February 2024 arXiv papers — page 138

Aimee Guo, Grace Fei, Hemanth Pasupuleti, Jing Wang

The newly released Segment Anything Model (SAM) is a popular tool used in image processing due to its superior segmentation accuracy, variety of input prompts, training capabilities, and efficient model design. However, its current model is trained on a diverse dataset not tailored to medical images, particularly ultrasound images. Ultrasound images tend to

E. Gabrielli, L. Marzola, K. Müürsepp, M. Raidal

The Belle II collaboration has recently observed the rare decay $B^+\to K^+ \nu \bar{\nu}$, finding an excess with respect to the Standard Model prediction. We explore the possibility that the data entails long-distance interactions induced by a massless dark photon, $\gamma_{\scriptscriptstyle{D}}$. This couples at the tree-level to an invisible, dark secto

Ben W. P. Lew, Thomas Roellig, Natasha E. Batalha, Michael Line

The launch of the James Webb Space Telescope (JWST) marks a pivotal moment for precise atmospheric characterization of Y dwarfs, the coldest brown dwarf spectral type. In this study, we leverage moderate spectral resolution observations (R $\sim$ 2700) with the G395H grating of the Near-Infrared Spectrograph (NIRSpec) onboard of JWST to characterize the near

Víctor Alonso, Juan Antonio González, Isaías García de la Fuente, José Carlos Cobos

Relative permittivities, $\varepsilon_{r}$, and refractive indixes, $n_{D}$, have been measured at (288.15-308.15) K and (293.15-303.15) K, respectively, for the mixtures 1-pentanol + octane, or + dibutyl ether and dibutyl ether + octane. These data have been used, together with density measurements available in the literature, to determine the correlation f

Claudia de Rham, John T. Giblin, Andrew J. Tolley

The class of Galileon scalar fields theories encapsulate the Vainshtein screening mechanism which is characteristic of a large range of infrared modified theories of gravity. Such theories can lead to testable departures from General Relativity through fifth forces and new scalar modes of gravitational radiation. However, the inherent non-linearity of the Va

Mary Gerhardinger, John T. Giblin, Andrew J. Tolley, Mark Trodden

The Galileon theory is a prototypical effective field theory that incorporates the Vainshtein screening mechanism--a feature that arises in some extensions of General Relativity, such as massive gravity. The Vainshtein effect requires that the theory contain higher order derivative interactions, which results in Galileons, and theories like them, failing to

Bruce L. Gary, Thomas G. Kaye

The transiting dust clouds that orbit the white dwarf J0328-1219 are devoid of small particles (< 0.1 micron). Observations show that fade amount doesn't depend on wavelength. This finding resembles a similar observation for white dwarf WD 1145+017, but the explanations for an absence of small particles in the two white dwarf systems may differ due to their

Sanaz Zarei

A tunable, polarization sensitive microwave filter based on a reconfigurable dual-layered two-dimensional metallic photonic crystal is presented. The filter consists of a metallic plate with periodic holes and metal pillars which are anchored in a substrate material. The diameter of the pillars is smaller than that of the holes and the lateral position of th

Stefano Cristiani, Guido Cupani, Andrea Trost, Valentina D'Odorico

The gravitationally lensed quasar J014516.6-094517 at z=2.719 has been observed with the ESPRESSO instrument at the ESO VLT to obtain high-fidelity spectra of the two images A and B with a resolving power R=70000. At the redshifts under investigation (2.1 < z < 2.7), the Lyman forests along the two sightlines are separated by sub-kiloparsec physical distance

Víctor Alonso, Mario García, Juan Antonio González, Isaías García De La Fuente

The coexistence curves of the liquid-liquid equilibria (LLE) for systems of 2-phenoxyethanol (2PhEE) with heptane, octane, cyclohexane, methylcyclohexane or ethylcyclohexane have been determined by the method of the critical opalescence using a laser scattering technique. All the curves show an upper critical solution temperature (UCST), have a rather horizo

Michael Bernreiter, Jan Maly, Oliviero Nardi, Stefan Woltran

Online discussion platforms are a vital part of the public discourse in a deliberative democracy. However, how to interpret the outcomes of the discussions on these platforms is often unclear. In this paper, we propose a novel and explainable method for selecting a set of most representative, consistent points of view by combining methods from computational

Iván Alonso, Víctor Alonso, Ismael Mozo, Isaías García de la Fuente

Densities, $\rho$, and speeds of sound, $u$, of 2-propanone + aniline, + N-methylaniline, or + pyridine systems have been measured at (293.15, 298.15 and 303.15) K and atmospheric pressure using a vibrating tube densimeter and sound analyser Anton Paar model DSA-5000. The $\rho$ and $u$ values were used to calculate excess molar volumes, $V^{E}$, and the exc

