March 2024 arXiv papers — page 65

Narek Tumanyan, Assaf Singer, Shai Bagon, Tali Dekel

We present DINO-Tracker -- a new framework for long-term dense tracking in video. The pillar of our approach is combining test-time training on a single video, with the powerful localized semantic features learned by a pre-trained DINO-ViT model. Specifically, our framework simultaneously adopts DINO's features to fit to the motion observations of the test v

Tom Burgert, Begüm Demir

The application of data augmentation for deep learning (DL) methods plays an important role in achieving state-of-the-art results in supervised, semi-supervised, and self-supervised image classification. In particular, channel transformations (e.g., solarize, grayscale, brightness adjustments) are integrated into data augmentation pipelines for remote sensin

Richard B. True, Henry P. Freund, Michael V. Fazio, Patrick G. O'Shea

High peak and average power free-electron lasers (FELs) in the terahertz region (THz) require small diameter, low-emittance, and high voltage electron beams. This paper presents two 1.5-2 MV, 100-200 A, thermionic cathode electron source approaches for compact megawatt range peak power, multi-kilowatt average power, high repetition rate, THz FELs. The prefer

Charlott Vallon, Alessandro Pinto, Bartolomeo Stellato, Francesco Borrelli

This paper introduces a novel data-driven hierarchical control scheme for managing a fleet of nonlinear, capacity-constrained autonomous agents in an iterative environment. We propose a control framework consisting of a high-level dynamic task assignment and routing layer and low-level motion planning and tracking layer. Each layer of the control hierarchy u

Ben Mazel, Joshua Sandor, Charles Wang, Xi Yin

We analyze deformations of two-dimensional conformal field theory (CFT) from the perspective of classical bosonic closed string field theory (SFT). The latter can be viewed as a version of Wilsonian renormalization group (RG) improved conformal perturbation theory, where the renormalization scheme is defined through the choice of string vertices in the const

Souhayl Sadik, Arash Yavari

It is known that the balance laws of hyperelasticity (Green elasticity), i.e., conservation of mass and balance of linear and angular momenta, can be derived using the first law of thermodynamics by postulating its invariance under superposed rigid body motions of the Euclidean ambient space -- the Green-Naghdi-Rivlin theorem. In the case of a non-Euclidean

Adam Ball, Y. T. Albert Law, Gabriel Wong

Previous work on black hole partition functions and entanglement entropy suggests the existence of "edge" degrees of freedom living on the (stretched) horizon. We identify a local and "shrinkable" boundary condition on the stretched horizon that gives rise to such degrees of freedom. They can be interpreted as the Goldstone bosons of gauge transformations su

Shimao Zhang, Yu Bao, Shujian Huang

Recently, Large Language Models (LLMs) have demonstrated outstanding performance across a wide range of downstream language tasks. Temperature sampling is a commonly used decoding strategy for LLMs' generation process. However, a fixed temperature parameter is used in most cases, which may not always be an optimal choice for balancing generation quality and

David M. Warme

"Strength" is an important property of inequalities used in mixed-integer optimization, both in theory and practice. Unfortunately, no good formal characterization for strength exists, nor is it well-understood. The first paper explored two strength indicators (extreme point ratio (EPR) and centroid distance (CD)), applying them to the subtour inequalities o

Junhyeong Cho, Kim Youwang, Hunmin Yang, Tae-Hyun Oh

Recent monocular 3D shape reconstruction methods have shown promising zero-shot results on object-segmented images without any occlusions. However, their effectiveness is significantly compromised in real-world conditions, due to imperfect object segmentation by off-the-shelf models and the prevalence of occlusions. To effectively address these issues, we pr

Colleen Robichaux

We give a minimal counterexample for a conjecture of Ross and Yong (2015) which proposes a K-Kohnert rule for Grothendieck polynomials. We conjecture a revised version of this rule. We then prove both rules hold in the $321$-avoiding case.

Marc Illa, Caroline E. P. Robin, Martin J. Savage

We explore the utility of $d=8$ qudits, qu8its, for quantum simulations of the dynamics of 1+1D SU(3) lattice quantum chromodynamics, including a mapping for arbitrary numbers of flavors and lattice size and a re-organization of the Hamiltonian for efficient time-evolution. Recent advances in parallel gate applications, along with the shorter application tim

Charlott Vallon, Mark Pustilnik, Alessandro Pinto, Francesco Borrelli

This paper focuses on the design of hierarchical control architectures for autonomous systems with energy constraints. We focus on systems where energy storage limitations and slow recharge rates drastically affect the way the autonomous systems are operated. Using examples from space robotics and public transportation, we motivate the need for formally desi

Haihao Lu

Linear programming is the seminal optimization problem that has spawned and grown into today's rich and diverse optimization modeling and algorithmic landscape. This article provides an overview of the recent development of first-order methods for solving large-scale linear programming.

