February 2024 arXiv papers — page 163

Cédric Lemieux-Leduc, Mahmoud R. M. Atalla, Simone Assali, Sebastian Koelling

Due to their narrow band gap and compatibility with silicon processing, germanium-tin (Ge$_{1-x}$Sn$_x$) alloys are a versatile platform for scalable integrated mid-infrared photonics. These semiconductors are typically grown on silicon wafers using Ge as an interlayer. However, the large lattice mismatch in this heteroepitaxy protocol leads to the build-up

S. Stoynev, G. Ambrosio, K. Amm, J. DiMarco

The high-luminosity LHC upgrade requires stronger than LHC low-beta quadrupole magnets to reach the luminosity goals of the project. The project is well advanced and HL-LHC quadrupole magnets are currently being commissioned in US Labs (MQXFA magnets) and CERN (MQXFB magnets). Those are the first Nb3Sn magnets to be used in any large particle accelerator. At

Anastasis Kratsios, Haitz Sáez de Ocáriz Borde, Takashi Furuya, Marc T. Law

Mixture-of-Experts (MoEs) can scale up beyond traditional deep learning models by employing a routing strategy in which each input is processed by a single "expert" deep learning model. This strategy allows us to scale up the number of parameters defining the MoE while maintaining sparse activation, i.e., MoEs only load a small number of their total paramete

Matthew Hofkes, Douglas Nychka, Tzahi Cath, Amanda Hering

Many industrial and engineering processes monitored as times series have smooth trends that indicate normal behavior and occasionally anomalous patterns that can indicate a problem. This kind of behavior can be modeled by a smooth trend, such as a spline or Gaussian process, and a disruption based on a sparser representation. Our approach is to expand the pr

María de los Santos Bruzón, Rafael de la Rosa, Rita Tracinà

In this paper, a family of variable-coefficient fifth-order KdV equations has been considered. By using an infinitesimal method based on the determination of the equivalence group, differential invariants and invariant equations are obtained. Invariants provide an alternative way to find equations from the family which may be equivalent to a specific subclas

Yasin Yousif, Jörg Müller

Developing accurate models for traffic trajectory predictions is crucial for achieving fully autonomous driving. Various deep neural network models have been employed to address this challenge, but their black-box nature hinders transparency and debugging capabilities in a deployed system. Glass-box models offer a solution by providing full interpretability

Siyuan Dai, Kai Ye, Kun Zhao, Ge Cui

Representation learning constitutes a pivotal cornerstone in contemporary deep learning paradigms, offering a conduit to elucidate distinctive features within the latent space and interpret the deep models. Nevertheless, the inherent complexity of anatomical patterns and the random nature of lesion distribution in medical image segmentation pose significant

Bertrand Marchand, Yoann Anselmetti, Manuel Lafond, Aïda Ouangraoua

Motivation: Non-coding RNAs (ncRNAs) express their functions by adopting molecular structures. Specifically, RNA secondary structures serve as a relatively stable intermediate step before tertiary structures, offering a reliable signature of molecular function. Consequently, within an RNA functional family, secondary structures are generally more evolutionar

K. Fleck, T. Blackburn, E. Gerstmayr, M. Bruschi

Inverse Compton scattering of an ultra-relativistic electron in the field of a high-intensity laser produces photon beams with angular and spectral distributions that are strongly dependent on the laser intensity. Here, we show that the laser intensity at the interaction point can be accurately inferred from the measurement of the angular number-density dist

Renata Kallosh

We introduce Ward identities for superamplitudes in D-dimensional N-extended supergravities. These identities help to clarify the relation between linearized superinvariants and superamplitudes. The solutions of these Ward identities for an $n$-partice superamplitude take a simple universal form for half-BPS and non-BPS amplitudes. These solutions involve ar

Lucile Soumah, Louise Desplat, Nhat-Tan Phan, Ahmed Sidi El Valli

We demonstrate a good agreement between mean dwell times measured in 50~nm diameter, perpendicularly magnetized superparamagnetic tunnel junctions (SMTJ), and theoretical predictions based on Langer's theory. Due to a large entropic contribution, the theory yields Arrhenius prefactors in the femtosecond range for the measured junctions, in stark contrast to

Alejandra Gaitan, Victor Lie

Building on arXiv:1902.03807, this paper develops a unifying study on the boundedness properties of several representative classes of hybrid operators, i.e. operators that enjoy both zero and non-zero curvature features. Specifically, via the LGC-method, we provide suitable $L^p$ bounds for three classes of operators: (1) Carleson-type operators, (2) Hilbert