Shengxiang Hu, Guobing Zou, Song Yang, Yanglan Gan

In service-oriented architectures, accurately predicting the Quality of Service (QoS) is crucial for maintaining reliability and enhancing user satisfaction. However, significant challenges remain due to existing methods always overlooking high-order latent collaborative relationships between users and services and failing to dynamically adjust feature learn

Emily S Sumner, Jonathan DeCastro, Jean Costa, Deepak E Gopinath

Recent advances in AI and intelligent vehicle technology hold promise to revolutionize mobility and transportation, in the form of advanced driving assistance (ADAS) interfaces. Although it is widely recognized that certain cognitive factors, such as impulsivity and inhibitory control, are related to risky driving behavior, play a significant role in on-road

Shufan Li, Harkanwar Singh, Aditya Grover

In recent years, Transformers have become the de-facto architecture for sequence modeling on text and a variety of multi-dimensional data, such as images and video. However, the use of self-attention layers in a Transformer incurs prohibitive compute and memory complexity that scales quadratically w.r.t. the sequence length. A recent architecture, Mamba, bas

M. Gloria Fiestras-Janeiro, Ignacio García-Jurado, Ana Meca, Manuel A. Mosquera

We introduce a new model involving TU-games and exogenous structures. Specifically, we consider that each player in a population can choose an element in a strategy set and that, for every possible strategy profile, a TU-game is associated with the population. This is what we call a TU-game with strategies. We propose and characterize the maxmin procedure to

Iván Alonso, Víctor Alonso, Ismael Mozo, Isaías García de la Fuente

Densities, $\rho$ , and speeds of sound, $u$, of 2-propanone + dipropylamine,+ dibutylamine or + triethylamine systems have been measured at (293.15, 298.15 and 303.15) K and atmospheric pressure using a vibrating tube densimeter and sound analyser Anton Paar model DSA-5000. The $\rho$ and $u$ values were used to calculate excess molar volumes, $V^{E}$, and

Shoubin Yu, Jaehong Yoon, Mohit Bansal

Despite impressive advancements in recent multimodal reasoning approaches, they are still limited in flexibility and efficiency, as these models typically process only a few fixed modality inputs and require updates to numerous parameters. This paper tackles these critical challenges and proposes CREMA, a generalizable, highly efficient, and modular modality

Anthony J. Brady, Jing Wu, Quntao Zhuang

Recent advancements in multi-mode Gottesman-Kitaev-Preskill (GKP) codes have shown great promise in enhancing the protection of both discrete and analog quantum information. This broadened range of protection brings opportunities beyond quantum computing to benefit quantum sensing by safeguarding squeezing -- the essential resource in many quantum metrology

Onur G. Guleryuz, Philip A. Chou, Berivan Isik, Hugues Hoppe

We propose sandwiching standard image and video codecs between pre- and post-processing neural networks. The networks are jointly trained through a differentiable codec proxy to minimize a given rate-distortion loss. This sandwich architecture not only improves the standard codec's performance on its intended content, but more importantly, adapts the codec t

Eduardo Cerpa, Nathaly Corrales, Matías Courdurier, Leonel E. Medina

This paper studies the phenomenon of conduction block in model neurons using high-frequency biphasic stimulation (HFBS). The focus is investigating the triggering of undesired onset action potentials when the HFBS is turned on. The approach analyzes the transient behavior of an averaged system corresponding to the FitzHugh-Nagumo neuron model using Lyapunov

Aditya Bommakanti, Harshith Reddy Vonteri, Sayan Ranu, Panagiotis Karras

The need to identify graphs with small structural distances from a query arises in domains such as biology, chemistry, recommender systems, and social network analysis. Among several methods for measuring inter-graph distance, Graph Edit Distance (GED) is preferred for its comprehensibility, though its computation is hindered by NP-hardness. Optimization bas

Jiehua Chen, William S. Zwicker

In fair division of a connected graph $G = (V, E)$, each of $n$ agents receives a share of $G$'s vertex set $V$. These shares partition $V$, with each share required to induce a connected subgraph. Agents use their own valuation functions to determine the non-negative numerical values of the shares, which determine whether the allocation is fair in some spec

Víctor Alonso, Iván Alonso, Ismael Mozo, Juan Antonio González

The coexistence curves of the liquid-liquid equilibria (LLE) for systems of -caprolactam with heptane, octane, nonane, decane or 2,2,4-trimethylpentane have been determined by the method of the critical opalescence using a laser scattering technique. All the curves show an upper critical solution temperature (UCST), have a rather horizontal top and their sym

