October 2023 arXiv papers — page 93

Ruixuan Miao, Xu Lu, Cong Tian, Bin Yu

Unlike the standard Reinforcement Learning (RL) model, many real-world tasks are non-Markovian, whose rewards are predicated on state history rather than solely on the current state. Solving a non-Markovian task, frequently applied in practical applications such as autonomous driving, financial trading, and medical diagnosis, can be quite challenging. We pro

Washim Uddin Mondal, Vaneet Aggarwal

We consider the problem of designing sample efficient learning algorithms for infinite horizon discounted reward Markov Decision Process. Specifically, we propose the Accelerated Natural Policy Gradient (ANPG) algorithm that utilizes an accelerated stochastic gradient descent process to obtain the natural policy gradient. ANPG achieves $\mathcal{O}({\epsilon

Junjun Pan, Yixin Liu, Yizhen Zheng, Shirui Pan

Node-level graph anomaly detection (GAD) plays a critical role in identifying anomalous nodes from graph-structured data in various domains such as medicine, social networks, and e-commerce. However, challenges have arisen due to the diversity of anomalies and the dearth of labeled data. Existing methodologies - reconstruction-based and contrastive learning

Hengran Zhang, Ruqing Zhang, Jiafeng Guo, Maarten de Rijke

Retrieval-enhanced methods have become a primary approach in fact verification (FV); it requires reasoning over multiple retrieved pieces of evidence to verify the integrity of a claim. To retrieve evidence, existing work often employs off-the-shelf retrieval models whose design is based on the probability ranking principle. We argue that, rather than releva

S. Ali Hassani Gangaraj, Boyuan Jin, Christos Argyropoulos, Francesco Monticone

Nonlinear light-matter interactions are typically enhanced by increasing the local field and its interaction time with matter. Conventional methods to achieve these goals are based on resonances or slow-light effects. However, these methods suffer from various issues, including narrow operational bandwidths, large footprints, and material absorption. An inte

Mikhail Kovalev, Zenghua Zhou, Xuefei Chen, Zhanwen Han

We use an updated method for the detection of double-lined spectroscopic binaries (SB2) using $v \sin{i}$ values from spectral fits. The method is applied to all spectra from LAMOST-MRS. Using this method, we detect 12426 SB2 candidates, where 4321 are already known and 8105 are new discoveries. We check their spectra manually to minimise possible false posi

Chen Ling, Xuchao Zhang, Xujiang Zhao, Yanchi Liu

Open-ended Commonsense Reasoning is defined as solving a commonsense question without providing 1) a short list of answer candidates and 2) a pre-defined answer scope. Conventional ways of formulating the commonsense question into a question-answering form or utilizing external knowledge to learn retrieval-based methods are less applicable in the open-ended

Jingheng Ye, Yinghui Li, Yangning Li, Hai-Tao Zheng

Data Augmentation through generating pseudo data has been proven effective in mitigating the challenge of data scarcity in the field of Grammatical Error Correction (GEC). Various augmentation strategies have been widely explored, most of which are motivated by two heuristics, i.e., increasing the distribution similarity and diversity of pseudo data. However

Hao Zhao, Jie Fu, Zhaofeng He

Parameter-efficient fine-tuning (PEFT) has shown its effectiveness in adapting the pre-trained language models to downstream tasks while only updating a small number of parameters. Despite the success, most existing methods independently adapt to each task without considering knowledge transfer between tasks and are limited to low-data regimes. To overcome t

Yongheng Ge, Ziming Zhu, Zeying Zhang, Weikang Wu

Realizing topological semimetal states with novel emergent fermions in magnetic materials is a focus of current research. Based on first-principle calculations and symmetry analysis, we reveal interesting magnetic emergent fermions in an existing material MnB2. In the temperature range from 157 K to 760 K, MnB2 is a collinear antiferromagnet. We find the coe

Yi Shen, Yahui Jin, Yongheng Ge, Mingxing Chen

We present a prediction of chiral topological metals with several classes of unconventional quasiparticle fermions in a family of SrGePt-type materials in terms of first-principles calculations. In these materials, fourfold spin-3/2 Rarita-Schwinger-Weyl (RSW) fermion, sixfold excitation, and Weyl fermions coexist around the Fermi level as spin-orbit couplin

Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang

Humans are social beings; we pursue social goals in our daily interactions, which is a crucial aspect of social intelligence. Yet, AI systems' abilities in this realm remain elusive. We present SOTOPIA, an open-ended environment to simulate complex social interactions between artificial agents and evaluate their social intelligence. In our environment, agent

