May 2024 arXiv papers — page 102

Sohail Reddy, Hillary Fairbanks

This work presents an efficient approach for accelerating multilevel Markov Chain Monte Carlo (MCMC) sampling for large-scale problems using low-fidelity machine learning models. While conventional techniques for large-scale Bayesian inference often substitute computationally expensive high-fidelity models with machine learning models, thereby introducing ap

Sichang Tu, Abigail Powers, Natalie Merrill, Negar Fani

The shortage of clinical workforce presents significant challenges in mental healthcare, limiting access to formal diagnostics and services. We aim to tackle this shortage by integrating a customized large language model (LLM) into the workflow, thus promoting equity in mental healthcare for the general population. Although LLMs have showcased their capabili

Hitoshi Konno, Kazuyuki Oshima

We introduce a new elliptic quantum toroidal algebra U_{q,\kappa,p}(g_tor) associated with an arbitrary toroidal algebra g_tor. We show that U_{q,\kappa,p}(g_tor) contains two elliptic quantum algebras associated with a corresponding affine Lie algebra bg as subalgebras. They are analogue of the horizontal and the vertical subalgebras in the quantum toroidal

Hyungtae Lim

Despite the remarkable advancements in deep learning-based perception technologies and simultaneous localization and mapping (SLAM), one can face the failure of these approaches when robots encounter scenarios outside their modeled experiences (here, the term modeling encompasses both conventional pattern finding and data-driven approaches). In particular, b

Nagamani Poloji, Priya Hasan, S. N. Hasan

In an earlier paper, we determined the morphological types of galaxies in the Coma Cluster using data from the HST/ACS Coma Cluster treasury survey. We found that of the 132 members, 51 are non dwarfs and 81 are dwarfs. We define dwarfs to have a absolute luminosity $M_{F814W}\geq -18.5$ as in \cite{2012ApJ...746..136M}. In this paper, we determine the morph

Yi C. Huang, Ze Yang

In this article we derive an explicit diameter bound for graphs satisfying the so-called curvature dimension conditions $CD(K,n)$. This refines a recent result due to Liu, M\"unch and Peyerimhoff when the dimension $n$ is finite.

Toma Yoneya, Kazuya Fujimoto, Yuki Kawaguchi

The truncated Wigner approximation (TWA) enables us to investigate bosonic quantum many-body dynamics, including open quantum systems described by the Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) equation. In the TWA, the Weyl-Wigner transformation, a way of mapping from quantum-mechanical operators to $c$-numbers, of the GKSL equation leads to the Fokker-Pl

Xueyiming Tang, Steven J. Miller

Assuming the Generalized Riemann Hypothesis, the non-trivial zeros of $L$-functions lie on the critical line with the real part $1/2$. We find an upper bound of the lowest first zero in families of even cuspidal newforms of prime level tending to infinity. We obtain explicit bounds using the $n$-level densities and results towards the Katz-Sarnak density con

Jielei Zhang

Hyperon-nucleon interactions are important to understand quantum chromodynamics and so-called "hyperon puzzle" of neutron star, but limited by the availability and short-lifetime of hyperon beams, the progress of relevant research is very slow. A novel method is used to study hyperon-nucleon interactions based on hyperons produced in the decays of 10 billion

Han Qi, Guo Fei, Li Zhu

In this paper, we study the stochastic multi-armed bandit problem with graph feedback. Motivated by the clinical trials and recommendation problem, we assume that two arms are connected if and only if they are similar (i.e., their means are close enough). We establish a regret lower bound for this novel feedback structure and introduce two UCB-based algorith

Shingo Kukita, Haruki Kiya, Yasushi Kondo

Precise control of quantum systems is one of the most important milestones for achieving practical quantum technologies, such as computation, sensing, and communication. Several factors deteriorate the control precision and thus their suppression is strongly demanded. One of the dominant factors is systematic errors, which are caused by discord between an ex

Yao Xiao

We prove that the Lagrangian correspondences induced by the symplectic reduction maps at free zero level sets of the moment maps are unobstructed after bulk deformation, assuming the existence of certain equivariant Kuranishi structures and compatible equivariant CF-perturbations on the moduli spaces of pseudoholomorphic discs.