Meng Cao, Hussain Hussain, Sandipan Sikdar, Denis Helic

In social recommender systems, it is crucial that the recommendation models provide equitable visibility for different demographic groups, such as gender or race. Most existing research has addressed this problem by only studying individual static snapshots of networks that typically change over time. To address this gap, we study the evolution of recommenda

Wenjie Liu, Panos Papadimitratos

GNSS are indispensable for various applications, but they are vulnerable to spoofing attacks. The original receiver autonomous integrity monitoring (RAIM) was not designed for securing GNSS. In this context, RAIM was extended with wireless signals, termed signals of opportunity (SOPs), or onboard sensors, typically assumed benign. However, attackers might al

Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis, Seyyedali Hosseinalipour

Decentralized federated learning (DFL) captures FL settings where both (i) model updates and (ii) model aggregations are exclusively carried out by the clients without a central server. Existing DFL works have mostly focused on settings where clients conduct a fixed number of local updates between local model exchanges, overlooking heterogeneity and dynamics

Annie Liang, Thomas Jemielita, Andy Liaw, Vladimir Svetnik

Variable importance plays a pivotal role in interpretable machine learning as it helps measure the impact of factors on the output of the prediction model. Model agnostic methods based on the generation of "null" features via permutation (or related approaches) can be applied. Such analysis is often utilized in pharmaceutical applications due to its ability

Michele Fossati, Filiberto Ares, Jerome Dubail, Pasquale Calabrese

The entanglement asymmetry is an information based observable that quantifies the degree of symmetry breaking in a region of an extended quantum system. We investigate this measure in the ground state of one dimensional critical systems described by a CFT. Employing the correspondence between global symmetries and defects, the analysis of the entanglement as

Titas Anciukevičius, Fabian Manhardt, Federico Tombari, Paul Henderson

Generating 3D scenes is a challenging open problem, which requires synthesizing plausible content that is fully consistent in 3D space. While recent methods such as neural radiance fields excel at view synthesis and 3D reconstruction, they cannot synthesize plausible details in unobserved regions since they lack a generative capability. Conversely, existing

Matt Larson

We give elementary and non-inductive proofs of three fundamental theorems about Chow rings of matroids: the standard monomial basis, Poincare duality, and the dragon-Hall-Rado formula. Our approach, which also works for augmented Chow rings of matroids, is based on a straightening law. This approach also gives a decomposition of the Chow ring of a matroid in

K. Szekerczes, T. Ryu, S. H. Suyu, S. Huber

Tidal disruption events (TDEs) are multi-messenger transients in which a star is tidally destroyed by a supermassive black hole at the center of galaxies. The Rubin Observatory Legacy Survey of Space and Time (LSST) is anticipated to annually detect hundreds to thousands of TDEs, such that the first gravitationally lensed TDE may be observed in the coming ye

Aayush Vijayvargia, Onur Erten

Motivated by the recent discovery of magnetism and heavy quasiparticles in van der Waals material CeSiI, we develop an effective model that incorporates the conduction electrons residing at the silicene layer interacting with the local moments of the Ce ions. Ce sites are arranged on two layers of triangular lattices, above and below the silicene layer, and

Stephen R. Kane, Robert A. Wittenmyer

A fundamental question in the study of planetary system demographics is: how common is the solar system architecture? The primary importance of this question lies in the potential of planetary systems to create habitable environments, and dissecting the various components of solar system evolution that contributed to a sustainable temperate surface for Earth

Jaime de la Cruz Rodríguez, Jorrit Leenaarts

Determination of solar magnetic fields with a spatial resolution set by the diffraction limit of a telescope is difficult because the time required to measure the Stokes vector with sufficient signal-to-noise is long compared to the solar evolution timescale. This difficulty gets worse with increasing telescope size as the photon flux per diffraction-limited

Yifan Zhang, Sarang Gopalakrishnan

Local measurements cannot create entanglement, but they can convert short-range entanglement to long-range entanglement, as in quantum teleportation. This phenomenon of measurement-induced entanglement (MIE) has been widely discussed in recent work on measurement-induced entanglement phase transitions and related phenomena. Here, we situate MIE in a broader

Gabriela Barenboim, Alberto M. Gago

Physical systems in real life are inextricably linked to their surroundings and never completely separated from them. Truly closed systems do not exist. The phenomenon of decoherence, which is brought about by the interaction with the environment, removes the relative phase of quantum states in superposition and makes them incoherent. In neutrino physics, de