N. Hizawa, K. Hagino

A microscopic description of nuclear fission represents one of the most challenging problems in nuclear theory. While phenomenological coordinates, such as multipole moments, have often been employed to describe fission, it is not obvious whether these parameters fully reflect the shape dynamics of interest. We here propose a novel method to extract collecti

Jiawei Hu, Wenhang Liu, Jingang Yi, Zhenhua Xiong

We present object handling and transporting by a multi-robot team with a deformable sheet as a carrier. Due to the deformability of the sheet and the high dimension of the whole system, it is challenging to clearly describe all the possible positions of the object on the sheet for a given formation of the multi-robot system. A complete forward kinematics (FK

Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou

Real-world graphs are typically complex, exhibiting heterogeneity in the global structure, as well as strong heterophily within local neighborhoods. While a growing body of literature has revealed the limitations of common graph neural networks (GNNs) in handling homogeneous graphs with heterophily, little work has been conducted on investigating the heterop

Tiwei Wei

Liquid jet impingement cooling is an efficient cooling technique where the liquid coolant is directly ejected from nozzles on the chip backside resulting in a high cooling efficiency due to the absence of the TIM and the lateral temperature gradient. In literature, several Si-fabrication based impingement coolers with nozzle diameters of a few distributed re

Lutz Warnke

Gunby-He-Narayanan showed that the logarithmic gap predictions of Kahn-Kalai and Talagrand (proved by Park-Pham and Frankston-Kahn-Narayanan-Park) about thresholds of up-sets do not apply to down-sets. In particular, for the down-set of triangle-free graphs, they showed that there is a polynomial gap between the threshold and the factional expectation thresh

Pedro Araújo, Simon Griffiths, Matas Šileikis, Lutz Warnke

We consider maximum rooted tree extension counts in random graphs, i.e., we consider M_n = \max_v X_v where X_v counts the number of copies of a given tree in G_{n,p} rooted at vertex v. We determine the asymptotics of M_n when the random graph is not too sparse, specifically when the edge probability p=p(n) satisfies p(1-p)n \gg \log n. The problem is more

Yasufumi Kojima, Shijun Yoshida

This study was focused on the investigation of a magnetic field penetrating from the core of a neutron star to its surface. The range of possible field configurations in the intermediate solid crust is less limited owing to the elastic force acting on the force balance. When the Lorentz force is excessively strong, the magnetoelastic equilibrium does not hol

Yunlong Song, Davide Scaramuzza

Trajectory visualization and animation play critical roles in robotics research. However, existing data visualization and animation tools often lack flexibility, scalability, and versatility, resulting in limited capability to fully explore and analyze flight data. To address this limitation, we introduce Flymation, a new flight trajectory visualization and

Trevor J. Bird, Jacob A. Siefert, Herschel C. Pangborn, Neera Jain

Control Co-Design (CCD) considers the coupled effects of both the plant and control parameters to optimize a system's closed-loop transient performance during the design stage. This paper presents a new method for CCD with guarantees on robustness to nondeterministic disturbances for all initial conditions within a specified region of operation. This is acco

Fahimul Hoque Shubho, Townim Faisal Chowdhury, Ali Cheraghian, Morteza Saberi

Zero-shot learning (ZSL) aims to classify objects that are not observed or seen during training. It relies on class semantic description to transfer knowledge from the seen classes to the unseen classes. Existing methods of obtaining class semantics include manual attributes or automatic word vectors from language models (like word2vec). We know attribute an

Alexander Chernyavsky, Alexey Bereza, Leonid Frumin, David Shapiro

Subwavelength gratings, with period shorter than the incident wavelength, have garnered significant attention in the fields of photonics, optoelectronics, and image sensor technology. In this research, we delve into the scattering characteristics of these gratings by employing the 2-dimensional point dipole approximation. Additionally, we propose a version o

Hotaka Maeda

Five thousand variations of the RoBERTa model, an artificially intelligent "transformer" that can understand text language, completed an English literacy exam with 29 multiple-choice questions. Data were used to calculate the psychometric properties of the items, which showed some degree of agreement to those obtained from human examinee data.

