents an analysis of thr

Aram Karakhanyan, Tomás Sanz-Perela

In this paper we prove a classification result for axially symmetric one phase minimizers of the Alt-Phillips free boundary problem in dimensions 3, 4, and 5. To accomplish this, we establish a stability inequality that extends the one for the Alt-Caffarelli problem.

Joshua Baines, Matt Visser

We consider the perturbative, fully explicit, analytical behaviour of photon escape cones in the Kerr spacetime. When one conducts the fully general non-perturbative Kerr analysis, one quickly finds that one must at some point appeal to numerical and/or graphical methods. Herein we find that we are able to say much more if we look at the slow rotation limit

Young-Lo Kim, Lluís Galbany, Isobel Hook, Yijung Kang

The environmental dependence of Type Ia supernova (SN Ia) luminosities is well-established, and efforts are being made to find its origin. Previous studies typically use the currently-observed status of the host galaxy. However, given the delay time between the birth of the progenitor star and the SN Ia explosion, the currently-observed status may differ fro

Jernej F. Kamenik, Nejc Košnik, Martín Novoa-Brunet

We consider the combined measurements of CP-averaged decay rates and direct CP asymmetries of $B^\pm\to K^\pm \ell^+ \ell^-$ and $B^\pm\to \pi^\pm \ell^+ \ell^-$ to probe (non-local) four-quark operator matrix element contributions to rare semileptonic B meson decays. We also explore how their effects could be in principle disentangled from possible local ne

T. O. Winterhalder, S. Lacour, A. Mérand, A. -L. Maire

Precise mass constraints are vital for the characterisation of brown dwarfs and exoplanets. Here we present how the combination of data obtained by Gaia and GRAVITY can help enlarge the sample of substellar companions with measured dynamical masses. We show how the Non-Single-Star (NSS) two-body orbit catalogue contained in Gaia DR3 can be used to inform hig

Sayantan Roy, Sameed Pervaiz, Thereza Paiva, Nandini Trivedi

Cold atom systems provide a rich platform to realize strongly interacting condensed matter systems, and recent progress in fluorescence imaging technique has enabled identification of nontrivial doublon, singlon, and holon correlation functions. We show that these correlators can be used to identify the conditions under which local moments form in an interac

Sangmin Choi, Alok Laddha, Andrea Puhm

Gauge theories and perturbative gravity in four dimensions are governed by a tower of infinite-dimensional symmetries which arise from tree-level soft theorems. However, aside from the leading soft theorems which are all-loop exact, subleading ones receive loop corrections due to long-range infrared effects which result in new soft theorems with logarithmic

Jorge Castelo Mourelle, Christoph Adam, Juan Calderón Bustillo, Nicolas Sanchis-Gual

Rotating fermion-boson stars are hypothetical celestial objects that consist of both fermionic and bosonic matter interacting exclusively through gravity. Bosonic fields are believed to arise in certain models of particle physics describing dark matter and could accumulate within neutron stars, modifying some of their properties and gravitational wave emissi

Khyati Malhan, Hans-Walter Rix

Using $\textit{Gaia}$ DR3 astrometry and spectroscopy, we study two new substructures in the orbit-metallicity space of the inner Milky Way: $\textit{Shakti}$ and $\textit{Shiva}$. They were identified as two confined, high-contrast overdensities in the $(L_z, E)$ distribution of bright ($G<16$) and metal-poor ($-2.5<\rm{[M/H]}<-1.0$) stars. Both have stella

Zoltan Bajnok, Bercel Boldis, Gregory P. Korchemsky

Various observables in different four-dimensional superconformal Yang-Mills theories can be computed exactly as Fredholm determinants of truncated Bessel operators. We exploit this relation to determine their dependence on the 't Hooft coupling constant. Unlike the weak coupling expansion, which has a finite radius of convergence, the strong coupling expansi

Davide Gaiotto, Justin Kulp, Jingxiang Wu

We discuss the role of formal deformation theory in quantum field theories and present various ``higher operations'' which control their deformations, (generalized) OPEs, and anomalies. Particular attention is paid to holomorphic-topological theories where we systematically describe and regularize the Feynman diagrams which compute these higher operations in