Ahmet Alp Kindiroglu, Ozgur Kara, Ogulcan Ozdemir, Lale Akarun

Sign language recognition (SLR) has recently achieved a breakthrough in performance thanks to deep neural networks trained on large annotated sign datasets. Of the many different sign languages, these annotated datasets are only available for a select few. Since acquiring gloss-level labels on sign language videos is difficult, learning by transferring knowl

Zijian Wang, Linhao Li

In this paper, we develop a systematic approach to characterize the 't Hooft anomaly in open quantum systems. Owing to nontrivial couplings to the environment, symmetries in such systems manifest as either strong or weak type. By representing their symmetry transformation through superoperators, we incorporate them in a unified framework that enables a direc

M. Benko, H. Balthasar, P. Gömöry, C. Kuckein

The physical parameters of the sunspot are not fully understood, especially the height dependence of the magnetic field. So far, it is also an open question as to which heights the He I 1083 nm spectral line is formed at. Our aim is to investigate the magnetic and dynamical properties in the atmosphere above a sunspot, from the photosphere to the chromospher

Jianbin Tan, Guoyu Zhang, Xueqin Wang, Hui Huang

Parameters of differential equations are essential to characterize intrinsic behaviors of dynamic systems. Numerous methods for estimating parameters in dynamic systems are computationally and/or statistically inadequate, especially for complex systems with general-order differential operators, such as motion dynamics. This article presents Green's matching,

Yihang Chen, Qianyi Wu, Weiyao Lin, Mehrtash Harandi

3D Gaussian Splatting (3DGS) has emerged as a promising framework for novel view synthesis, boasting rapid rendering speed with high fidelity. However, the substantial Gaussians and their associated attributes necessitate effective compression techniques. Nevertheless, the sparse and unorganized nature of the point cloud of Gaussians (or anchors in our paper

Marko Slapar

We introduce different notions of polynomial convexity with bounds on degrees of polynomials in $\mathbb C^n$. We provide some examples in higher dimensions and show necessary and sufficient conditions for polynomial convexity with degree bounds for certain sets of points in $\mathbb C$ and for certain arcs in the unit circle.

Ruben La

The graded Iwahori--Matsumoto involution $\mathbb{IM}$ is an algebra involution on a graded Hecke algebra closely related to the more well-known Iwahori--Matsumoto involution on an affine Hecke algebra. It induces an involution on the Grothendieck group of complex finite-dimensional representations of $\mathbb{H}$. When $\mathbb{H}$ is a geometric graded Hec

Vyacheslav Ivanovskiy, Dmitry Ponomarev

We find that point particles interacting with a self-dual Yang-Mills field and self-dual gravity manifestly satisfy color-kinematics duality at the level of action. In a similar way color-kinematics duality also holds for a scalar field minimally coupled to a self-dual Yang-Mills field and self-dual gravity. By applying the appropriate limiting procedure to

Nikolaos Tsagkas, Jack Rome, Subramanian Ramamoorthy, Oisin Mac Aodha

Precise manipulation that is generalizable across scenes and objects remains a persistent challenge in robotics. Current approaches for this task heavily depend on having a significant number of training instances to handle objects with pronounced visual and/or geometric part ambiguities. Our work explores the grounding of fine-grained part descriptors for p

Faraz Farahvash, Ao Tang

In this paper, we aim to improve the percentage of packets meeting their deadline in discrete-time M/M/1 queues with infrequent monitoring. More specifically, we look into policies that only monitor the system (and subsequently take actions) after a packet arrival. We model the system as an MDP and provide the optimal policy for some special cases. Furthermo

Tingyu Zhang, Yixin Guo, Hiroyuki Tajima, Haozhao Liang

We theoretically investigate the tunneling transport in a repulsively interacting ultracold Bose-Fermi mixture. A two-terminal model is applied to such a mixture and the supersymmetric-like tunneling current through the junction can be induced by the bias of fermion chemical potential between two reservoirs. The Goldstino, which is the Nambu-Goldstone fermio