Hangbin Lee, Il Do Ha, Changha Hwang, Youngjo Lee

There is a growing interest in subject-specific predictions using deep neural networks (DNNs) because real-world data often exhibit correlations, which has been typically overlooked in traditional DNN frameworks. In this paper, we propose a novel hierarchical likelihood learning framework for introducing gamma random effects into the Poisson DNN, so as to im

Thales Augusto Barbosa Pinto Silva, David Gelbwaser-Klimovsky

It has been recently claimed that no protocol for measuring quantum work can satisfy standard required physical principles, casting doubts on the compatibility between quantum mechanics, thermodynamics, and the classical limit. In this Letter, we present a solution for this incompatibility. We demonstrate that the standard formulation of these principles fai

Kazuhiro Kuwae

In the framework of quasi-regular strongly local Dirichlet form $(\mathscr{E},D(\mathscr{E}))$ on $L^2(X;\mathfrak{m})$ admitting minimal $\mathscr{E}$-dominant measure $\mu$, we construct a natural $p$-energy functional $(\mathscr{E}^{\,p},D(\mathscr{E}^{\,p}))$ on $L^p(X;\mathfrak{m})$ and $(1,p)$-Sobolev space $(H^{1,p}(X),\|\cdot\|_{H^{1,p}})$ for $p\in]

Rouhan Noor, Himanandhan Reddy Kottur, Patrick J Craig, Liton Kumar Biswas

The semiconductor industry is experiencing a significant shift from traditional methods of shrinking devices and reducing costs. Chip designers actively seek new technological solutions to enhance cost-effectiveness while incorporating more features into the silicon footprint. One promising approach is Heterogeneous Integration (HI), which involves advanced

Siyu An, Ye Liu, Haoyuan Peng, Di Yin

Extracting structured information from videos is critical for numerous downstream applications in the industry. In this paper, we define a significant task of extracting hierarchical key information from visual texts on videos. To fulfill this task, we decouple it into four subtasks and introduce two implementation solutions called PipVKIE and UniVKIE. PipVK

Wei Tao, Zhen-Jun Xiao

We present the three-loop calculations of the nonrelativistic QCD (NRQCD) current renormalization constants and corresponding anomalous dimensions, and the matching coefficients for the spatial-temporal tensor and spatial-spatial axial-tensor currents with two different heavy quark masses. We obtain the convergent decay constant ratio up to the next-to-next-

Qi Jia, Siyu Ren, Yizhu Liu, Kenny Q. Zhu

Despite tremendous improvements in natural language generation, summarization models still suffer from the unfaithfulness issue. Previous work evaluates faithfulness either using models trained on the other tasks or in-domain synthetic data, or prompting a large model such as ChatGPT. This paper proposes to do zero-shot faithfulness evaluation simply with a

Alexander Dunlap, Yu Gu

For the one dimensional Burgers equation with a random and periodic forcing, it is well-known that there exists a family of invariant measures, each corresponding to a different average velocity. In this paper, we consider the coupled invariant measures and study how they change as the velocity parameter varies. We show that the derivative of the invariant m

Zhenyuan Zeng, Chengkang Zhou, Honglin Zhou, Lankun Han

Emergent quasiparticles with a Dirac dispersion in condensed matter systems can be described by the Dirac equation for relativistic electrons, in analogy with Dirac particles in high-energy physics. For example, electrons with a Dirac dispersion have been intensively studied in electronic systems such as graphene and topological insulators. However, charge i

Khoa Tuan Nguyen, Francesca Tozzi, Nikdokht Rashidian, Wouter Willaert

Given that a conventional laparoscope only provides a two-dimensional (2-D) view, the detection and diagnosis of medical ailments can be challenging. To overcome the visual constraints associated with laparoscopy, the use of laparoscopic images and videos to reconstruct the three-dimensional (3-D) anatomical structure of the abdomen has proven to be a promis

Serafina Kamp, Morteza Fayazi, Zineb Benameur-El, Shuyan Yu

With the abundant amount of available online and offline text data, there arises a crucial need to extract the relation between phrases and summarize the main content of each document in a few words. For this purpose, there have been many studies recently in Open Information Extraction (OIE). OIE improves upon relation extraction techniques by analyzing rela

Lodewijk L. Gelauff, Ashish Goel

In 2020 the tragic murder of George Floyd at the hands of law enforcement ignited and intensified nationwide protests, demanding changes in police funding and allocation. This happened during a budgeting feedback exercise where residents of Austin, Texas were invited to share opinions on the budgets of various city service areas, including the Police Departm

Fan Xu, Jinghong Su, Bin Lan, Peng Zhao

Direct numerical simulations are performed to explore the effects of rotating direction of the vertical asymmetric rough wall on the transport properties of Taylor-Couette (TC) flow up to a Taylor number of $\textit{Ta} = 2.39 \times 10^7$. It is shown that compared to the smooth wall, the rough wall with vertical asymmetric strips can enhance the dimensionl

Yirong Zhou, Yanhuang Wu, Yuhan Su, Jing Li

Magnetic Resonance Imaging (MRI) plays an important role in medical diagnosis, generating petabytes of image data annually in large hospitals. This voluminous data stream requires a significant amount of network bandwidth and extensive storage infrastructure. Additionally, local data processing demands substantial manpower and hardware investments. Data isol

Saleh Momeni, Bagher BabaAli

Keystroke biometrics is a promising approach for user identification and verification, leveraging the unique patterns in individuals' typing behavior. In this paper, we propose a Transformer-based network that employs self-attention to extract informative features from keystroke sequences, surpassing the performance of traditional Recurrent Neural Networks.