Michael Gekhtman, Hugh Thomas

Generalized associahedra are a well-studied family of polytopes associated to a finite-type cluster algebra and choice of starting cluster. We show that the generalized associahedra constructed by Padrol, Palu, Pilaud, and Plamondon, building on ideas from Arkani-Hamed, Bai, He, and Yan, can be naturally viewed as moment polytopes for an open patch of the qu

Euclid Collaboration, L. Scharré, M. Hirschmann, G. De Lucia

In anticipation of the Euclid Wide and Deep Surveys, we present optical emission-line predictions at intermediate redshifts from 0.4 to 2.5. Our approach combines a mock light cone from the GAEA semi-analytic model to self-consistently model nebular emission from HII regions, narrow-line regions of active galactic nuclei (AGN), and evolved stellar population

Sergi Blanco-Cuaresma

This study explores the use of Large Language Models (LLMs) to analyze text comments from Reddit users, aiming to achieve two primary objectives: firstly, to pinpoint critical excerpts that support a predefined psychological assessment of suicidal risk; and secondly, to summarize the material to substantiate the preassigned suicidal risk level. The work is c

Lewis Sword, David Vegh

We show that for a particular model, the quantum mechanical bootstrap is capable of finding exact results. We consider a solvable system with Hamiltonian $H=SZ(1-Z)S$, where $Z$ and $S$ satisfy canonical commutation relations. While this model may appear unusual, using an appropriate coordinate transformation, the Schr\"odinger equation can be cast into a st

Xie Chen, Michael Hermele, David T. Stephen

In previous work, it was shown that non-trivial gapped states can be generated from a product state using a sequential quantum circuit. Explicit circuit constructions were given for a variety of gapped states at exactly solvable fixed points. In this paper, we show that a similar generation procedure can be established for chiral topological states as well,

Yanjie Zeng, Yuxin Liu, Chunlong Li, Yuxiang Liu

Dark photons, as a minimal extension of the Standard Model through an additional Abelian gauge group, may propagate relativistically across the galaxy, originating from dark matter decay or annihilation, thereby contributing to a galactic dark photon background. The generation of dark photons typically favors certain polarization modes, which are dependent o

Yohei Ema, Maxim Pospelov, Anupam Ray

Strongly-interacting dark matter can be accumulated in large quantities inside the Earth, and for dark matter particles in a few GeV mass range, it can exist in large quantities near the Earth's surface. We investigate the constraints imposed on such dark matter properties by its upscattering by fast neutrons in nuclear reactors with subsequent scattering in

Simon Rozier, Raphaël Errani

Placed slightly out of dynamical equilibrium, an isolated stellar system quickly returns towards a steady virialized state. We study this process of collisionless relaxation using the matrix method of linear response theory. We show that the full phase space distribution of the final virialized state can be recovered directly from the disequilibrium initial

Stephane Ouvry, Alexios P. Polychronakos

We present the microscopic formulation of inclusion statistics, a counterpoint to exclusion statistics in which particles tend to coalesce more than ordinary bosons. We derive the microscopic occupation multiplicities of 1-body quantum states and show that they factorize into a product of clusters of neighbouring occupied states with enhanced statistical wei

Devesh Nandal, John A. Regan, Tyrone E. Woods, Eoin Farrell

The chemical enrichment of the early Universe is a crucial element in the formation and evolution of galaxies, and Population III (PopIII) stars must play a vital role in this process. In this study, we examine metal enrichment from massive stars in the early Universe's embryonic galaxies. Using radiation hydrodynamic simulations and stellar evolution modell

Santiago Sanz-Wuhl, Héctor Gil-Marín, Antonio J. Cuesta, Licia Verde

We study the impact of the assumption of a non-flat fiducial cosmology on the measurement, analysis and interpretation of BAO distance variables, along and across the line-of-sight. The assumption about cosmology enters in the choice of the base template, as well as on the transformation of tracer's redshifts into distances (the catalog cosmology): here we f

David I. Dunsky, Marius Kongsore

The QCD axion can solve the Strong CP Problem and be the dark matter of our universe. If the PQ symmetry breaking scale associated with the axion is below the inflationary reheating temperature, axion strings and domain walls populate the universe. Most of these strings and walls decay away into axion dark matter, but a small subset of the walls will be self

Netta Engelhardt, Åsmund Folkestad, Adam Levine, Evita Verheijden

We formulate and take two large strides towards proving a quantum version of the weak cosmic censorship conjecture. We first prove "Cryptographic Censorship": a theorem showing that when the time evolution operator of a holographic CFT is approximately pseudorandom (or Haar random) on some code subspace, then there must be an event horizon in the correspondi