Dianye Huang, Chenyang Li, Angelos Karlas, Xiangyu Chu

Precise percutaneous needle detection is crucial for ultrasound (US)-guided interventions. However, inherent limitations such as speckles, needle-like artifacts, and low resolution make it challenging to robustly detect needles, especially when their visibility is reduced or imperceptible. To address this challenge, we propose VibNet, a learning-based framew

David M. Warme

We study strength of inequalities used in mixed-integer programming, and in branch-and-cut algorithms that solve such problems. Strength is an ethereal property lacking good formal definition, but crucial for computational speed. We review several quantitative indicators proposed in the literature we claim provide a measure of the relative strength of inequa

Rémi Blinder, Yuliya Mindarava, Martin Korzeczek, Alastair Marshall

Nuclear hyperpolarization is a known method to enhance the signal in nuclear magnetic resonance (NMR) by orders of magnitude. The present work addresses the $^{13}$C hyperpolarization in diamond micro- and nanoparticles, using the optically-pumped nitrogen-vacancy center (NV) to polarize $^{13}$C spins at room temperature. Consequences of the small particle

Han Zhao, Min Zhang, Wei Zhao, Pengxiang Ding

In recent years, the application of multimodal large language models (MLLM) in various fields has achieved remarkable success. However, as the foundation model for many downstream tasks, current MLLMs are composed of the well-known Transformer network, which has a less efficient quadratic computation complexity. To improve the efficiency of such basic models

Mahroo Bahreinian, Mehdi Kermanshah, Roberto Tron

We consider the problem of designing output feedback controllers that use measurements from a set of landmarks to navigate through a cell-decomposable environment using duality, Control Lyapunov and Barrier Functions (CLF, CBF), and Linear Programming. We propose two objectives for navigating in an environment, one to traverse the environment by making loops

Richard Lang, Mathias Schacht, Jan Volec

We show that for all $k\geq 4$, $\varepsilon >0$, and $n$ sufficiently large, every $k$-uniform hypergraph on $n$ vertices in which each set of $k-3$ vertices is contained in at least $(5/8 + \varepsilon) \binom{n}{3}$ edges contains a tight Hamilton cycle. This is asymptotically best possible.

Mauricio J. del Razo, Luigi Delle Site

A varying number of particles is one of the most relevant characteristics of systems of interest in nature and technology, ranging from the exchange of energy and matter with the surrounding environment to the change of particle number through internal dynamics such as reactions. The physico-mathematical modeling of these systems is extremely challenging, wi

Farhad Rezazadeh

Algorithmic innovation can unleash the potential of the beyond 5G (B5G)/6G communication systems. Artificial intelligence (AI)-driven zero-touch network slicing is envisaged as a promising cutting-edge technology to harness the full potential of heterogeneous 6G networks and enable the automation of demand-aware management and orchestration (MANO). The netwo

Gustavo Polleti

In this paper we discuss a first attempt to build a language learning game for brazilian indigenous languages and the challenges around it. We present a design for the tool with gamification aspects. Then we describe a process to automatically generate language exercises and questions from a dependency treebank and a lexical database for Tupian languages. We

Robert Szalai

We identify reduced order models (ROM) of forced systems from data using invariant foliations. The forcing can be external, parametric, periodic or quasi-periodic. The process has four steps: 1. identify an approximate invariant torus and the linear dynamics about the torus; 2. identify a globally defined invariant foliation about the torus; 3. identify a lo

Quan Zhang, Lei Wang, Vishal M. Patel, Xiaohua Xie

Existing person re-identification methods have achieved remarkable advances in appearance-based identity association across homogeneous cameras, such as ground-ground matching. However, as a more practical scenario, aerial-ground person re-identification (AGPReID) among heterogeneous cameras has received minimal attention. To alleviate the disruption of disc

Le Van Hien

In this paper, we first present a simpler proof of a result on the strict Fr\'echet differentiability of the metric projection operator onto closed balls centered at the origin in Hilbert spaces, which given by Li in \cite{Li24}. Then, based on this result, we prove the strict Fr\'echet differentiability of the metric projection operator onto closed balls wi

G. Guijarro, G. E. Astrakharchik, G. Morigi, J. Boronat

We predict that ultracold bosonic dipolar gases, confined within a multilayer geometry, may undergo self-assembling processes, leading to the formation of chain gases and solids. These dipolar chains, with dipoles aligned across different layers, emerge at low densities and resemble phases observed in liquid crystals, such as nematic and smectic phases. We c