Chen Zhu-Tian, Haijun Xia

Data documents play a central role in recording, presenting, and disseminating data. Despite the proliferation of applications and systems designed to support the analysis, visualization, and communication of data, writing data documents remains a laborious process, requiring a constant back-and-forth between data processing and writing tools. Interviews wit

Linhao Luo, Thuy-Trang Vu, Dinh Phung, Gholamreza Haffari

Previous studies have relied on existing question-answering benchmarks to evaluate the knowledge stored in large language models (LLMs). However, this approach has limitations regarding factual knowledge coverage, as it mostly focuses on generic domains which may overlap with the pretraining data. This paper proposes a framework to systematically assess the

Sreetama Sarkar, Xinan Ye, Gourav Datta, Peter A. Beerel

Efficient and effective on-line detection and correction of bad-pixels can improve yield and increase the expected lifetime of image sensors. This paper presents a comprehensive Deep Learning (DL) based on-line detection and correction approach, suitable for a wide range of pixel corruption rates. A confidence calibrated segmentation approach is introduced,

Marcelo Arenas, Pablo Barcelo, Diego Bustamante, Jose Caraball

The formal XAI community has studied a plethora of interpretability queries aiming to understand the classifications made by decision trees. However, a more uniform understanding of what questions we can hope to answer about these models, traditionally deemed to be easily interpretable, has remained elusive. In an initial attempt to understand uniform langua

Sang-Yoon Kim, Woochang Lim

The basal ganglia (BG) in the brain exhibit diverse functions for motor, cognition, and emotion. Such BG functions could be made via competitive harmony between the two competing pathways, direct pathway (DP) (facilitating movement) and indirect pathway (IP) (suppressing movement). As a result of break-up of harmony between DP and IP, there appear pathologic

Arkil Patel, Satwik Bhattamishra, Siva Reddy, Dzmitry Bahdanau

Humans possess a remarkable ability to assign novel interpretations to linguistic expressions, enabling them to learn new words and understand community-specific connotations. However, Large Language Models (LLMs) have a knowledge cutoff and are costly to finetune repeatedly. Therefore, it is crucial for LLMs to learn novel interpretations in-context. In thi

Christopher Daggett, Kaijie Yang, Chaoxing Liu, Lukas Muechler

The application of topology, a branch of mathematics, to the study of electronic states in crystalline materials has had a revolutionary impact on the field of condensed matter physics. For example, the development of topological band theory has delivered new approaches and tools to characterize the electronic structure of materials, resulting in the discove

Weston Miller

Assuming standard conjectures, we show that the canonical symmetrizing trace evaluated at powers of a Coxeter element produces rational Catalan numbers for irreducible spetsial complex reflection groups. This extends a technique used by Galashin, Lam, Trinh, and Williams to uniformly prove the enumeration of their noncrossing Catalan objects for finite Coxet

Daniel Monclair, Jean-Marc Schlenker, Nicolas Tholozan

We consider hyperbolic and anti-de Sitter (AdS) structures on $M\times (0,1)$, where $M$ is a $d$-dimensional Gromov-Thurston manifold. If $M$ has cone angles greater than $2π$, we show that there exists a "quasifuchsian" (globally hyperbolic maximal) AdS manifold such that the future boundary of the convex core is isometric to $M$. When $M$ has cone

Xue-Yang Song, Chao-Ming Jian, Liang Fu, Cenke Xu

Motivated by the recent experimental breakthrough on the observation of the fractional quantum anomalous Hall (FQAH) effects in semiconductor and graphene moir\'{e} materials, we explore the rich physics associated with the coexistence of FQAH effect and the charge density wave (CDW) order that spontaneously breaks the translation symmetry. We refer to a sta

Isaac Davis, Funing Li, Daniel Chavas

The effect of warming on severe convective storm potential is commonly explained in terms of changes in vertically-integrated ("bulk") environmental parameters, such as CAPE and 0--6 km shear. However, such events are known to depend on details of the vertical structure of the thermodynamic and kinematic environment that can change independently of these bul