Alphonse Finel

We propose a new discrete FFT-based method for computational homogenization of micromechanics on a regular grid that is simple, fast and robust. The discretization scheme is based on a tetrahedral stencil that displays three crucial properties. First, and most importantly, the Fourier representation of the associated Green operator is defined for any finite

Rui Chen, Adrien Merlini, Francesco P. Andriulli

Surface integral equations (SIEs)-based boundary element methods are widely used for analyzing electromagnetic scattering scenarii. However, after discretization of SIEs, the spectrum and eigenvectors of the boundary element matrices are not usually representative of the spectrum and eigenfunctions of the underlying surface integral operators, which can be p

Takaaki Aoki, Kohei Nagamachi, Tetsuya Shimane

In declining and ageing societies, local communities face the `risk of eventual extinction.' In Japan, a population equivalent to that of an entire city is lost every year, representing one of the most severe cases of population decline. Thus, attracting young people has become a policy priority for many local municipalities in Japan, prompting the implement

Mengxi Zhang, Wenhao Wu, Yu Lu, Yuxin Song

Current multimodal Large Language Models (MLLMs) suffer from ``hallucination'', occasionally generating responses that are not grounded in the input images. To tackle this challenge, one promising path is to utilize reinforcement learning from human feedback (RLHF), which steers MLLMs towards learning superior responses while avoiding inferior ones. We rethi

Amarjit Soni

In the early 80's Sanda-san and collaborators wrote key papers on the direct and clean determination of the unitarity angle $\phi_1$ ($\beta$). This motivated many of us for analogously coming up with ways for direct and clean determinations of the other two unitarity angles, $\phi_2 (\alpha)$ and $\phi_3 (\gamma)$. Current status of these direct determinati

Zilin Liang, Zheng Zheng, Weihai Chen, Xinzhi Ma

The distribution shift of electroencephalography (EEG) data causes poor generalization of braincomputer interfaces (BCIs) in unseen domains. Some methods try to tackle this challenge by collecting a portion of user data for calibration. However, it is time-consuming, mentally fatiguing, and user-unfriendly. To achieve zerocalibration BCIs, most studies emplo

Yongrae Jo, Seongyun Lee, Minju Seo, Sung Ju Hwang

Text-to-SQL models are pivotal for making Electronic Health Records (EHRs) accessible to healthcare professionals without SQL knowledge. With the advancements in large language models, these systems have become more adept at translating complex questions into SQL queries. Nonetheless, the critical need for reliability in healthcare necessitates these models

Hosein Zarini, Amir Mohammadisarab, Maryam Farajzadeh Dehkordi, Mohammad Robat Mili

This paper centers around a multiple-input-multiple-output (MIMO) visible light communication (VLC) system, where an unmanned aerial vehicle (UAV) benefits from a light emitting diode (LED) array to serve photo-diode (PD)-equipped users for illumination and communication simultaneously. Concerning the battery limitation of the UAV and considerable energy con

Aniket Sanghi, Michael C. Liu, Trent J. Dupuy, William M. Best

We synthesize JWST NIRCam photometry for the F164N, F187N, F212N narrow filters, F140M, F162M, F182M, F210M medium filters, and F115W, F150W, F200W wide filters, Euclid Near Infrared Spectrometer and Photometer (NISP) photometry for the $Y_E J_E H_E$ filters, and Roman Wide Field Instrument (WFI) photometry for the F106, F129, F146, F158, F184 and F213 filte

Dong Seob Kim, Chengxin Xiao, Roy C. Dominguez, Zhida Liu

Semiconductor moir\'e systems, characterized by their periodic spatial light emission, unveil a new paradigm of active metasurfaces. Here, we show that ferroelectric moir\'e domains formed in a twisted hexagonal boron nitride (t-hBN) substrate can modulate light emission from an adjacent semiconductor MoSe$_2$ monolayer, enhancing its functionality as an act

Madhu Vankadari, Samuel Hodgson, Sangyun Shin, Kaichen Zhou Andrew Markham

Self-supervised depth estimation algorithms rely heavily on frame-warping relationships, exhibiting substantial performance degradation when applied in challenging circumstances, such as low-visibility and nighttime scenarios with varying illumination conditions. Addressing this challenge, we introduce an algorithm designed to achieve accurate self-supervise

Oleksiy Ostapenko, Zhan Su, Edoardo Maria Ponti, Laurent Charlin

The growing number of parameter-efficient adaptations of a base large language model (LLM) calls for studying whether we can reuse such trained adapters to improve performance for new tasks. We study how to best build a library of adapters given multi-task data and devise techniques for both zero-shot and supervised task generalization through routing in suc

Andrew T. Karl

We introduce a heuristic to test the significance of fit of Self-Validated Ensemble Models (SVEM) against the null hypothesis of a constant response. A SVEM model averages predictions from nBoot fits of a model, applied to fractionally weighted bootstraps of the target dataset. It tunes each fit on a validation copy of the training data, utilizing anti-corre