Ahmed ElGazzar, Marcel van Gerven

The unprecedented availability of large-scale datasets in neuroscience has spurred the exploration of artificial deep neural networks (DNNs) both as empirical tools and as models of natural neural systems. Their appeal lies in their ability to approximate arbitrary functions directly from observations, circumventing the need for cumbersome mechanistic modeli

M. Gambarini, G. Agate, G. Ciaramella, E. Miglio

Wave energy conversion is emerging as a promising technology for generating energy from renewable sources. Large-scale implementation of this technology requires the installation of parks of devices. We study the problem of optimizing the park layout and control for wave energy converters of the oscillating water column type. As a test case, we consider a de

Baohe Zhang, Yuan Zhang, Lilli Frison, Thomas Brox

Reinforcement Learning (RL) has been widely applied to many control tasks and substantially improved the performances compared to conventional control methods in many domains where the reward function is well defined. However, for many real-world problems, it is often more convenient to formulate optimization problems in terms of rewards and constraints simu

Parham Rezaee, Shervin Alikhah Asl, Mohammad Hasan Javadi, Shahab Rezaee

Burning fossil fuels emits a significant amount of CO2, causing climate change concerns. CO2 Capture and Storage (CCS) aims to reduce emissions, with fullerenes showing promise as CO2 adsorbents. Recent research focuses on modifying fullerenes using an electric field. In light of this, we carried out DFT studies on some B, N, and P doped C20 (C20-nXn (n = 0,

Lucas Marti, Refik Mansuroglu, Michael J. Hartmann

We present a cooling algorithm for ground state preparation of fermionic Hamiltonians. Our algorithm makes use of the Hamiltonian simulation of the considered system coupled to an ancillary fridge, which is regularly reset to its known ground state. We derive suitable interaction Hamiltonians that originate from ladder operators of the free theory and initia

N. Lazarides, Giorgos P. Veldes, D. J. Frantzeskakis, Ioannis Kourakis

An asymmetric pair of coupled nonlinear Schr{\"o}dinger (CNLS) equations has been derived through a multiscale perturbation method applied to a plasma fluid model, in which two wavepackets of distinct carrier wavenumbers and amplitudes are allowed to co-propagate and interact. The original fluid model was set up for a non-magnetized plasma consisting of cold

Soroush Ghandi, Benjamin Quost, Cassio de Campos

Probabilistic Circuits (PCs) are prominent tractable probabilistic models, allowing for a range of exact inferences. This paper focuses on the main algorithm for training PCs, LearnSPN, a gold standard due to its efficiency, performance, and ease of use, in particular for tabular data. We show that LearnSPN is a greedy likelihood maximizer under mild assumpt

Temple He, Prahar Mitra, Allic Sivaramakrishnan, Kathryn M. Zurek

We derive the soft effective action in $(d+2)$-dimensional abelian gauge theories from the on-shell action obeying Neumann boundary conditions at timelike and null infinity and Dirichlet boundary conditions at spatial infinity. This allows us to identify the on-shell degrees of freedom on the boundary with the soft modes living on the celestial sphere. Follo

R. F. Almada, N. A. M. Araujo, P. Patricio

Wounds in epithelial tissues compromise their vital role in homeostasis. A rapid and efficient wound healing encompasses different mechanisms, which includes the formation of a contractile actin-myosin cable around its edge, known as the purse-string mechanism. We combine mean-field calculations and numerical simulations of the Vertex model to study the inte

Riccardo Busetto, Valentina Breschi, Federica Baracchi, Simone Formentin

Data-driven control offers a viable option for control scenarios where constructing a system model is expensive or time-consuming. Nonetheless, many of these algorithms are not entirely automated, often necessitating the adjustment of multiple hyperparameters through cumbersome trial-and-error processes and demanding significant amounts of data. In this pape

Alicia Durrer, Julia Wolleb, Florentin Bieder, Paul Friedrich

Monitoring diseases that affect the brain's structural integrity requires automated analysis of magnetic resonance (MR) images, e.g., for the evaluation of volumetric changes. However, many of the evaluation tools are optimized for analyzing healthy tissue. To enable the evaluation of scans containing pathological tissue, it is therefore required to restore

Jiří Svoboda, Václav Kozmík, Kvetoslava Bajzíková, Michal Kohout

Recent liquid-crystalline (LC) research is focused on structurally new molecular systems distinct from simple nematic or smectic phases. Sophisticated molecular shape may reveal structural complexity, combining helicity and polarity. Achiral symmetry-breaking in bent-core molecules leads to propensity for synclinic and anticlinic molecular structures within