He Yinqiu, Song Peter X. -K., Xu Gongjun

Mediation analysis aims to assess if, and how, a certain exposure influences an outcome of interest through intermediate variables. This problem has recently gained a surge of attention due to the tremendous need for such analyses in scientific fields. Testing for the mediation effect is greatly challenged by the fact that the underlying null hypothesis (i.e

Lihao Wang, Antonyo Musabini, Christel Leonet, Rachid Benmokhtar

Current parking slot detection in advanced driver-assistance systems (ADAS) primarily relies on ultrasonic sensors. This method has several limitations such as the need to scan the entire parking slot before detecting it, the incapacity of detecting multiple slots in a row, and the difficulty of classifying them. Due to the complex visual environment, vehicl

Avijit Thawani, Saurabh Ghanekar, Xiaoyuan Zhu, Jay Pujara

Language models typically tokenize text into subwords, using a deterministic, hand-engineered heuristic of combining characters into longer surface-level strings such as 'ing' or whole words. Recent literature has repeatedly shown the limitations of such a tokenization strategy, particularly for documents not written in English and for representing numbers.

Haille M. L. Perkins, John Ellis, Brian D. Fields, Dieter H. Hartmann

Binary neutron star mergers (BNS) produce high-energy emissions from several physically different sources, including a gamma-ray burst (GRB) and its afterglow, a kilonova, and, at late times, a remnant many parsecs in size. Ionizing radiation from these sources can be dangerous for life on Earth-like planets when located too close. Work to date has explored

Brenda Praggastis, Sinan Aksoy, Dustin Arendt, Mark Bonicillo

HyperNetX (HNX) is an open source Python library for the analysis and visualization of complex network data modeled as hypergraphs. Initially released in 2019, HNX facilitates exploratory data analysis of complex networks using algebraic topology, combinatorics, and generalized hypergraph and graph theoretical methods on structured data inputs. With its 2023

Abdellah Lahdili, Eveline Legendre, Carlo Scarpa

Given a Kaehler manifold polarised by a holomorphic ample line bundle, we consider the circle bundle associated to the polarisation with the induced transversal holomorphic structure. The space of contact structures compatible with this transversal structure is naturally identified with a bundle, of infinite rank, over the space of Kaehler metrics in the fir

M. Kotschenreuther, X. Liu, S. M. Mahajan, D. R. Hatch

The free energy balance equation for gyrokinetic fluctuations is derived and applied to instabilities. An additional term due to electromagnetic sources is included. This can provide a simpler way to compute the free energy balance in practical applications, and is also conceptually clarifying. The free energy balance, by itself, is not sufficient to determi

Liwei Chen, Yuan Yuan

The disc property is formulated for domains in $\mathbb{C}^n$. Holomorphic Lipschitz functions enjoy a gain in the order of Lipschitz regularity along the complex tangential direction on domains with disc property. Disc property is studied on various domains of infinite type. As applications, the local version of Stein's theorem is obtained on these domains,

Wojciech Sirko, Emmanuel Asiedu Brempong, Juliana T. C. Marcos, Abigail Annkah

Mapping buildings and roads automatically with remote sensing typically requires high-resolution imagery, which is expensive to obtain and often sparsely available. In this work we demonstrate how multiple 10 m resolution Sentinel-2 images can be used to generate 50 cm resolution building and road segmentation masks. This is done by training a `student' mode

Jaeeun Kim, Myoungwon Jeon, Yumi Choi, Hannah Richstein

We investigate how patchy reionization affects the star formation history (SFH) and stellar metallicity of ultra-faint dwarf galaxies (UFDs). Patchy reionization refers to varying ultraviolet (UV) background strengths depending on a galaxy's environment. Recent observations highlight the significance of this effect on UFDs, as UFDs can have different SFHs de

Ziren Jiang, Jared D. Huling

The causal effects of continuous treatments are often characterized through the average dose response function, which is challenging to estimate from observational data due to confounding and positivity violations. Modified treatment policies (MTPs) are an alternative approach that aim to assess the effect of a modification to observed treatment values and w

Pavithra Harsha, Shivaram Subramanian, Ali Koc, Mahesh Ramakrishna

We introduce a new class of data-driven and distribution-free optimistic-robust bimodal inventory optimization (BIO) strategy to effectively allocate inventory across a retail chain to meet time-varying, uncertain omnichannel demand. The bimodal nature of BIO stems from its ability to balance downside risk, as in traditional Robust Optimization (RO), which f

Heath Camphire

Let $k$ be a field of odd characteristic $p$. Fix an even number $d<p+1$ and a power $q\geq d+3$ of $p$. For most choices of degree $d$ standard graded hypersurfaces $R=k[x,y,z]/(f)$ with homogeneous maximal ideal $\mathfrak{m}$, we can determine the graded Betti numbers of $R/\mathfrak{m}^{[q]}$. In fact, given two fixed powers $q_0,q_1\geq d+3$, for most c