Simone Giacomelli, William Harding, Noppadol Mekareeya, Alessandro Mininno

Discrete global symmetries of 4d $\mathcal{N}=2$ SCFTs are studied via two operations: gauging and twisted compactification. We consider gauging of discrete symmetries in several well-known 4d $\mathcal{N}=2$ SCFTs, including $\mathrm{SU}(n)$ SQCD with $2n$ flavors, theories of class $\mathcal{S}$ of type $A_{2n-1}$, and Argyres--Douglas theories of type $(A

Charles L. Steinhardt

A new model is proposed in which typical galaxies form most of their stellar mass in a phase with an intrinsically red stellar population. In the standard picture, galaxies with intrinsically red stellar populations are believed to have old stellar populations, so that only galaxies with blue stellar populations have significant star formation, and subsequen

Saverio Cambioni, Katherine de Kleer, Michael Shepard

Main-belt asteroid (16) Psyche is the largest M-type asteroid, a class of object classically thought to be the metal cores of differentiated planetesimals and the parent bodies of the iron meteorites. de Kleer, Cambioni, and Shepard (2021, https://doi.org/10.3847/psj/ac01ec) presented new data from the Atacama Large Millimeter Array (ALMA), from which they d

Leonardo Badurina, Clara Murgui, Ryan Plestid

We study the decoherence of a system of $N$ non-interacting heavy particles (atoms) due to coherent scattering with a background gas. We introduce a framework for computing the induced phase shift and loss of contrast for arbitrary preparations of $N$-particle quantum states. We find phase shifts that are inherently $(N\geq 2)$-body effects and may be search

Ramona Augustin, Céline Péroux, Arjun Karki, Varsha Kulkarni

The physical processes by which gas is accreted onto galaxies, transformed into stars and then expelled from galaxies are of paramount importance to galaxy evolution studies. Observationally constraining each of these baryonic components in the same systems however, is challenging. Furthermore, simulations indicate that the stellar mass of galaxies is a key

Iryna S. Butsky, Cameron B. Hummels, Philip F. Hopkins, Thomas R. Quinn

The cold ($\sim 10^{4}\,{\rm K}$) component of the circumgalactic medium (CGM) accounts for a significant fraction of all galactic baryons. However, using current galaxy-scale simulations to determine the origin and evolution of cold CGM gas poses a significant challenge, since it is computationally infeasible to directly simulate a galactic halo alongside t

Hyoungseob Park, Anjali Gupta, Alex Wong

It is common to observe performance degradation when transferring models trained on some (source) datasets to target testing data due to a domain gap between them. Existing methods for bridging this gap, such as domain adaptation (DA), may require the source data on which the model was trained (often not available), while others, i.e., source-free DA, requir

Shengcao Cao, Dhiraj Joshi, Liang-Yan Gui, Yu-Xiong Wang

The human visual perception system demonstrates exceptional capabilities in learning without explicit supervision and understanding the part-to-whole composition of objects. Drawing inspiration from these two abilities, we propose Hierarchical Adaptive Self-Supervised Object Detection (HASSOD), a novel approach that learns to detect objects and understand th

Jihan Yang, Runyu Ding, Ellis Brown, Xiaojuan Qi

There is a sensory gulf between the Earth that humans inhabit and the digital realms in which modern AI agents are created. To develop AI agents that can sense, think, and act as flexibly as humans in real-world settings, it is imperative to bridge the realism gap between the digital and physical worlds. How can we embody agents in an environment as rich and

Mohamad Qadri, Kevin Zhang, Akshay Hinduja, Michael Kaess

Underwater perception and 3D surface reconstruction are challenging problems with broad applications in construction, security, marine archaeology, and environmental monitoring. Treacherous operating conditions, fragile surroundings, and limited navigation control often dictate that submersibles restrict their range of motion and, thus, the baseline over whi

Mark N. Costantini, Elie Hammou, Zahari Kassabov, Maeve Madigan

We present the open-source SIMUnet code, designed to fit Standard Model Effective Field Theory (SMEFT) Wilson coefficient alongside Parton Distribution Functions (PDFs) of the proton. SIMUnet can perform SMEFT global fits, as well as simultaneous fits of the PDFs and of an arbitrarily large number of SMEFT degrees of freedom, by including both PDF-dependent