R. G. Tress, M. C. Sormani, P. Girichidis, S. C. O. Glover

The interstellar medium in the Milky Way's Central Molecular Zone (CMZ) is known to be strongly magnetised, but its large-scale morphology and impact on the gas dynamics are not well understood. We explore the impact and properties of magnetic fields in the CMZ using three-dimensional non-self gravitating magnetohydrodynamical simulations of gas flow in an e

Mykhaylo Usatyuk, Ying Zhao

We study closed universes in holographic theories of quantum gravity. We argue that within any fixed theory, factorization implies there is one unique closed universe state. The wave function of any state that can be prepared by the path integral is proportional to the Hartle-Hawking wave function. This unique wave function depends on the properties of the u

Shayan Majidy

Studying noncommuting conserved quantities, or 'charges,' has revealed a conceptual puzzle: noncommuting charges hinder thermalization in some ways yet promote it in others. While many quantum systems thermalize according to the Eigenstate Thermalization Hypothesis (ETH), systems with 'dynamical symmetries' violate the ETH and exhibit non-stationary dynamics

Benjamin M. Tofflemire, Lisa Prato, Adam L. Kraus, Dominique Segura-Cox

Close binary systems present challenges to planet formation. As binary separations decrease, so too do the occurrence rates of protoplanetary disks in young systems and planets in mature systems. For systems that do retain disks, their disk masses and sizes are altered by the presence of the binary companion. Through the study of protoplanetary disks in bina

Hadi Alzayer, Zhihao Xia, Xuaner Zhang, Eli Shechtman

We propose a generative model that, given a coarsely edited image, synthesizes a photorealistic output that follows the prescribed layout. Our method transfers fine details from the original image and preserve the identity of its parts. Yet, it adapts it to the lighting and context defined by the new layout. Our key insight is that videos are a powerful sour

Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia

This paper focuses on task-agnostic prompt compression for better generalizability and efficiency. Considering the redundancy in natural language, existing approaches compress prompts by removing tokens or lexical units according to their information entropy obtained from a causal language model such as LLaMa-7B. The challenge is that information entropy may

Willem Elbers, Carlos S. Frenk, Adrian Jenkins, Baojiu Li

Large-scale structure surveys have reported measurements of the density of matter, $\Omega_\mathrm{m}$, and the amplitude of clustering, $\sigma_8$, that are in tension with the values inferred from observations of the cosmic microwave background. While this may be a sign of new physics that slows the growth of structure at late times, strong astrophysical f

Zuyan Liu, Yuhao Dong, Yongming Rao, Jie Zhou

In the realm of vision-language understanding, the proficiency of models in interpreting and reasoning over visual content has become a cornerstone for numerous applications. However, it is challenging for the visual encoder in Large Vision-Language Models (LVLMs) to extract useful features tailored to questions that aid the language model's response. Furthe

Mengting Chen, Xi Chen, Zhonghua Zhai, Chen Ju

This paper introduces a novel framework for virtual try-on, termed Wear-Any-Way. Different from previous methods, Wear-Any-Way is a customizable solution. Besides generating high-fidelity results, our method supports users to precisely manipulate the wearing style. To achieve this goal, we first construct a strong pipeline for standard virtual try-on, suppor

Ce Zhang, Simon Stepputtis, Katia Sycara, Yaqi Xie

Large-scale pre-trained Vision-Language Models (VLMs) have exhibited impressive zero-shot performance and transferability, allowing them to adapt to downstream tasks in a data-efficient manner. However, when only a few labeled samples are available, adapting VLMs to distinguish subtle differences between similar classes in specific downstream tasks remains c

Linjiang Huang, Rongyao Fang, Aiping Zhang, Guanglu Song

In this study, we delve into the generation of high-resolution images from pre-trained diffusion models, addressing persistent challenges, such as repetitive patterns and structural distortions, that emerge when models are applied beyond their trained resolutions. To address this issue, we introduce an innovative, training-free approach FouriScale from the p

Shuai Yang, Yifan Zhou, Ziwei Liu, Chen Change Loy

The remarkable efficacy of text-to-image diffusion models has motivated extensive exploration of their potential application in video domains. Zero-shot methods seek to extend image diffusion models to videos without necessitating model training. Recent methods mainly focus on incorporating inter-frame correspondence into attention mechanisms. However, the s

Carlos Rodriguez-Pardo, Dan Casas, Elena Garces, Jorge Lopez-Moreno

We introduce TexTile, a novel differentiable metric to quantify the degree upon which a texture image can be concatenated with itself without introducing repeating artifacts (i.e., the tileability). Existing methods for tileable texture synthesis focus on general texture quality, but lack explicit analysis of the intrinsic repeatability properties of a textu