William M. Wolf, Josiah Schwab, R. Farmer, Evan B. Bauer

Regular, automated testing is a foundational principle of modern software development. Numerous widely-used continuous integration systems exist, but they are often not suitable for the unique needs of scientific simulation software. Here we describe the testing infrastructure developed for and used by the Modules for Experiments in Stellar Astrophysics (MES

Yiming Chen, Victor Ivo, Juan Maldacena

In this paper we revisit the double cone wormhole introduced by Saad, Shenker and Stanford (SSS), which was shown to reproduce the ramp in the spectral form factor. As a first approximation we can say that this solution computes $\textrm{Tr}[e^{-iKT}]$, a trace of the "evolution" operator that generates Schwarzschild time translations on the two sided wormho

David Ilić, Gilles E. Gignac

Large language models (LLMs) are advanced artificial intelligence (AI) systems that can perform a variety of tasks commonly found in human intelligence tests, such as defining words, performing calculations, and engaging in verbal reasoning. There are also substantial individual differences in LLM capacities. Given the consistent observation of a positive ma

GF LHer, AG Osborne, AE Schweikert, CS Ramstein

Lack of electricity access is widespread in the developing world and associated with increased mortality, reduced educational levels, and economic and social disadvantages, especially among women. The 2030 Agenda for Sustainable Development has emphasized securing access to affordable, reliable, and sustainable energy for all. For climatological and health r

Leonardo Hernandez Cano, Yewen Pu, Robert D. Hawkins, Josh Tenenbaum

A typical way in which a machine acquires knowledge from humans is by programming. Compared to learning from demonstrations or experiences, programmatic learning allows the machine to acquire a novel skill as soon as the program is written, and, by building a library of programs, a machine can quickly learn how to perform complex tasks. However, as programs

Wendeline Swart, Guillaume Cabanac

The 'Problematic Paper Screener' (PPS, WCRI'22, https://doi.org/10.48550/arXiv.2210.04895) flagged 12k+ questionable articles featuring tortured phrases, such as 'glucose bigotry' instead of 'glucose intolerance.' It daily screens the literature for 'fingerprints' from a list of 4k tortured phrases known to reflect nonsensical paraphrasing with synonyms. We

Galen J. Bergsten, Ilaria Pascucci, Kevin K. Hardegree-Ullman, Rachel B. Fernandes

Reliable detections of Earth-sized planets in the habitable zone remain elusive in the Kepler sample, even for M dwarfs. The Kepler sample was once thought to contain a considerable number of M dwarf stars ($T_\mathrm{eff} < 4000$ K), which hosted enough Earth-sized ($[0.5,1.5]$ R$_\oplus$) planets to estimate their occurrence rate ($\eta_\oplus$) in the hab

Yimu Wang, Xiangru Jian, Bo Xue

In this work, we present a post-processing solution to address the hubness problem in cross-modal retrieval, a phenomenon where a small number of gallery data points are frequently retrieved, resulting in a decline in retrieval performance. We first theoretically demonstrate the necessity of incorporating both the gallery and query data for addressing hubnes

Aditya Desai, Anshumali Shrivastava

When considering a model architecture, there are several ways to reduce its memory footprint. Historically, popular approaches included selecting smaller architectures and creating sparse networks through pruning. More recently, randomized parameter-sharing (RPS) methods have gained traction for model compression at start of training. In this paper, we compr

Huajie Liu, Shiguang Ma, Jie Qing, Shuhui Zhong

In this paper we develop the p-thinness and the p-fine topology for the asymptotic behavior of p-superharmonic functions at singular points. We consider these as extensions of earlier works on superharmonic functions in dimension 2, on the Riesz and Log potentials in higher dimensions,, and on p-harmonic functions. It is remarkable that, contrary to the abov

Austin Cheng, Alston Lo, Santiago Miret, Brooks Pate

Structure determination is necessary to identify unknown organic molecules, such as those in natural products, forensic samples, the interstellar medium, and laboratory syntheses. Rotational spectroscopy enables structure determination by providing accurate 3D information about small organic molecules via their moments of inertia. Using these moments, Kraitc

Santiago Gerling Konrad, Julie Stephany Berrio, Mao Shan, Favio Masson

Despite the continual advances in Advanced Driver Assistance Systems (ADAS) and the development of high-level autonomous vehicles (AV), there is a general consensus that for the short to medium term, there is a requirement for a human supervisor to handle the edge cases that inevitably arise. Given this requirement, it is essential that the state of the vehi