Yuanxing Duan, Fangyin Wei, Qiyu Dai, Yuhang He

We consider the problem of novel-view synthesis (NVS) for dynamic scenes. Recent neural approaches have accomplished exceptional NVS results for static 3D scenes, but extensions to 4D time-varying scenes remain non-trivial. Prior efforts often encode dynamics by learning a canonical space plus implicit or explicit deformation fields, which struggle in challe

Pacôme Perrotin, Eurico Ruivo, Pedro Paulo Balbi

We present a family of automata networks that solve the k-parity problem when run in parallel. These solutions are constructed by connecting cliques in a non-cyclical fashion. The size of the local neighbourhood is linear in the size of the alphabet, and the convergence time is proven to always be the diameter of the interaction graph. We show that this fami

Qiyao Liang, Ziming Liu, Ila Fiete

Diffusion models are capable of impressive feats of image generation with uncommon juxtapositions such as astronauts riding horses on the moon with properly placed shadows. These outputs indicate the ability to perform compositional generalization, but how do the models do so? We perform controlled experiments on conditional DDPMs learning to generate 2D sph

Heather Macbeth

We prove an $L^2$ estimate for the drift heat equation on a complete gradient shrinking Ricci soliton. This estimate has a time-dependent weight which is Gaussian in its spatial asymptotics. When transferred and scaled to an estimate for the heat equation along the Ricci flow of the soliton, this estimate is uniform up to the singular time.

Edward Kim

Given the impressive capabilities of recent Large Language Models (LLMs), we investigate and benchmark the most popular proprietary and different sized open source models on the task of explicit instruction following in conflicting situations, e.g. overrides. These include the ability of the model to override the knowledge within the weights of the model, th

Jiarun Liu, Hao Yang, Hong-Yu Zhou, Yan Xi

Accurate medical image segmentation demands the integration of multi-scale information, spanning from local features to global dependencies. However, it is challenging for existing methods to model long-range global information, where convolutional neural networks (CNNs) are constrained by their local receptive fields, and vision transformers (ViTs) suffer f

Bakul Agarwal, Gudrun Heinrich, Stephen P. Jones, Matthias Kerner

We present numerical results for the two-loop virtual amplitude entering the NNLO corrections to Higgs boson production in association with a top quark pair at the LHC, focusing, as a proof of concept of our method, on the part of the quark-initiated channel containing loops of massless or massive quarks. Results for the UV renormalised and IR subtracted two

Rafael de la Rosa, María Luz Gandarias, María de los Santos Bruzón

In this work we study a generalized variable-coefficient Gardner equation from the point of view of Lie symmetries in partial differential equations. We find conservation laws by using the multipliers method of Anco and Bluman which does not require the use of a variational principle. We also construct conservation laws using Ibragimov theorem which is based

Yuancheng Xu, Jiarui Yao, Manli Shu, Yanchao Sun

Vision-Language Models (VLMs) excel in generating textual responses from visual inputs, but their versatility raises security concerns. This study takes the first step in exposing VLMs' susceptibility to data poisoning attacks that can manipulate responses to innocuous, everyday prompts. We introduce Shadowcast, a stealthy data poisoning attack where poison

Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu

Mathematical reasoning poses a significant challenge for language models due to its complex and structured nature. In this paper, we introduce DeepSeekMath 7B, which continues pre-training DeepSeek-Coder-Base-v1.5 7B with 120B math-related tokens sourced from Common Crawl, together with natural language and code data. DeepSeekMath 7B has achieved an impressi

Haibo Jin, Ruoxi Chen, Peiyan Zhang, Andy Zhou

The discovery of "jailbreaks" to bypass safety filters of Large Language Models (LLMs) and harmful responses have encouraged the community to implement safety measures. One major safety measure is to proactively test the LLMs with jailbreaks prior to the release. Therefore, such testing will require a method that can generate jailbreaks massively and efficie

Michał A. Borysiewicz, Patrycja Barańczyk, Aleksandra Wójcicka, Jakub Zawadzki

Magnesium nanostructures find increased use in applications for hydrogen storage, catalysis, waste treatment, and heat storage to name a few. Currently, most nanoparticles are made using a chemical synthesis approach, necessitating the use of organic solvents and yielding material covered in ligands. To apply these nanoparticles, one has to use them in paint

Yiming Chen, Sameer Murthy, Gustavo J. Turiaci

The fundamental heterotic string has a tower of BPS states whose supersymmetric index has an exponential growth in the charges. We construct the saddle-point of the gravitational path integral corresponding to this index. The saddle-point configuration is a supersymmetric rotating non-extremal Euclidean black hole. This configuration is singular in the two-d