Dejin Ren, Zhen Liang, Chenyu Wu, Jianqiang Ding

Inner-approximate reachability analysis involves calculating subsets of reachable sets, known as inner-approximations. This analysis is crucial in the fields of dynamic systems analysis and control theory as it provides a reliable estimation of the set of states that a system can reach from given initial states at a specific time instant. In this paper, we s

Fan Yang, Mingxuan Xia, Sangzhou Xia, Chicheng Ma

Understanding the vulnerability of large-scale pre-trained vision-language models like CLIP against adversarial attacks is key to ensuring zero-shot generalization capacity on various downstream tasks. State-of-the-art defense mechanisms generally adopt prompt learning strategies for adversarial fine-tuning to improve the adversarial robustness of the pre-tr

Boyi Xue, Jintian Lin, Jiankun Hou, Yicheng Zhu

Perfect absorption of light critically affects light-matter interaction for various applications. Coherent perfect absorbers (CPA) gain the unique capability of controlling light with light in a linear fashion. Multi-color CPAs [Phys. Rev. Lett. 107, 033901] are highly desirable for broadband and nonlinear light-to-light coherent control, however, the experi

Michalis Anoussis, Alexandros Chatzinikolaou, Ivan G. Todorov

We introduce an operator system, universal for the probabilistic models of a contextuality scenario, and identify its maximal C*-cover via the right C*-algebra of a canonical ternary ring of operators, arising from a hypergraph version of stochastic operator matrices. We study dilating contextuality scenarios, which have the property that each positive opera

Xiaolu Kang, Zhuoqi Ma, Kang Liu, Yunan Li

Polyp segmentation for colonoscopy images is of vital importance in clinical practice. It can provide valuable information for colorectal cancer diagnosis and surgery. While existing methods have achieved relatively good performance, polyp segmentation still faces the following challenges: (1) Varying lighting conditions in colonoscopy and differences in pol

Jichao Zhang, Shangquan Bu

In this paper, we study the $\ell^p$-maximal regularity for the fractional difference equation with finite delay: \begin{equation*} \ \ \ \ \ \ \ \ \left\{\begin{array}{cc} \Delta^{\alpha}u(n)=Au(n)+\gamma u(n-\lambda)+f(n), \ n\in \mathbb N_0, \lambda \in \mathbb N, \gamma \in \mathbb R; u(i)=0,\ \ i=-\lambda, -\lambda+1,\cdots, 1, 2, \end{array} \right. \e

Zhelun Li, Lento Nagano, Koji Terashi

Recent developments in the field of quantum machine learning have promoted the idea of incorporating physical symmetries in the structure of quantum circuits. A crucial milestone in this area is the realization of $S_{n}$-permutation equivariant quantum neural networks (QNN) that are equivariant under permutations of input objects. In this work, we focus on

Edward W. Schwieterman, Thomas J. Fauchez, Jacob Haqq-Misra, Ravi K. Kopparapu

Atmospheric pollutants such as CFCs and NO$_{2}$ have been proposed as potential remotely detectable atmospheric technosignature gases. Here we investigate the potential for artificial greenhouse gases including CF$_{4}$, C$_{2}$F$_{6}$, C$_{3}$F$_{8}$, SF$_{6}$, and NF$_{3}$ to generate detectable atmospheric signatures. In contrast to passive incidental by

Min Hun Lee

In this paper, we explore the feasibility of using a transformer-based, spatiotemporal attention network (STAN) for gradient-based time-series explanations. First, we trained the STAN model for video classifications using the global and local views of data and weakly supervised labels on time-series data (i.e. the type of an activity). We then leveraged a gr

Timur Oikhberg, Mary Angelica Tursi

Suppose $X$ is a locally compact Polish space, and $G$ is a group of lattice isometries of $C_0(X)$ which satisfies certain conditions. Then we can equip $C_0(X)$ with an equivalent lattice norm $| \! | \! | \cdot | \! | \! |$ so that $G$ is the group of lattice isometries of $(C_0(X), | \! | \! | \cdot | \! | \! |)$. As an application, we show that for any

Yi C. Huang, Jian-Yang Zhang

In this paper we extend Galbis' elegant norm bounds for self-adjoint Toeplitz operators on the Fock space to bounded and integrable symbols which are non-radial. The main ingredients are a transplantation of the remarkable Nicola-Tilli isoperimetric inequality to the realm of Fock-Toeplitz operator theory and a two-dimensional adaption of Galbis' integration

Stephen Scarano, Vijayalakshmi Vasudevan, Mattia Samory, Kai-Cheng Yang

Social media platforms allow users to create polls to gather public opinion on diverse topics. However, we know little about what such polls are used for and how reliable they are, especially in significant contexts like elections. Focusing on the 2020 presidential elections in the U.S., this study shows that outcomes of election polls on Twitter deviate fro