Jakub Micorek, Horst Possegger, Dominik Narnhofer, Horst Bischof

We propose a novel approach to video anomaly detection: we treat feature vectors extracted from videos as realizations of a random variable with a fixed distribution and model this distribution with a neural network. This lets us estimate the likelihood of test videos and detect video anomalies by thresholding the likelihood estimates. We train our video ano

Thu Nguyen, Alessandro Canossa, Jichen Zhu

Despite its technological breakthroughs, eXplainable Artificial Intelligence (XAI) research has limited success in producing the {\em effective explanations} needed by users. In order to improve XAI systems' usability, practical interpretability, and efficacy for real users, the emerging area of {\em Explainable Interfaces} (EIs) focuses on the user interfac

Lie-Liang Yang

The fundamentals of MIMO communications and MIMO sensing are firstly analyzed with regard to channel and sensing capacities. It is shown that the different objectives of communications and sensing lead to different signaling waveforms required for achieving their capacities. Hence, the optimization of integrated sensing and communications (ISAC) is relied on

Dylan Auty, Roy Miles, Benedikt Kolbeinsson, Krystian Mikolajczyk

Traditional knowledge distillation (KD) relies on a proficient teacher trained on the target task, which is not always available. In this setting, cross-task distillation can be used, enabling the use of any teacher model trained on a different task. However, many KD methods prove ineffective when applied to this cross-task setting. To address this limitatio

Ronan Terpereau, Susanna Zimmermann

We determine the rational real forms of the complex Mori fiber spaces for which the identity component of the automorphism group is a maximal connected algebraic subgroup of $\mathrm{Bir}(\mathbb{P}_{\mathbb{C}}^{3})$. This yields a list of maximal connected algebraic subgroup of $\mathrm{Bir}(\mathbb{P}_{\mathbb{R}}^{3})$. We furthermore determine the equiv

Javier Conde, Miguel González, Nina Melero, Raquel Ferrando

The growing interest in Large Language Models (LLMs) and in particular in conversational models with which users can interact has led to the development of a large number of open-source chat LLMs. These models are evaluated on a wide range of benchmarks to assess their capabilities in answering questions or solving problems on almost any possible topic or to

Dieter Rautenbach, Florian Werner

Graph isomorphism, subgraph isomorphism, and maximum common subgraphs are classical well-investigated objects. Their (parameterized) complexity and efficiently tractable cases have been studied. In the present paper, for a given set of forests, we study maximum common induced subforests and minimum common induced superforests. We show that finding a maximum

Tomás M. Coronado, Joan Carles Pons, Gabriel Riera

Orchard and tree-child networks share an important property with phylogenetic trees: they can be completely reduced to a single node by iteratively deleting cherries and reticulated cherries. As it is the case with phylogenetic trees, the number of ways in which this can be done gives information about the topology of the network. Here, we show that the prob

Gianmaria Ventura, Zaman Bhalli, Michele Rossi, Jacopo Pegoraro

In this letter, we present for the first time a method to estimate the bistatic Doppler frequency of a target with clock asynchronous and mobile Integrated Sensing And Communication (ISAC) devices. Existing approaches have separately tackled the presence of phase offsets due to clock asynchrony or the additional Doppler shift due to device movement. However,

Saba Heidari Gheshlaghi, Milan Aryal, Nasim Yahyasoltani, Masoud Ganji

Enhancing the robustness of deep learning models against adversarial attacks is crucial, especially in critical domains like healthcare where significant financial interests heighten the risk of such attacks. Whole slide images (WSIs) are high-resolution, digitized versions of tissue samples mounted on glass slides, scanned using sophisticated imaging equipm

Ricardo Cannizzaro, Michael Groom, Jonathan Routley, Robert Osazuwa Ness

Manipulation tasks require robots to reason about cause and effect when interacting with objects. Yet, many data-driven approaches lack causal semantics and thus only consider correlations. We introduce COBRA-PPM, a novel causal Bayesian reasoning architecture that combines causal Bayesian networks and probabilistic programming to perform interventional infe

Yueru Jia, Yuhui Yuan, Aosong Cheng, Chuke Wang

Recently, how to achieve precise image editing has attracted increasing attention, especially given the remarkable success of text-to-image generation models. To unify various spatial-aware image editing abilities into one framework, we adopt the concept of layers from the design domain to manipulate objects flexibly with various operations. The key insight