Murad Hasan, Shahriar Iqbal, Md. Billal Hossain Faisal, Md. Musnad Hossin Neloy

Criminal and suspicious activity detection has become a popular research topic in recent years. The rapid growth of computer vision technologies has had a crucial impact on solving this issue. However, physical stalking detection is still a less explored area despite the evolution of modern technology. Nowadays, stalking in public places has become a common

Sebastian Haney

We construct a Lagrangian in the cotangent bundle of a 3-torus whose projection to the fiber is a neighborhood of a tropical curve with a single 4-valent vertex. This Lagrangian has an isolated conical singular point, and its smooth locus is diffeomorphic to the minimally-twisted five component chain link complement, a cusped hyperbolic 3-manifold. From this

Yongchang Hao, Yanshuai Cao, Lili Mou

Second-order optimization approaches like the generalized Gauss-Newton method are considered more powerful as they utilize the curvature information of the objective function with preconditioning matrices. Albeit offering tempting theoretical benefits, they are not easily applicable to modern deep learning. The major reason is due to the quadratic memory and

Kaifei Kang, Bowen Shen, Yichen Qiu, Kenji Watanabe

Quantum spin Hall (QSH) insulators are two-dimensional electronic materials that have a bulk band gap like an ordinary insulator but have topologically protected pairs of edge modes of opposite chiralities. To date, experimental studies have found only integer QSH insulators with counter-propagating up-spins and down-spins at each edge leading to a quantized

Yongchang Hao, Yanshuai Cao, Lili Mou

Despite large neural networks demonstrating remarkable abilities to complete different tasks, they require excessive memory usage to store the optimization states for training. To alleviate this, the low-rank adaptation (LoRA) is proposed to reduce the optimization states by training fewer parameters. However, LoRA restricts overall weight update matrices to

Quang-Huy Nguyen, Jin Peng Zhou, Zhenzhen Liu, Khanh-Huyen Bui

Recent object detectors have achieved impressive accuracy in identifying objects seen during training. However, real-world deployment often introduces novel and unexpected objects, referred to as out-of-distribution (OOD) objects, posing significant challenges to model trustworthiness. Modern object detectors are typically overconfident, making it unreliable

Jilang Miao, Miaomiao Jin

We provide details in understanding the Watt spectrum sampling method. The algorithm is given in "R12" from "3rd Monte Carlo Sampler" without detailed derivation. We rederive the algorithm by optimizating the sampling efficiency of the rejection method.

Sajjadur Rahman, Frederick Choi, Hannah Kim, Dan Zhang

Constructing and serving knowledge graphs (KGs) is an iterative and human-centered process involving on-demand programming and analysis. In this paper, we present Kyurem, a programmable and interactive widget library that facilitates human-in-the-loop knowledge acquisition and integration to enable continuous curation a knowledge graph (KG). Kyurem provides

Xudong Wang, Trevor Darrell, Sai Saketh Rambhatla, Rohit Girdhar

Text-to-image diffusion models produce high quality images but do not offer control over individual instances in the image. We introduce InstanceDiffusion that adds precise instance-level control to text-to-image diffusion models. InstanceDiffusion supports free-form language conditions per instance and allows flexible ways to specify instance locations such

Vincent Russo, Andrea Mari

A widely used method for mitigating errors in noisy quantum computers is Richardson extrapolation, a technique in which the overall effect of noise on the estimation of quantum expectation values is captured by a single parameter that, after being scaled to larger values, is eventually extrapolated to the zero-noise limit. We generalize this approach by intr

Matthew DeLorenzo, Animesh Basak Chowdhury, Vasudev Gohil, Shailja Thakur

Existing large language models (LLMs) for register transfer level code generation face challenges like compilation failures and suboptimal power, performance, and area (PPA) efficiency. This is due to the lack of PPA awareness in conventional transformer decoding algorithms. In response, we present an automated transformer decoding algorithm that integrates

Matías Gámez-Marín, Isabel Santos-Santos, Rosa Domínguez Tenreiro, Susana E. Pedrosa

Kinematically-persistent planes of satellites (KPPs) are fixed sets of satellites co-orbiting around their host galaxy, whose orbital poles are conserved and clustered across long cosmic time intervals. They play the role of 'skeletons', ensuring the long-term durability of positional planes. We explore the physical processes behind their formation in terms

Mulun Na, Jonathan Klein, Biao Zhang, Wojtek Pałubicki

We introduce the Lennard-Jones layer (LJL) for the equalization of the density of 2D and 3D point clouds through systematically rearranging points without destroying their overall structure (distribution normalization). LJL simulates a dissipative process of repulsive and weakly attractive interactions between individual points by considering the nearest nei