Nicholas Botzer, David Vasquez, Tim Weninger, Issam Laradji

The ability to detect intent in dialogue systems has become increasingly important in modern technology. These systems often generate a large amount of unlabeled data, and manually labeling this data requires substantial human effort. Semi-supervised methods attempt to remedy this cost by using a model trained on a few labeled examples and then by assigning

Sahbani Rachid

Let $G=(V,A)$ be a digraph. For $X\subseteq V$, the subdigraph of $G$ induced by $X$ is denoted by $G[X]$. A subset $I$ of $V$ is an interval of $G$ if for every $a,b \in I$ and $x \in V \setminus I$, $(x,a) \in A$ if and only if $(x,b) \in A$, and similarly for $(a,x)$ and $(b,x)$. The trivial intervals of $G$ are $\varnothing$, $V$ and $\lbrace x\rbrace$,

Monika Kwiatkowski, Simon Matern, Olaf Hellwich

When taking images of some occluded content, one is often faced with the problem that every individual image frame contains unwanted artifacts, but a collection of images contains all relevant information if properly aligned and aggregated. In this paper, we attempt to build a deep learning pipeline that simultaneously aligns a sequence of distorted images a

Teyun Kwon, Norman Di Palo, Edward Johns

Large Language Models (LLMs) have recently shown promise as high-level planners for robots when given access to a selection of low-level skills. However, it is often assumed that LLMs do not possess sufficient knowledge to be used for the low-level trajectories themselves. In this work, we address this assumption thoroughly, and investigate if an LLM (GPT-4)

Ruyi Liu, Fan Li, Denise Esserman, Mary M. Ryan

The two-stage preference design (TSPD) enables the inference for treatment efficacy while allowing for incorporation of patient preference to treatment. It can provide unbiased estimates for selection and preference effects, where a selection effect occurs when patients who prefer one treatment respond differently than those who prefer another, and a prefere

Panagiota Fatourou, Eleftherios Kosmas, Themis Palpanas, George Paterakis

We present FreSh, a lock-free data series index that exhibits good performance (while being robust). FreSh is based on Refresh, which is a generic approach we have developed for supporting lock-freedom in an efficient way on top of any localityaware data series index. We believe Refresh is of independent interest and can be used to get well-performed lock-fr

A. Poudel, J. Medina, J. O'Hara, H. Salazar

The Los Alamos Neutron Science Center (LANSCE) accelerator at Los Alamos National Laboratory (LANL) has been in service for over 50 years. Efforts to update and modernize crucial systems, many of which are origi-nal, are ongoing. This paper reports on the refurbishment of the Low-Level Radio Frequency (LLRF) Resonance Control Water System (RCWS) for the half

E. Sander, J. D. Meiss

In this paper, we focus on a numerical technique, the weighted Birkhoff average (WBA) to distinguish between four categories of dynamics for quasiperiodically-forced circle maps. Regular dynamics can be classified by rotation vectors, and these can be rapidly computed to machine precision using the WBA. Regular orbits can be resonant or incommensurate and we

Michael Burgess

Trajectories are optimized for a two-dimensional simplified skateboarding system to allow it to perform a fundamental skateboarding trick called an "ollie". A methodology for generating trick trajectories by controlling the position of a point-mass relative to a board is presented and demonstrated over a range of peak jump heights. A hybrid dynamics approach

Kahraman Kostas, Mike Just, Michael A. Lones

Previous research on behavior-based attack detection for networks of IoT devices has resulted in machine learning models whose ability to adapt to unseen data is limited and often not demonstrated. This paper presents IoTGeM, an approach for modeling IoT network attacks that focuses on generalizability, yet also leads to better detection and performance. We

Pengchong Hu, Zhizhong Han

Learning neural implicit representations has achieved remarkable performance in 3D reconstruction from multi-view images. Current methods use volume rendering to render implicit representations into either RGB or depth images that are supervised by multi-view ground truth. However, rendering a view each time suffers from incomplete depth at holes and unaware

Kunyang Li, Kyle Domico, Jean-Charles Noirot Ferrand, Patrick McDaniel

Today, the security of many domains rely on the use of Machine Learning to detect threats, identify vulnerabilities, and safeguard systems from attacks. Recently, transformer architectures have improved the state-of-the-art performance on a wide range of tasks such as malware detection and network intrusion detection. But, before abandoning current approache