Gabriel Lentchner, William Fritsch, Robert Crowder, Noah Walton

Monte Carlo-transport codes are designed to simulate the complex neutron transport physics associated with nuclear systems. These codes are tasked with simulating phenomena such as temperature effects on cross-sections, thermo-physical effects, reaction rates, and kinematics. It is not computationally possible to simulate the physics of a system exactly. How

Erdal Catak, Mustafa Mullahasanoglu

In this paper, we aim to study the three-dimensional $\mathcal N=2$ supersymmetric dual gauge theories on $S_b^3/\mathbb{Z}_r$ in the context of the gauge/YBE correspondence. We consider hyperbolic hypergeometric integral identities acquired via the equality of supersymmetric lens partition functions as solutions to the decoration transformation and the flip

Mehul Arora, Chirag Shantilal Jain, Lalith Bharadwaj Baru, Kamalaker Dadi

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by varied social cognitive challenges and repetitive behavioral patterns. Identifying reliable brain imaging-based biomarkers for ASD has been a persistent challenge due to the spectrum's diverse symptomatology. Existing baselines in the field have made significant strides in this

Shaojie Li, Xinqi Dong, Danqing Ma, Bo Dang

Mobile Internet user credit assessment is an important way for communication operators to establish decisions and formulate measures, and it is also a guarantee for operators to obtain expected benefits. However, credit evaluation methods have long been monopolized by financial industries such as banks and credit. As supporters and providers of platform netw

Honghui Kim, Neung-Kyung Yu, Nianhan Tian, Andrew J. Medford

Increasing interest in sustainable synthesis of ammonia, nitrates, and urea has led to an increase in studies of catalytic conversion between nitrogen-containing compounds using heterogeneous catalysts. Density functional theory (DFT) is commonly employed to obtain molecular-scale insight into these reactions, but there have been relatively few assessments o

Giulia Baracchini, Ju-Chi Yu, Jenny Rieck, Derek Beaton

Similarity analyses between multiple correlation or covariance tables constitute the cornerstone of network neuroscience. Here, we introduce covSTATIS, a versatile, linear, unsupervised multi-table method designed to identify structured patterns in multi-table data, and allow for the simultaneous extraction and interpretation of both individual and group-lev

Samaresh Mondal, Gabriele Ponti, Tong Bao, Frank Haberl

For many years, it has been claimed that the Galactic ridge X-ray emission at the Galactic Center (GC) is truly diffuse in nature. However, with the advancement of modern X-ray satellites, it has been found that most of the diffuse emission is actually comprised of thousands of previously unresolved X-ray point sources. Further, many studies suggest that a v

Jared Krandel

We investigate characterizations of uniformly rectifiable (UR) metric spaces by so-called weak Carleson conditions for flatness coefficients which measure the extent to which Hausdorff measure on the metric space differs from Hausdorff measure on a normed space. First, we show that UR metric spaces satisfy David and Semmes's weak constant density condition,

Gabriela Fernández, Luis A. Hernández, R. Zamora

We compute the 1-loop vertex function of the QCD coupling in the presence of an ultra intense magnetic field. From the vertex function, we extract the effective coupling and show that it grows with increasing magnetic field. We consider the quark-gluon vertex and the three-gluon vertex, accounting for the propagators of charged particles within the loops usi

Niclas Bernhoff

At higher altitudes, for high temperature gases, for instance near space shuttles moving at hypersonic speed, not only mechanical collisions are affecting the gas flow, but also chemical reactions have an impact on such hypersonic flows. In this work we insert chemical reactions, in form of dissociations and recombinations (associations), in an existing mode

Baijun Li, Yunlan Zuo, Le-Man Kuang, Hui Jing

Attribute to their robustness against loss and external noise, nonreciprocal photonic devices hold great promise for applications in quantum information processing. Recent advancements have demonstrated that nonreciprocal optical transmission in linear systems can be achieved through the strategic introduction of loss. However, a crucial question remains una

Callum Reader

It is known that every monoidal bicategory has an associated braided monoidal category of scalars. In this thesis we show that every monoidal bicategory, which is closed both monoidally and compositionally, can be enriched over the monoidal 2-category of scalar-enriched categories. This enrichment provides a number of key insights into the relationship betwe

Sibo Wang, Hui Tong, Chencan Wang, Qiang Zhao

Within the relativistic Brueckner-Hartree-Fock theory in the full Dirac space, the tensor-force effects on infinite nuclear matter are elucidated by subtracting the matrix elements of tensor forces from the realistic nucleon-nucleon interaction. The tensor-force effects for the binding energy per particle of symmetric nuclear matter (SNM) as well as the symm