Yoad Tewel, Omri Kaduri, Rinon Gal, Yoni Kasten

Text-to-image models offer a new level of creative flexibility by allowing users to guide the image generation process through natural language. However, using these models to consistently portray the same subject across diverse prompts remains challenging. Existing approaches fine-tune the model to teach it new words that describe specific user-provided sub

Tiago Domingues, Ronald Coifman, Amir Haji-Akbari

Confinement can substantially alter the physicochemical properties of materials by breaking translational isotropy and rendering all physical properties position-dependent. Molecular dynamics (MD) simulations have proven instrumental in characterizing such spatial heterogeneities and probing the impact of confinement on materials' properties. For static prop

Anthony Sicilia, Hyunwoo Kim, Khyathi Raghavi Chandu, Malihe Alikhani

Effective interlocutors account for the uncertain goals, beliefs, and emotions of others. But even the best human conversationalist cannot perfectly anticipate the trajectory of a dialogue. How well can language models represent inherent uncertainty in conversations? We propose FortUne Dial, an expansion of the long-standing "conversation forecasting" task:

Rohit Verma, Arun Raghunath

There is growing interest in visual data management systems that support queries with specialized operations ranging from resizing an image to running complex machine learning models. With a plethora of such operations, the basic need to receive query responses in minimal time takes a hit, especially when the client desires to run multiple such operations in

Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano, Ambuj Tewari

The growing deployment of reinforcement learning from human feedback (RLHF) calls for a deeper theoretical investigation of its underlying models. The prevalent models of RLHF do not account for neuroscience-backed, partially-observed "internal states" that can affect human feedback, nor do they accommodate intermediate feedback during an interaction. Both o

Leonard Kreutz, Bernd Schmidt

In this short note we review results on equilibrium shapes of minimizers to the sessile drop problem. More precisely, we study the Winterbottom problem and prove that the Winterbottom shape is indeed optimal. The arguments presented here are based on relaxation and the (anisotropic) isoperimetric inequality.

José Calos García-Marino, Carmen Calvo-Jurado, Enrique García-Macías

Surrogate modelling techniques have opened up new possibilities to overcome the limitations of computationally intensive numerical models in various areas of engineering and science. However, while fundamental in many engineering applications and decision-making, the incorporation of uncertainty quantification into meta-models remains a challenging open area

Mohan, Bhuwanesh Rao Patil, Ram Krishna Pandey

Let $A$ be a set of natural numbers. A set $B$, a set of natural numbers, is said to be an additive complement of the set $A$ if all sufficiently large natural numbers can be represented in the form $x+y$, where $x\in A$ and $y\in B$. This article describes various types of additive complements of the set $A$ such as those additive complement of $A$ that doe

Tiffany D. Do, Camille Isabella Protko, Ryan P. McMahan

In many consumer virtual reality (VR) applications, users embody predefined characters that offer minimal customization options, frequently emphasizing storytelling over user choice. We explore whether matching a user's physical characteristics, specifically ethnicity and gender, with their virtual self-avatar affects their sense of embodiment in VR. We cond

Damien Calaque, Giovanni Felder, Gabriele Rembado, Richard Wentworth

We study truncated gauge-orbits through principal parts of irregular-singular connection germs, in the untwisted/unramified setting: for any connected complex reductive structure group $G$, in the general multilevel case. In particular, we compute the stabilisers of the formal normal forms using filtrations of Levi root systems, showing that they are connect

Luyi Ma, Nimesh Sinha, Parth Vajge, Jason HD Cho

Many current recommender systems mainly focus on the product-to-product recommendations and user-to-product recommendations even during the time of events rather than modeling the typical recommendations for the target event (e.g., festivals, seasonal activities, or social activities) without addressing the multiple aspects of the shopping demands for the ta

Manuel Inselmann

Define the map $\mathsf{T}$ on the positive integers by $\mathsf{T}(m)=\frac{m}{2}$ if $m$ is even and by $\mathsf{T}(m)=\frac{3m+1}{2}$ if $m$ is odd. Results of Terras and Everett imply that, given any $\epsilon>0$, almost all $m\in\mathbb{Z}^+$ (in the sense of natural density) fulfill $(\frac{\sqrt{3}}{2})^km^{1-\epsilon}\leq \mathsf{T}^k(m)\leq (\frac{\

Lorenzo Mercuri, Andrea Perchiazzo, Edit Rroji

This paper presents an algorithm for the simulation of Hawkes-type processes where the intensity is expressed in terms of a continuous-time autoregressive moving average model. We identify upper bounds for both the univariate and the multivariate intensity functions that are used to develop simulation algorithms based on the thinning technique.