F. S. Rocha, J. C. Bellizotti Souza, N. P. Vizarim, C. J. O. Reichhardt

Using atomistic simulations, we have investigated the transport and annihilation of skyrmions interacting with a funnel array under a current applied perpendicular to the funnel axis. We find that transport without annihilation is possible at low currents, when the motion is dominated by skyrmion-skyrmion interactions and skyrmions push each other through th

Jun Xia, Zhihao Yue, Yingbo Zhou, Zhiwei Ling

Due to the popularity of Artificial Intelligence (AI) technology, numerous backdoor attacks are designed by adversaries to mislead deep neural network predictions by manipulating training samples and training processes. Although backdoor attacks are effective in various real scenarios, they still suffer from the problems of both low fidelity of poisoned samp

Taejin Kim, Jiarui Li, Shubhranshu Singh, Nikhil Madaan

The delicate equilibrium between user privacy and the ability to unleash the potential of distributed data is an important concern. Federated learning, which enables the training of collaborative models without sharing of data, has emerged as a privacy-centric solution. This approach brings forth security challenges, notably poisoning and backdoor attacks wh

Yaqing Wang, Jiepu Jiang, Mingyang Zhang, Cheng Li

Personalized text generation presents a specialized mechanism for delivering content that is specific to a user's personal context. While the research progress in this area has been rapid, evaluation still presents a challenge. Traditional automated metrics such as BLEU and ROUGE primarily measure lexical similarity to human-written references, and are not a

Isabel J. Kain, Phil Hinz, Marius Doetz, Benjamin Bulla

High-contrast imaging has been used to discover and characterize dozens of exoplanets to date. The primary limiting performance factor for these instruments is contrast, the ratio of exoplanet to host star brightness that an instrument can successfully resolve. Contrast is largely determined by wavefront error, consisting of uncorrected atmospheric turbulenc

Piotr Achinger, Jakob Stix

We study pairs of non-constant maps between two integral schemes of finite type over two (possibly different) fields of positive characteristic. When the target is quasi-affine, Tamagawa showed that the two maps are equal up to a power of Frobenius if and only if they induce the same homomorphism on their \'etale fundamental groups. We extend Tamagawa's resu

Hillary Ngai, Rohan Agrawal, Neeraj Gaur, Ronny Huang

Adapters are an efficient, composable alternative to full fine-tuning of pre-trained models and help scale the deployment of large ASR models to many tasks. In practice, a task ID is commonly prepended to the input during inference to route to single-task adapters for the specified task. However, one major limitation of this approach is that the task ID may

Qiping Zhang, Nathan Tsoi, Mofeed Nagib, Booyeon Choi

Understanding human perceptions of robot performance is crucial for designing socially intelligent robots that can adapt to human expectations. Current approaches often rely on surveys, which can disrupt ongoing human-robot interactions. As an alternative, we explore predicting people's perceptions of robot performance using non-verbal behavioral cues and ma

Belinda Z. Li, Alex Tamkin, Noah Goodman, Jacob Andreas

Language models (LMs) can be directed to perform target tasks by using labeled examples or natural language prompts. But selecting examples or writing prompts for can be challenging--especially in tasks that involve unusual edge cases, demand precise articulation of nebulous preferences, or require an accurate mental model of LM behavior. We propose to use *

Chun Yuen Tsang, ManYee Betty Tsang, William G. Lynch, Rohit Kumar

With recent advances in neutron star observations, major progress has been made in determining the pressure of neutron star matter at high density. This pressure is constrained by the neutron star deformability, determined from gravitational waves emitted in a neutron-star merger, and measurements of radii of two neutron stars, using a new X-ray observatory

Joseph Cummings, Jonathan Hauenstein

We describe an algorithm for computing Macaulay dual spaces for multi-graded ideals. For homogeneous ideals, the natural grading is inherited by the Macaulay dual space which has been leveraged to develop algorithms to compute the Macaulay dual space in each homogeneous degree. Our main theoretical result extends this idea to multi-graded Macaulay dual space

C. E. Starrett, T. Q. Thelen, C. J. Fontes, D. A. Rehn

Accurate modeling of warm and hot dense matter is challenging in part due to the multitude of excited states that must be considered. In thermal density functional theory, these excited states are averaged over to produce a single, averaged, thermal ground state. Here we present a variational framework and model that includes explicit excited states. In this

Guillaume Marcaud, Alex Taekyung Lee, Adam J. Hauser, F. Y. Yang

We reveal in this study the fundamental low-energy landscape in the ferrimagnetic Sr2CrReO6 double perovskite and describe the underlying mechanisms responsible for the three low-energy excitations below 1.4 eV. Based on resonant inelastic x-ray scattering and magnetic dynamics calculations, and experiments collected from both Sr2CrReO6 powders and epitaxial