Junzhang Liu, Zhecan Wang, Hammad Ayyubi, Haoxuan You

Despite the widespread adoption of Vision-Language Understanding (VLU) benchmarks such as VQA v2, OKVQA, A-OKVQA, GQA, VCR, SWAG, and VisualCOMET, our analysis reveals a pervasive issue affecting their integrity: these benchmarks contain samples where answers rely on assumptions unsupported by the provided context. Training models on such data foster biased

V. N. Krishnachandran

This paper examines what computational procedures \'Sankara Varman (1774-1839) and Sangamagrama M\=adhava (c. 1340 - 1425), astronomer-mathematicians of the Kerala school, might have used to arrive at their respective values for the circumferences of certain special circles (a circle of diameter $10^{17}$ by the former and a circle of diameter $9\times 10^{1

Klajdi Hoxha

How do consultants price expertise? This paper studies a problem of selling information products (expertise) to a buyer (client) who faces decision-making problem under uncertainty. The client is privately informed about the type of expertise she needs and her willingness to pay (WTP) for additional information. A monopolist seller (consultant) designs and s

Negin Ayoughi, Shiva Nejati, Mehrdad Sabetzadeh, Patricio Saavedra

Intrusion detection systems are crucial for network security. Verification of these systems is complicated by various factors, including the heterogeneity of network platforms and the continuously changing landscape of cyber threats. In this paper, we use automata learning to derive state machines from network-traffic data with the objective of supporting be

Cameron McGarry, Kerrianne Harrington, Alex O. C. Davis, Peter J. Mosley

Recent progress in the development and applications of microstructured optical fibres for quantum technologies is summarised. The optical nonlinearity of solid-core and gas-filled hollow-core fibres provides a valuable medium for the generation of quantum resource states, as well as for quantum frequency conversion between the operating wavelengths of existi

Jay Patrikar, Sushant Veer, Apoorva Sharma, Marco Pavone

Modern motion planners for autonomous driving frequently use imitation learning (IL) to draw from expert driving logs. Although IL benefits from its ability to glean nuanced and multi-modal human driving behaviors from large datasets, the resulting planners often struggle with out-of-distribution (OOD) scenarios and with traffic rule compliance. On the other

Taveesh Sharma, Paul Schmitt, Francesco Bronzino, Nick Feamster

Despite significant investments in access network infrastructure, universal access to high-quality Internet connectivity remains a challenge. Policymakers often rely on large-scale, crowdsourced measurement datasets to assess the distribution of access network performance across geographic areas. These decisions typically rest on the assumption that Internet

Shunsuke Tomioka

The Perron--Frobenius theorem in infinite-dimensional Hilbert spaces can be breifly stated as follows: Given a Hilbert cone in a real Hilbert space, a bounded positive self-adjoint operator $A$ is ergodic with respect to this cone if and only if the maximum eigenvalue $\|A\|$ of $A$ is simple, and the corresponding eigenvector is strictly positive with respe

Weitao Feng, Wenbo Zhou, Jiyan He, Jie Zhang

Diffusion models have achieved remarkable success in generating high-quality images. Recently, the open-source models represented by Stable Diffusion (SD) are thriving and are accessible for customization, giving rise to a vibrant community of creators and enthusiasts. However, the widespread availability of customized SD models has led to copyright concerns

V. N. Krishnachandran

This paper is intended to serve two purposes: one, to present an account of the life of Sangamagr\=ama M\=adhava, the founder of the Kerala school of astronomy and mathematics which flourished during the 15th - 18th centuries, based on modern historical scholarship and two, to present a critical study of the three enigmatic correction terms, attributed to M\

Lavsen Dahal, Mobina Ghojoghnejad, Dhrubajyoti Ghosh, Yubraj Bhandari

Virtual Imaging Trials (VIT) offer a cost-effective and scalable approach for evaluating medical imaging technologies. Computational phantoms, which mimic real patient anatomy and physiology, play a central role in VITs. However, the current libraries of computational phantoms face limitations, particularly in terms of sample size and diversity. Insufficient

Keqin Feng, Qiuyue Liu, Jinzhao Pan, Ye Tian

A positive integer $n$ is called a tiling number if the equilateral triangle can be dissected into $nk^2$ congruent triangles for some integer $k$. An integer $n>3$ is tiling number if and only if at least one of the elliptic curves $E^{(\pm n)}:\pm ny^2=x(x-1)(x+3)$ has positive Mordell-Weil rank. Let $A$ denote one of the two curves. In this paper, using W