Sandra Kiefer, Daniel Neuen

The Weisfeiler-Leman (WL) dimension is an established measure for the inherent descriptive complexity of graphs and relational structures. It corresponds to the number of variables that are needed and sufficient to define the object of interest in a counting version of first-order logic (FO). These bounded-variable counting logics were even candidates to cap

Konrad K. Dabrowski, Peter Jonsson, Sebastian Ordyniak, George Osipov

Difference Logic (DL) is a fragment of linear arithmetics where atoms are constraints x+k <= y for variables x,y (ranging over Q or Z) and integer k. We study the complexity of deciding the truth of existential DL sentences. This problem appears in many contexts: examples include verification, bioinformatics, telecommunications, and spatio-temporal reasoning

Francisco Silva-Santos, Ruben da Silva, Yuset Guerra Dávila, Maykol Oliveira

In the present work, Raman and photoluminescence spectroscopies were used to study the dynamics of phonons and different excitons of MoS$_2$ bilayer under a rotation of 29$^{\circ}$ dependent of the temperature. The twisted bilayer (T-2L) of MoS$_2$ was obtained through mechanical exfoliation, and subsequently rotated using a dimethyl polysiloxane (PDMS) sub

Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao

In the face of uncertainty, the ability to *seek information* is of fundamental importance. In many practical applications, such as medical diagnosis and troubleshooting, the information needed to solve the task is not initially given and has to be actively sought by asking follow-up questions (for example, a doctor asking a patient for more details about th

Hector Alaiz-Moreton, Jose Aveleira-Mata, Jorge Ondicol-Garcia, Angel Luis Muñoz-Castañeda

The large number of sensors and actuators that make up the Internet of Things obliges these systems to use diverse technologies and protocols. This means that IoT networks are more heterogeneous than traditional networks. This gives rise to new challenges in cybersecurity to protect these systems and devices which are characterized by being connected continu

Masato Hagiwara, Marius Miron, Jen-Yu Liu

Traditionally, bioacoustics has relied on spectrograms and continuous, per-frame audio representations for the analysis of animal sounds, also serving as input to machine learning models. Meanwhile, the International Phonetic Alphabet (IPA) system has provided an interpretable, language-independent method for transcribing human speech sounds. In this paper,

Xinyi Wang, Alfonso Amayuelas, Kexun Zhang, Liangming Pan

Pre-trained language models (LMs) are able to perform complex reasoning without explicit fine-tuning. To understand how pre-training with a next-token prediction objective contributes to the emergence of such reasoning capability, we propose that we can view an LM as deriving new conclusions by aggregating indirect reasoning paths seen at pre-training time.

Svyatoslav M. Novikov

Given a Gaussian risk process $R(t)=u+c(t)-X(t),t\ge 0$, the cumulative Parisian ruin probability on a finite time interval $[0,T]$ with respect to $L \geq 0$ is defined as the probability that the sojourn time that the risk process $R$ spends under the level 0 on this time interval $[0,T]$ exceeds $L$. In this contribution we derive exact asymptotic approxi

Igor Bogush, Kirill Kobialko, Dmitri Gal'tsov

The procedure for constructing the massive particle surfaces in static space-times is described in detail and the equivalence of the main results with the results of the geodesic approach is demonstrated.

Rafael de la Rosa, María Luz Gandarias, María de los Santos Bruzón

A fifth-order KdV equation with time dependent coefficients and linear damping has been studied. Symmetry groups have several different applications in the context of nonlinear differential equations. For instance, they can be used to determine conservation laws. We obtain the symmetries of the model applying Lie's classical method. The choice of some arbitr

Ammar Haydari, Dongjie Chen, Zhengfeng Lai, Michael Zhang

Generative models have shown promising results in capturing human mobility characteristics and generating synthetic trajectories. However, it remains challenging to ensure that the generated geospatial mobility data is semantically realistic, including consistent location sequences, and reflects real-world characteristics, such as constraining on geospatial

Grayson W. White, Josh K. Yamamoto, Dinan H. Elsyad, Julian F. Schmitt

The United States (US) Forest Inventory & Analysis Program (FIA) collects data on and monitors the trends of forests in the US. FIA is increasingly interested in monitoring forest attributes such as biomass at fine geographic and temporal scales, resulting in a need for assessment and development of small area estimation techniques in forest inventory. We im