Joschka Haltaufderheide, Robert Ranisch

With the introduction of ChatGPT, Large Language Models (LLMs) have received enormous attention in healthcare. Despite their potential benefits, researchers have underscored various ethical implications. While individual instances have drawn much attention, the debate lacks a systematic overview of practical applications currently researched and ethical issu

Mengru Wang, Ningyu Zhang, Ziwen Xu, Zekun Xi

This paper investigates using knowledge editing techniques to detoxify Large Language Models (LLMs). We construct a benchmark, SafeEdit, which covers nine unsafe categories with various powerful attack prompts and equips comprehensive metrics for systematic evaluation. We conduct experiments with several knowledge editing approaches, indicating that knowledg

Yongqiang Wang, Haisheng Fu, Qi Cao, Shang Wang

Recently, deep learning technology has been successfully applied in the field of image compression, leading to superior rate-distortion performance. It is crucial to design an effective and efficient entropy model to estimate the probability distribution of the latent representation. However, the majority of entropy models primarily focus on one-dimensional

Rafael Bailo, Alethea Barbaro, Susana N. Gomes, Konstantin Riedl

We introduce CBXPy and ConsensusBasedX.jl, Python and Julia implementations of consensus-based interacting particle systems (CBX), which generalise consensus-based optimization methods (CBO) for global, derivative-free optimisation. The raison d'\^etre of our libraries is twofold: on the one hand, to offer high-performance implementations of CBX methods that

Hanieh Alipour, Nick Pendar, Kohinoor Roy

In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities has ignited a surge in research contributions within this domain, spanning a diverse spectrum of topics. These contributi

Max Ku, Cong Wei, Weiming Ren, Harry Yang

In the dynamic field of digital content creation using generative models, state-of-the-art video editing models still do not offer the level of quality and control that users desire. Previous works on video editing either extended from image-based generative models in a zero-shot manner or necessitated extensive fine-tuning, which can hinder the production o

Jennifer Chien, Kevin R. McKee, Jackie Kay, William Isaac

Researchers and developers increasingly rely on toxicity scoring to moderate generative language model outputs, in settings such as customer service, information retrieval, and content generation. However, toxicity scoring may render pertinent information inaccessible, rigidify or "value-lock" cultural norms, and prevent language reclamation processes, parti

Matt Raymond, Jacob Charles Saldinger, Paolo Elvati, Clayton Scott

Extracting meaningful features from complex, high-dimensional datasets across scientific domains remains challenging. Current methods often struggle with scalability, limiting their applicability to large datasets, or make restrictive assumptions about feature-property relationships, hindering their ability to capture complex interactions. BoUTS's general an

Alex Ranne, Liming Kuang, Yordanka Velikova, Nassir Navab

In minimally invasive endovascular procedures, contrast-enhanced angiography remains the most robust imaging technique. However, it is at the expense of the patient and clinician's health due to prolonged radiation exposure. As an alternative, interventional ultrasound has notable benefits such as being radiation-free, fast to deploy, and having a small foot

Joseph Moyalan, Sriram S. K. S Narayanan, Andrew Zheng, Umesh Vaidya

We consider the problem of navigating a nonlinear dynamical system from some initial set to some target set while avoiding collision with an unsafe set. We extend the concept of density function to control density function (CDF) for solving navigation problems with safety constraints. The occupancy-based interpretation of the measure associated with the dens

Alexander Yurishchev, Neima Brauner, Amos Ullmann

Two-phase flow with low liquid loads is common in high-pressure natural gas offshore gathering and transmission pipelines. During gas production slowdowns or shutdowns, an accumulation of liquid in the lower sections of subsea pipelines may occur. This phenomenon is observed in jumpers that connect different units in deep-water subsea gas production faciliti

Marcos Marino, Maximilian Schwick

We study the relation between large N instantons and conventional instantons, focusing on matrix models and topological strings. We show that the resurgent properties of the perturbative series at fixed but arbitrary N, including the replica limit N = 0, can be obtained from large N instantons. In the case of topological strings, it has been conjectured that

Krzysztof Lebioda, Viktor Vorobev, Nenad Petrovic, Fengjunjie Pan

We propose a novel model- and feature-based approach to development of vehicle software systems, where the end architecture is not explicitly defined. Instead, it emerges from an iterative process of search and optimization given certain constraints, requirements and hardware architecture, while retaining the property of single-system illusion, where applica