Baifeng Shi, Ziyang Wu, Maolin Mao, Xin Wang

Scaling up the size of vision models has been the de facto standard to obtain more powerful visual representations. In this work, we discuss the point beyond which larger vision models are not necessary. First, we demonstrate the power of Scaling on Scales (S$^2$), whereby a pre-trained and frozen smaller vision model (e.g., ViT-B or ViT-L), run over multipl

Kartik Narayan, Vibashan VS, Rama Chellappa, Vishal M. Patel

In this work, we introduce FaceXFormer, an end-to-end unified transformer model capable of performing ten facial analysis tasks within a single framework. These tasks include face parsing, landmark detection, head pose estimation, attribute prediction, age, gender, and race estimation, facial expression recognition, face recognition, and face visibility. Tra

Wanqi Yin, Zhongang Cai, Ruisi Wang, Fanzhou Wang

Estimating human and camera trajectories with accurate scale in the world coordinate system from a monocular video is a highly desirable yet challenging and ill-posed problem. In this study, we aim to recover expressive parametric human models (i.e., SMPL-X) and corresponding camera poses jointly, by leveraging the synergy between three critical players: the

Jeffrey Cheng, Marc Marone, Orion Weller, Dawn Lawrie

Released Large Language Models (LLMs) are often paired with a claimed knowledge cutoff date, or the dates at which training data was gathered. Such information is crucial for applications where the LLM must provide up to date information. However, this statement only scratches the surface: do all resources in the training data share the same knowledge cutoff

Xianglong He, Junyi Chen, Sida Peng, Di Huang

In recent years, 3D Gaussian splatting has emerged as a powerful technique for 3D reconstruction and generation, known for its fast and high-quality rendering capabilities. To address these shortcomings, this paper introduces a novel diffusion-based framework, GVGEN, designed to efficiently generate 3D Gaussian representations from text input. We propose two

Maria Gabriella Kuhn

Let $G=PGL(2,Q_q)$. In this paper we shall investigate the group of measurable currents taking values in $G$. The key observation is that $G$ is acting by automorphisms on a homogeneous tree, which will play the role of the upper half plane in the case of $PSL(2,R)$.

Hongwei Bran Li, Fernando Navarro, Ivan Ezhov, Amirhossein Bayat

Uncertainty in medical image segmentation tasks, especially inter-rater variability, arising from differences in interpretations and annotations by various experts, presents a significant challenge in achieving consistent and reliable image segmentation. This variability not only reflects the inherent complexity and subjective nature of medical image interpr

Vittorio Cocchi, Rossana Morandi

In the research on the origin of life, topics that can be considered reasonably shared by the generality of researchers are initially identified. It is then shown that the application of these principles to the results obtained with the IdLE-IdLA mathematical model for the simulation of aggregative processes, leads to the conclusion that the primordial forma

Hongyang Li, Hao Zhang, Shilong Liu, Zhaoyang Zeng

In this paper, we propose a simple and strong framework for Tracking Any Point with TRansformers (TAPTR). Based on the observation that point tracking bears a great resemblance to object detection and tracking, we borrow designs from DETR-like algorithms to address the task of TAP. In the proposed framework, in each video frame, each tracking point is repres

T. Chaumont-Frelet, A. Ern

We derive a posteriori error estimates for the the scalar wave equation discretized in space by continuous finite elements and in time by the explicit leapfrog scheme. Our analysis combines the idea of invoking extra time-regularity for the right-hand side, as previously introduced in the space semi-discrete setting, with a novel, piecewise quartic, globally

Rajeev Yasarla, Manish Kumar Singh, Hong Cai, Yunxiao Shi

In this paper, we propose a novel video depth estimation approach, FutureDepth, which enables the model to implicitly leverage multi-frame and motion cues to improve depth estimation by making it learn to predict the future at training. More specifically, we propose a future prediction network, F-Net, which takes the features of multiple consecutive frames a

Yaxi Hu, Amartya Sanyal, Bernhard Schölkopf

When analysing Differentially Private (DP) machine learning pipelines, the potential privacy cost of data-dependent pre-processing is frequently overlooked in privacy accounting. In this work, we propose a general framework to evaluate the additional privacy cost incurred by non-private data-dependent pre-processing algorithms. Our framework establishes uppe