Javad Chevinly, Shervin Salehi Rad, Elias Nadi, Bogdan Proca

This paper presents a design and implementation of a high-power Gallium Nitride (GaN)-based multilevel Hbridge inverter to excite wireless charging coils for the wireless power transfer of electric vehicles (EVs). Compared to the traditional conductive charging, wireless charging technology offers a safer and more convenient way to charge EVs. Due to the inc

Ponkoj Chandra Shill, David Feil-Seifer, Jiullian-Lee Vargas Ruiz, Rui Wu

Our ongoing development and deployment of an online robotics education platform highlighted a gap in providing an interactive, feedback-rich learning environment essential for mastering programming concepts in robotics, which they were not getting with the traditional code-simulate-turn in workflow. Since teaching resources are limited, students would benefi

Xinli Guo, Weidong Zhang, Ruonan Liu, Peng Han

With their high-fidelity scene representation capability, the attention of SLAM field is deeply attracted by the Neural Radiation Field (NeRF) and 3D Gaussian Splatting (3DGS). Recently, there has been a surge in NeRF-based SLAM, while 3DGS-based SLAM is sparse. A novel 3DGS-based SLAM approach with a fusion of deep visual feature, dual keyframe selection an

Parosh Aziz Abdulla, Mohamed Faouzi Atig, Sarbojit Das, Bengt Jonsson

Stateless model checking is a fully automatic verification technique for concurrent programs that checks for safety violations by exploring all possible thread schedulings. It becomes effective when coupled with Dynamic Partial Order Reduction (DPOR), which introduces an equivalence on schedulings and reduces the amount of needed exploration. DPOR algorithms

Qi Huang, Zi-Xuan Ma, Jia-Jun Wu, Rong-Gang Ping

In this study, the impact of triangle singularity is investigated in the isospin-breaking process $J/ψ\to Λ\barΛ π$. The triangle singularity is found to play a significant role in the process, resulting in the creation of a resonance-like structure around 1.4 GeV in the $Λπ(\barΛπ)$ invariant mass spectrum. To amplify the impact of this triangle singularity

Mojtaba Hosseini, John Turner

Since its inception, Benders Decomposition (BD) has been successfully applied to a wide range of large-scale mixed-integer (linear) problems. The key element of BD is the derivation of Benders cuts, which are often not unique. In this paper, we introduce a novel unifying Benders cut selection technique based on a geometric interpretation of cut ``depth'&

Setareh Cohan, Guy Tevet, Daniele Reda, Xue Bin Peng

Motion in-betweening, a fundamental task in character animation, consists of generating motion sequences that plausibly interpolate user-provided keyframe constraints. It has long been recognized as a labor-intensive and challenging process. We investigate the potential of diffusion models in generating diverse human motions guided by keyframes. Unlike previ

Hasti Toossi, Guo Qing Huai, Jinyu Liu, Eric Khiu

In the pursuit of supporting more languages around the world, tools that characterize properties of languages play a key role in expanding the existing multilingual NLP research. In this study, we focus on a widely used typological knowledge base, URIEL, which aggregates linguistic information into numeric vectors. Specifically, we delve into the soundness a

Han Yu, Peikun Guo, Akane Sano

Time series data analysis is a critical component in various domains such as finance, healthcare, and meteorology. Despite the progress in deep learning for time series analysis, there remains a challenge in addressing the non-stationary nature of time series data. Traditional models, which are built on the assumption of constant statistical properties over

Tsung-Wei Hu, Ming-Jun Lai

This paper outlines a methodology for constructing a geometrically smooth interpolatory curve in $\mathbb{R}^d$ applicable to oriented and flattenable points with $d\ge 2$. The construction involves four essential components: local functions, blending functions, redistributing functions, and gluing functions. The resulting curve possesses favorable attribute

Adam Erickson, Syed Qamar Abbas Shah, Ather Mahmood, Pratyush Buragohain

Chromia (Cr2O3) is a magnetoelectric oxide which permits voltage-control of the antiferromagnetic (AFM) order, but it suffers technological constraints due to its low Neel Temperature (TN ~307 K) and the need of a symmetry breaking applied magnetic field to achieve reversal of the Neel vector. Recently, boron (B) doping of Cr2O3 films led to an increase TN >

Saad Mohammad Abrar, Kazi Tasnim Zinat, Naman Awasthi, Vanessa Frias-Martinez

Early in the pandemic, counties and states implemented a variety of non-pharmacological interventions (NPIs) focused on mobility, such as national lockdowns or work-from-home strategies, as it became clear that restricting movement was essential to containing the epidemic. Due to these restrictions, businesses were severely affected and in particular, small,