Lucas Monteiro Paes, Dennis Wei, Hyo Jin Do, Hendrik Strobelt

Despite the increasing use of large language models (LLMs) for context-grounded tasks like summarization and question-answering, understanding what makes an LLM produce a certain response is challenging. We propose Multi-Level Explanations for Generative Language Models (MExGen), a technique to provide explanations for context-grounded text generation. MExGe

Tobias Fritz

It is an important feature of our existing physical theories that observables generate one-parameter groups of transformations. In classical Hamiltonian mechanics and quantum mechanics, this is due to the fact that the observables form a Lie algebra, and it manifests itself in Noether's theorem. In this paper, we introduce Lie quandles as the minimal mathema

Anirudh Sundar, Christopher Richardson, Larry Heck

Distilling large, unstructured text into a structured, condensed form such as tables is an open research problem. One of the primary challenges in automatically generating tables is ensuring their syntactic validity. Prior approaches address this challenge by including additional parameters in the Transformer's attention mechanism to attend to specific rows

Hermann König

For $2 < p < p_0 \simeq 26.265$, the hyperplane section of the $l_p^n$-unit ball $B_p^n$ perpendicular to a^(n) = 1/sqrt(n) (1, ... ,1) for large $n$ has larger volume than the one orthogonal to a^(2) = 1/sqrt(2) (1,1,0, ...,0), as shown by Oleszkiewicz. This is different from the case of $l_\infty^n$ considered by Ball. We give a quantitative estimate for w

Suresh Venkatasubramanian, Timnit Gebru, Ufuk Topcu, Haley Griffin

Based on our workshop activities, we outlined three ways in which research can support community needs: (1) Mapping the ecosystem of both the players and ecosystem and harm landscapes, (2) Counter-Programming, which entails using the same surveillance tools that communities are subjected to observe the entities doing the surveilling, effectively protecting p

Po-Chen Kuo, Shen-Liang Yang, Neill Lambert, Jhen-Dong Lin

The Liouvillian skin effect and the non-Hermitian skin effect have both been used to explain the localization of eigenmodes near system boundaries, though the former is arguably more accurate in some regimes due to its incorporation of quantum jumps. However, these frameworks predominantly focus on weak Markovian interactions, neglecting the potentially cruc

Fan Zhou, Vincent Vandeghinste

Machine translation (MT) encompasses a variety of methodologies aimed at enhancing the accuracy of translations. In contrast, the process of human-generated translation relies on a wide range of translation techniques, which are crucial for ensuring linguistic adequacy and fluency. This study suggests that these translation techniques could further optimize

Hakim Boumaza, Olivier Lafitte

In this article we present comparisons between the spectrum of a one-dimensional Schr\"odinger operator for a particular periodic potential and for its restriction to a finite number of sites. We deduce from this finite, but large, number of sites, the Integrated Density of States (IDS) associated to the Hamiltonian operator whose derivate is the DOS. The ex

Michael Gorczyca, Justice Sefas

Studies in circadian biology often use trigonometric regression to model phenomena over time. Ideally, protocols in these studies would collect samples at evenly distributed and equally spaced time points over a 24 hour period. This sample collection protocol is known as an equispaced design, which is considered the optimal experimental design for trigonomet

Inder Tecuapetla-Gómez, Francisco Rosales-Marticorena, Berenice Fanny Galicia-Gómez

Vegetation phenology consists of studying synchronous stationary events, such as the vegetation green up and leaves senescence, that can be construed as adaptive responses to climatic constraints. In this paper, we propose a method to estimate the annual phenology curve from multi-annual observations of time series of vegetation indices derived from satellit

Bo-Yu Yang, Hsuan Yu, Hao-Chung Cheng

In this work, maximal $\alpha$-leakage is introduced to quantify how much a quantum adversary can learn about any sensitive information of data upon observing its disturbed version via a quantum privacy mechanism. We first show that an adversary's maximal expected $\alpha$-gain using optimal measurement is characterized by measured conditional R\'enyi entrop

Haiwei Dong, Yang Liu, Ted Chu, Abdulmotaleb El Saddik

On March 18, 2024, NVIDIA unveiled Project GR00T, a general-purpose multimodal generative AI model designed specifically for training humanoid robots. Preceding this event, Tesla's unveiling of the Optimus Gen 2 humanoid robot on December 12, 2023, underscored the profound impact robotics is poised to have on reshaping various facets of our daily lives. Whil