Qilong Wu, Varun Chandrasekaran

Watermarking approaches are proposed to identify if text being circulated is human or large language model (LLM) generated. The state-of-the-art watermarking strategy of Kirchenbauer et al. (2023a) biases the LLM to generate specific (``green'') tokens. However, determining the robustness of this watermarking method is an open problem. Existing attack method

Elaine Sui, Xiaohan Wang, Serena Yeung-Levy

Advancements in vision-language models (VLMs) have propelled the field of computer vision, particularly in the zero-shot learning setting. Despite their promise, the effectiveness of these models often diminishes due to domain shifts in test environments. To address this, we introduce the Test-Time Prototype Shifting (TPS) framework, a pioneering approach de

James Hughes

This work studies Legendrian loop actions on exact Lagrangian fillings of Legendrian links in $(\R^3, \xi_{\st})$. By identifying the induced action of Legendrian loops as generators of cluster modular groups, we establish the existence of faithful group actions on the exact Lagrangian fillings of several families of Legendrian positive braid closures, inclu

Joe Suk, Arpit Agarwal

In $K$-armed dueling bandits, the learner receives preference feedback between arms, and the regret of an arm is defined in terms of its suboptimality to a $\textit{winner}$ arm. The $\textit{non-stationary}$ variant of the problem, motivated by concerns of changing user preferences, has received recent interest (Saha and Gupta, 2022; Buening and Saha, 2023;

Ahlam Hannachi, Wael Jaafar, Salim Bitam, Nabil Ouazene

The 6TiSCH protocol stack plays a vital role in enabling reliable and energy-efficient communications for the Industrial Internet of Things (IIoT). However, it faces challenges, including prolonged network formation, inefficient parent switching, high control packet overhead, and suboptimal resource utilization. To tackle these issues, we propose in this pap

Christian Fiedler, Johanna Menn, Lukas Kreisköther, Sebastian Trimpe

Optimizing an unknown function under safety constraints is a central task in robotics, biomedical engineering, and many other disciplines, and increasingly safe Bayesian Optimization (BO) is used for this. Due to the safety critical nature of these applications, it is of utmost importance that theoretical safety guarantees for these algorithms translate into

Sohail, Vivek Pandey, Uttam Singh, Siddhartha Das

Quantum information processing and computing tasks can be understood as quantum networks, comprising quantum states and channels and possible physical transformations on them. It is hence pertinent to estimate the change in informational content of quantum processes due to physical transformations they undergo. The physical transformations of quantum states

He Wang, Laixi Shi, Yuejie Chi

In offline reinforcement learning (RL), the absence of active exploration calls for attention on the model robustness to tackle the sim-to-real gap, where the discrepancy between the simulated and deployed environments can significantly undermine the performance of the learned policy. To endow the learned policy with robustness in a sample-efficient manner i

Alexander Khazatsky, Karl Pertsch, Suraj Nair, Ashwin Balakrishna

The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. However, creating such datasets is challenging: collecting robot manipulation data in diverse environments poses logistical and safety challenges and requires substantial investments

C. H. Zepeda-Fernández, F. A. Sánchez-Arévalo, E. Moreno-Barbosa

The solar radiation are electromagnetic waves, composed of infrared, visible spectrum and ultraviolet. The infrared component is the cause of thermal energy, the visible spectrum allows to see and the ultraviolet component is the most energetic part and dangerous for the human body (skin and eyes). The ultraviolet rays are divided in a wavelength range, in t

Vidhi Jain, Maria Attarian, Nikhil J Joshi, Ayzaan Wahid

Large-scale multi-task robotic manipulation systems often rely on text to specify the task. In this work, we explore whether a robot can learn by observing humans. To do so, the robot must understand a person's intent and perform the inferred task despite differences in the embodiments and environments. We introduce Vid2Robot, an end-to-end video-conditioned

Luca Boccioli, Lorenzo Roberti

Recent developments in multi-dimensional simulations of core-collapse supernovae have considerably improved our understanding of this complex phenomenon. In addition to that, one-dimensional (1D) studies have been employed to study the explosion mechanism and its causal connection to the pre-collapse structure of the star, as well as to explore the vast para