Na Bo, Jong-Hyeon Jeong, Erick Forno, Ying Ding

An important aspect of precision medicine focuses on characterizing diverse responses to treatment due to unique patient characteristics, also known as heterogeneous treatment effects (HTE), and identifying beneficial subgroups with enhanced treatment effects. Estimating HTE with right-censored data in observational studies remains challenging. In this paper

William E Bishop, Alice Li, Christopher Rawles, Oriana Riva

A common problem for agents operating in real-world environments is that the response of an environment to their actions may be non-deterministic and observed through noise. This renders environmental state and progress towards completing a task latent. Despite recent impressive demonstrations of LLM's reasoning abilities on various benchmarks, whether LLMs

S. Tyler, J. Newland, P. Hepworth, A. Wijesekara

Mechanical polishing of diamond is known to be detrimental to the spin lifetime and strain environment of near-surface defects. By utilising a chemical mechanical polishing (CMP) process, we demonstrate that we can achieve 13C-limited spin lifetimes of shallow implanted (<34 nm) NV centres in an industrially scalable process. We compare spin lifetimes (T2) o

Emin Burak Onat, Shangqing Cao, Raiyan Rizwan, Xuan Jiang

Environmental factors pose a significant challenge to the operational efficiency and safety of advanced air mobility (AAM) networks. This paper presents a simulation-optimization framework that dynamically integrates wind variability into AAM operations. We employ a nonlinear charging model within a multi-vertiport environment to optimize fleet size and sche

Allmin Balloccu, Jack Zhang

This paper introduces Dynamic Embeddings with Task-Oriented prompting (DETOT), a novel approach aimed at improving the adaptability and efficiency of machine learning models by implementing a flexible embedding layer. Unlike traditional static embeddings [14], DETOT dynamically adjusts embeddings based on task-specific requirements and performance feedback,

Ameneh Maghsoodi, Kaushik Bhattacharya

Liquid crystal elastomers are cross-linked elastomer networks with liquid crystal mesogens incorporated into the main or side chain. Polydomain liquid crystalline (nematic) elastomers exhibit unusual mechanical properties like soft elasticity, where the material deforms at nearly constant stress, due to the reorientation of mesogens. In this paper, we use nu

Pengming Song, Qianhao Zhao, Ruihai Wang, Ninghe Liu

Non-line-of-sight (NLOS) imaging enables the visualization of objects hidden from direct view, with applications in surveillance, remote sensing, and light detection and ranging. Here, we introduce a NLOS imaging technique termed ptychographic NLOS (pNLOS), which leverages coded ptychography for depth-resolved imaging of obscured objects. Our approach involv

Yi Wang, Qian Zhou, David Ledo

Automated plot generation for games enhances the player's experience by providing rich and immersive narrative experience that adapts to the player's actions. Traditional approaches adopt a symbolic narrative planning method which limits the scale and complexity of the generated plot by requiring extensive knowledge engineering work. Recent advancements use

Ankit Shaw

This research delves into the enhancement of control mechanisms for the da Vinci Surgical System, focusing on the implementation of gravity compensation and refining the modeling of the master and patient side manipulators. Leveraging the Robot Operating System (ROS) the study aimed to fortify the precision and stability of the robots movements essential for

Shreedhar Bhat

This paper explores the dual space corresponding to p-Bergman space and examines the essential condition for the dual space to be a q-Bergman space. The investigation involves a detailed examination of the interpolation space of a Banach couple. Additionally, we draw comparisons between the `duality', `integrability' and `regularity' properties of a domain.

J. Buitenhuis

We explore the field of wildlife re-identification by implementing an MLP from scratch using NumPy, A DCNN using Keras, and a binary classifier with LightGBM for the purpose of learning for an assignment. Analyzing the performance of multiple models on multiple datasets. We attempt to replicate prior research in metric learning for wildlife re-identification

Tianyi Chen, Zachary Lubberts, Avanti Athreya, Youngser Park

We describe a model for a network time series whose evolution is governed by an underlying stochastic process, known as the latent position process, in which network evolution can be represented in Euclidean space by a curve, called the Euclidean mirror. We define the notion of a first-order changepoint for a time series of networks, and construct a family o

Leron Borsten, Simon Jonsson, Hyungrok Kim

Asymptotic observables in quantum field theory beyond the familiar $S$-matrix have recently attracted much interest, for instance in the context of gravity waveforms. Such observables can be understood in terms of Schwinger-Keldysh-type 'amplitudes' computed by a set of modified Feynman rules involving cut internal legs and external legs labelled by time-fol