Serte Donderwinkel, Brett Kolesnik

Sina\u{i} initiated the study of random walks with persistently positive area processes, motivated by shock waves in solutions to the inviscid Burgers' equation. We find the precise asymptotic probability that the area process of a random walk bridge is an excursion. A key ingredient is an analogue of Sparre Andersen's classical formula. The asymptotics are

Serte Donderwinkel, Brett Kolesnik

We study the relationship between tournaments and random walks. This connection was first observed by Erd\H{o}s and Moser. Winston and Kleitman came close to showing that $S_n=\Theta(4^n/n^{5/2})$. Building on this, and works by Tak\'acs, these asymptotic bounds were confirmed by Kim and Pittel. In this work, we verify Moser's conjecture that $S_n\sim C4^n/n

Yang Li, Diederik Roest, Tonnis ter Veldhuis

It was recently discovered by Arkani-Hamed et al and Cao et al that the colour-ordered scattering amplitudes of Tr$(\Phi^3)$, the non-linear sigma model and Yang-Mills-scalar vanish at specific loci. We build on this observation and demonstrate that, beyond colour ordering, scattering amplitudes can display higher-order hidden zeros. A first example are the

James Koch, Madelyn Shapiro, Himanshu Sharma, Draguna Vrabie

Differential algebraic equations (DAEs) describe the temporal evolution of systems that obey both differential and algebraic constraints. Of particular interest are systems that contain implicit relationships between their components, such as conservation laws. Here, we present an Operator Splitting (OS) numerical integration scheme for learning unknown comp

Krystof Brezina, Hubert Beck, Ondrej Marsalek

Aromatic compounds form an unusual kind of hydrogen bond with water and ammonia molecules, known as the $\pi$-hydrogen bond. In this work, we report ab initio path integral molecular dynamics simulations enhanced by machine-learning potentials to study the structural, dynamical, and spectroscopic properties of solutions of benzene in liquid water and ammonia

Joana Ribeiro de Faria, Huiyuan Xie, Felix Steffek

Court transcripts and judgments are rich repositories of legal knowledge, detailing the intricacies of cases and the rationale behind judicial decisions. The extraction of key information from these documents provides a concise overview of a case, crucial for both legal experts and the public. With the advent of large language models (LLMs), automatic inform

Efrain Torres-Lomas, Jimena Lado-Jimena, Guillermo Garcia-Zamora, Luis Diaz-Garcia

Grape cluster architecture and compactness are complex traits influencing disease susceptibility, fruit quality, and yield. Evaluation methods for these traits include visual scoring, manual methodologies, and computer vision, with the latter being the most scalable approach. Most of the existing computer vision approaches for processing cluster images often

K. V. Plakitina, M. S. Kirsanova, S. V. Kalenskii, S. V. Salii

We present results of a spectral survey towards a dense molecular condensation and young stellar objects (YSOs) projected on the border of the HII region RCW 120 and discuss emission of 20 molecules which produce the brightest lines. The survey was performed with the APEX telescope in the frequency range 200 -- 260 GHz. We provide evidences for two outflows

Wenjing Wang, Huan Yang, Jianlong Fu, Jiaying Liu

Understanding illumination and reducing the need for supervision pose a significant challenge in low-light enhancement. Current approaches are highly sensitive to data usage during training and illumination-specific hyper-parameters, limiting their ability to handle unseen scenarios. In this paper, we propose a new zero-reference low-light enhancement framew

K. Fukushima, S. B. Kobayashi, K. Matsushita

The interstellar medium (ISM) in starburst galaxies contains plenty of chemical elements synthesised by core-collapse supernova explosions. By measuring the abundances of these metals, we can study the chemical enrichment within galaxies and the transportation of metals into circumgalactic environments through powerful outflows. We perform the spectral analy

Hang Jung Ling, Salomé Bru, Julia Puig, Florian Vixège

Intraventricular vector flow mapping (iVFM) seeks to enhance and quantify color Doppler in cardiac imaging. In this study, we propose novel alternatives to the traditional iVFM optimization scheme by utilizing physics-informed neural networks (PINNs) and a physics-guided nnU-Net-based supervised approach. When evaluated on simulated color Doppler images deri

Yihong Luo, Xiaolong Chen, Xinghua Qu, Tianyang Hu

Recently, some works have tried to combine diffusion and Generative Adversarial Networks (GANs) to alleviate the computational cost of the iterative denoising inference in Diffusion Models (DMs). However, existing works in this line suffer from either training instability and mode collapse or subpar one-step generation learning efficiency. To address these i