Aloni Cohen, Alexander Hoover, Gabe Schoenbach

We study watermarking schemes for language models with provable guarantees. As we show, prior works offer no robustness guarantees against adaptive prompting: when a user queries a language model more than once, as even benign users do. And with just a single exception (Christ and Gunn, 2024), prior works are restricted to zero-bit watermarking: machine-gene

Ivan Kaygorodov, Abror Khudoyberdiyev, Zarina Shermatova

We compute $\frac{1}{2}$-derivations on the deformative Schr\"{o}dinger-Witt algebra, on not-finitely graded Witt algebras $W_n(G)$, and on not-finitely graded Heisenberg-Witt algebra $HW_n(G)$. We classify all transposed Poisson structures on such algebras.

Antoine Remond-Tiedrez, Leslie M. Smith, Samuel N. Stechmann

A linear decomposition of states underpins many classical systems. This is the case of the Helmholtz decomposition, used to split vector fields into divergence-free and potential components, and of the dry Boussinesq system in atmospheric dynamics, where identifying the slow and fast components of the flow can be viewed as a decomposition. The dry Boussinesq

Chuanneng Sun, Songjun Huang, Dario Pompili

In recent years, Large Language Models (LLMs) have shown great abilities in various tasks, including question answering, arithmetic problem solving, and poem writing, among others. Although research on LLM-as-an-agent has shown that LLM can be applied to Reinforcement Learning (RL) and achieve decent results, the extension of LLM-based RL to Multi-Agent Syst

Chengwu Huang, U-Wai Lok, Jingke Zhang, Hui Liu

Effective clutter filtering is crucial in suppressing tissue clutter and extracting blood flow signal in Doppler ultrasound. Recent advances in eigen-based clutter filtering techniques have enabled ultrasound imaging of microvasculature without the need for contrast agents. However, simultaneously achieving fully adaptive, highly sensitive and real-time impl

Gerd Pühlhofer, Fabian Leuschner, Heiko Salzmann

The High Energy Stereoscopic System H.E.S.S. is an array of Cherenkov Telescopes located in the Khomas Highlands in Namibia. H.E.S.S. started operations in 2003 and has been operated very successfully since then. With its location in the Southern hemisphere, the system provides a privileged view of the Milky Way and the Galactic center region. With H.E.S.S.,

Greg Dresden, Jacob Siehler

We take Conway's Look and Say Sequence into a base-3 world, and we discover that there are only 24 interesting and irreducible sequences in base 3.

Valerie Yoshioka, Jicheng Jin, Haiqi Zhou, Zichen Tang

Commercial production of integrated photonic devices is limited by scalability of desirable material platforms. We explore a relatively new photonic material, AlScN, for its use in electro-optic modulation. Its CMOS-compatibility could facilitate large-scale production of integrated photonic modulators, and it exhibits an enhanced second-order optical nonlin

Mia Kumamoto, Sanjay Reddy

Repulsive short-range interactions can induce p-wave attraction between fermions in dense matter and lead to Cooper pairing at the Fermi surface. We investigate this phenomenon, well-known as the Kohn-Luttinger effect in condensed matter physics, in dense matter with strong short-range repulsive interactions. We find that repulsive interactions required to s

Owen Fiedorowicz, Tyler C. Grover, Vincent G. J. Rodgers, Hazal D. Zenger

The geometric action of the semi-direct product of the Kac-Moody and Virasoro algebras contains the WZW action equipped with a background vector potential $A$ associated to a coadjoint element of the Kac-Moody algebra as well as the 2D gravitational Polyakov action and an accompanying background field, $\mathcal{D}$, called the diffeomorphism field. Just as

José Luiz Nunes, Guilherme F. C. F. Almeida, Marcelo de Araujo, Simone D. J. Barbosa

Large language models (LLMs) have taken centre stage in debates on Artificial Intelligence. Yet there remains a gap in how to assess LLMs' conformity to important human values. In this paper, we investigate whether state-of-the-art LLMs, GPT-4 and Claude 2.1 (Gemini Pro and LLAMA 2 did not generate valid results) are moral hypocrites. We employ two research

Jiaming Chen, Alex Küronya, Yusuf Mustopa, Jakob Stix

We study effective global generation properties of projectivizations of curve semistable vector bundles over curves and abelian varieties.

Jaime Guajardo, Ozgun Bursalioglu, Dan B Goldman

In this pilot project, we teamed up with artists to develop new workflows for 2D animation while producing a short educational cartoon. We identified several workflows to streamline the animation process, bringing the artists' vision to the screen more effectively.

Laura Eslava, Sayle Sigarreta, Arno Siri-Jegousse

We prove that the generalized Randic index over graphs following the Erd\H{o}s-Renyi model, for both the sparse and dense regimes, is concentrated around its mean when the number of vertices tends to infinity.

Hiba Kobeissi, Xining Gao, Samuel J. DePalma, Jourdan K. Ewoldt

Movies of human induced pluripotent stem cell (hiPSC)-derived engineered cardiac tissue (microbundles) contain abundant information about structural and functional maturity. However, extracting these data in a reproducible and high-throughput manner remains a major challenge. Furthermore, it is not straightforward to make direct quantitative comparisons acro

Alexander Stollenwerk, Laurent Jacques

We propose a novel algorithm for distributed stochastic gradient descent (SGD) with compressed gradient communication in the parameter-server framework. Our gradient compression technique, named flattened one-bit stochastic gradient descent (FO-SGD), relies on two simple algorithmic ideas: (i) a one-bit quantization procedure leveraging the technique of dith

Donghun Noh, Hyunwoo Nam, Kyle Gillespie, Yeting Liu

This paper presents Yummy Operations Robot Initiative (YORI), a proprioceptive dual-arm robotic system that demonstrates autonomous multi-dish cooking for scalable food service applications. YORI integrates a dual-arm manipulator equipped with proprioceptive actuators, custom-designed tools, appliances, and a structured kitchen environment to address the com

Asmaa Abada, Nicolás Bernal, Antonio E. Cárcamo Hernández, Sergey Kovalenko

Radiative seesaw models are examples of interesting and testable extensions of the Standard Model to explain the light neutrino masses. In radiative models at 1-loop level, such as the popular scotogenic model, in order to successfully reproduce neutrino masses and mixing, one has to rely either on unnaturally small Yukawa couplings or on a very small mass s

David Xu

Multi-modal learning in the audio-language domain has seen significant advancements in recent years. However, audio-language learning faces challenges due to limited and lower-quality data compared to image-language tasks. Existing audio-language datasets are notably smaller, and manual labeling is hindered by the need to listen to entire audio clips for acc

Saad Mohammad Abrar, Naman Awasthi, Daniel Smolyak, Vanessa Frias-Martinez

The US COVID-19 Forecast Hub, a repository of COVID-19 forecasts from over 50 independent research groups, is used by the Centers for Disease Control and Prevention (CDC) for their official COVID-19 communications. As such, the Forecast Hub is a critical centralized resource to promote transparent decision making. While the Forecast Hub has provided valuable

Yuya Asano, Diane Litman, Quentin King-Shepard, Tristan Maidment

One of the keys to the success of collaborative learning is balanced participation by all learners, but this does not always happen naturally. Pedagogical robots have the potential to facilitate balance. However, it remains unclear what participation balance robots should aim at; various metrics have been proposed, but it is still an open question whether we

Lauren Dallachiesa, Ivan Biaggio

We introduce electrically-poled small molecule assemblies that can serve as the active electro-optic material in nano-scale guided-wave circuits such as those of the silicon photonics platform. These monolithic organic materials can be vacuum-deposited to homogeneously fill nanometer-size integrated-optics structures, and electrically poled at higher tempera

Jing Su, Ivan Biaggio

Appropriately designed dual-core fibers using coupling-length phase matching (CLPM) allow for phase-matched frequency downconversion over wide frequency intervals using the third-order optical nonlinearity of glass. By tuning the distance between the two cores, CLPM allows continuously tunable phase matching for widely different wavelengths for the process i

Eric Graves, Jake B. Perazzone, Kevin Chan

When making decisions in a network, it is important to have up-to-date knowledge of the current state of the system. Obtaining this information, however, comes at a cost. In this paper, we determine the optimal finite-time update policy for monitoring the binary states of remote sources with a reporting rate constraint. We first prove an upper and lower boun

Yang Li, Donggyu B. Sohn, Matthew Hummon, Susan Schima

We describe a process for fabricating a wafer-scale array of alkali metal vapor cells with low residual gas pressure. We show that by etching long, thin channels between the cells on the Si wafer surface, the residual gas pressure in the evacuated vapor cell can be reduced to below 0.5 kPa (4 Torr) with a yield above 50 %. The low residual gas pressure in th

Howard E. Bond, Akshat S. Chaturvedi, Robin Ciardullo, Klaus Werner

During our spectroscopic survey of central stars of faint planetary nebulae (PNe), we found that the nucleus of Abell 57 exhibits strong nebular emission lines. Using synthetic narrow-band images, we show that the emission arises from an unresolved compact emission knot (CEK) coinciding with the hot (90,000 K) central star. Thus Abell 57 belongs to the rare