Peter Stechlinski, Sameh Eisa, Hesham Abdelfattah

New sensitivity-based methods are developed for determining identifiability and observability of nonsmooth input-output systems. More specifically, lexicographic calculus is used to construct nonsmooth sensitivity rank condition (SERC) tests, which we call lexicographic SERC (L-SERC) tests. The introduced L-SERC tests are: (i) practically implementable and a

Antonin Badura, Warlley H. Campos, Venkata K. Bharadwaj, Ismaïla Kounta

The anomalous Nernst effect generates transverse voltage to the applied thermal gradient in magnetically ordered systems. The effect was previously considered excluded in compensated magnetic materials with collinear ordering. However, in the recently identified class of compensated magnetic materials, dubbed altermagnets, time-reversal symmetry breaking in

Gionnieve Lim, Simon T. Perrault

Generative artificial intelligence (GenAI) can rapidly produce large and diverse volumes of content. This lends to it a quality of creativity which can be empowering in the early stages of design. In seeking to understand how creative ways to address practical issues can be conceived between humans and GenAI, we conducted a rapid ideation workshop with 21 pa

Bruce G. Elmegreen

The correlation between interstellar turbulent speed and local star formation rate surface density, Sigma_SFR, is studied using CO observations in the PHANGS survey. The local velocity dispersion of molecular gas, sigma, increases with Sigma_SFR, but the virial parameter, alpha_vir, is about constant, suggesting the molecular gas remains self-gravitating. Th

Vladimir S. Gerdjikov, Georgi G. Grahovski

The paper is devoted to $N$-wave equations with constant boundary conditions related to symplectic Lie algebras. We study the spectral properties of a class of Lax operators $L$, whose potentials $Q(x,t)$ tend to constants $Q_\pm$ for $x\to \pm \infty$. For special choices of $Q_\pm$ we outline the spectral properties of $L$, the direct scattering transform

Grant Buster, Pavlo Pinchuk, Jacob Barrons, Ryan McKeever

The recent growth in renewable energy development in the United States has been accompanied by a simultaneous surge in renewable energy siting ordinances. These zoning laws play a critical role in dictating the placement of wind and solar resources that are critical for achieving low-carbon energy futures. In this context, efficient access to and management

Quang Minh Bui, Margarida Carvalho, José Neto

The combinatorial pricing problem (CPP) is a bilevel problem in which the leader maximizes their revenue by imposing tolls on certain items that they can control. Based on the tolls set by the leader, the follower selects a subset of items corresponding to an optimal solution of a combinatorial optimization problem. To accomplish the leader's goal, the tolls

Hanlin Wang, Zhan Tong, Kecheng Zheng, Yujun Shen

The Audio Description (AD) task aims to generate descriptions of visual elements for visually impaired individuals to help them access long-form video content, like movies. With video feature, text, character bank and context information as inputs, the generated ADs are able to correspond to the characters by name and provide reasonable, contextual descripti

Maximilian Daschner, Bruno Gudac, Mario Novak, Cheng Liu

We report a detailed investigation of the Fermi surface in the layered Dirac semimetal TaNiTe$_5$. We probed the magnetization, magnetic torque and magnetoresistance in high-quality single crystals. Pronounced Shubnikov - de Haas (SdH) and de Haas - van Alphen (dHvA) oscillations are observed in magnetic fields above 3T and at temperatures of up to 22K. Mult

Taehyeon Kim, Byung-Cheol Min

In this paper, we introduce Semantic Layering in Room Segmentation via LLMs (SeLRoS), an advanced method for semantic room segmentation by integrating Large Language Models (LLMs) with traditional 2D map-based segmentation. Unlike previous approaches that solely focus on the geometric segmentation of indoor environments, our work enriches segmented maps with

Jun Gao, Suyun Jiang, Hong Liu, Maya Sankar

We study the generalized Ramsey--Tur\'an function $\mathrm{RT}(n,K_s,K_t,o(n))$, which is the maximum possible number of copies of $K_s$ in an $n$-vertex $K_t$-free graph with independence number $o(n)$. The case when $s=2$ was settled by Erd{\H{o}}s, S{\'o}s, Bollob{\'a}s, Hajnal, and Szemer\'{e}di in the 1980s. We combinatorially resolve the general case f