Kelly Payette, Céline Steger, Roxane Licandro, Priscille de Dumast

Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and the Fetal Brain Tissue Annotation (FeTA) Challenge 2021 helped to establish an excellent standard of fetal brain segmentation. However, FeTA 2021 was a single center study, and the g

Gabriela Pinto, Keith Burghardt, Kristina Lerman, Emilio Ferrara

TikTok is one of the largest and fastest-growing social media sites in the world. TikTok features, however, such as voice transcripts, are often missing and other important features, such as OCR or video descriptions, do not exist. We introduce the Generative AI Enriched TikTok (GET-Tok) data, a pipeline for collecting TikTok videos and enriched data by augm

Matteo Nerini, Golsa Ghiaasi, Bruno Clerckx

Reconfigurable intelligent surface (RIS) is a key technology to control the communication environment in future wireless networks. Recently, beyond diagonal RIS (BD-RIS) emerged as a generalization of RIS achieving larger coverage through additional tunable impedance components interconnecting the RIS elements. However, conventional RIS and BD-RIS can effect

Nikhil Sharma, Q. Vera Liao, Ziang Xiao

Large language models (LLMs) powered conversational search systems have already been used by hundreds of millions of people, and are believed to bring many benefits over conventional search. However, while decades of research and public discourse interrogated the risk of search systems in increasing selective exposure and creating echo chambers -- limiting e

M. L. Savchenko, J. Gospodaric, A. Shuvaev, I. A. Dmitriev

We report on dynamic Shubnikov - de Haas (SdH) oscillations that are measured in the optical response, sub - terahertz transmittance of two-dimensional systems, and reveal two distinct types of oscillation nodes: "universal" nodes at integer ratios of radiation and cyclotron frequencies and "tunable" nodes at positions sensitive to all parameters of the stru

Nicolas Nguyen, Imad Aouali, András György, Claire Vernade

We study the problem of Bayesian fixed-budget best-arm identification (BAI) in structured bandits. We propose an algorithm that uses fixed allocations based on the prior information and the structure of the environment. We provide theoretical bounds on its performance across diverse models, including the first prior-dependent upper bounds for linear and hier

Yi-Hsuan Lin, Teemu Tyni, Philipp Zimmermann

This article is devoted to forward and inverse problems associated with time-independent semilinear nonlocal wave equations. We first establish comprehensive well-posedness results for some semilinear nonlocal wave equations. The main challenge is due to the low regularity of the solutions of linear nonlocal wave equations. We then turn to an inverse problem

Jiin Woo, Laixi Shi, Gauri Joshi, Yuejie Chi

Offline reinforcement learning (RL), which seeks to learn an optimal policy using offline data, has garnered significant interest due to its potential in critical applications where online data collection is infeasible or expensive. This work explores the benefit of federated learning for offline RL, aiming at collaboratively leveraging offline datasets at m

Jung Won Cho, Nik Ruskuc

It was proved by Oliveira and Silva (2005) that every finitely generated inverse subsemigroup of the monogenic free inverse semigroup $FI_1$ is finitely presented. The present paper continues this development, and gives generating sets and presentations for general (i.e. not necessarily finitely generated) inverse subsemigroups of $FI_1$. For an inverse semi

Priyanka Dey, Luca Luceri, Emilio Ferrara

Social media has become a crucial conduit for the swift dissemination of information during global crises. However, this also paves the way for the manipulation of narratives by malicious actors. This research delves into the interaction dynamics between coordinated (malicious) entities and organic (regular) users on Twitter amidst the Gaza conflict. Through

Parker Ewen, Hao Chen, Yuzhen Chen, Anran Li

Robots must be able to understand their surroundings to perform complex tasks in challenging environments and many of these complex tasks require estimates of physical properties such as friction or weight. Estimating such properties using learning is challenging due to the large amounts of labelled data required for training and the difficulty of updating t

Yinglei Peng, Marko Ristić, Atul Kedia, Richard O'Shaughnessy

Kilonovae are the electromagnetic transients created by the radioactive decay of freshly synthesized elements in the environment surrounding a neutron star merger. To study the fundamental physics in these complex environments, kilonova modeling requires, in part, the use of radiative transfer simulations. The microphysics involved in these simulations resul

Houwen Wu, Zihan Yan, Shuxuan Ying

In this letter, we derive the singular condition for black holes and demonstrate the potential resolution of the Schwarzschild black hole singularity in general relativity using non-perturbative $\alpha^{\prime}$ corrections of string theory. This work is motivated by the Belinskii, Khalatnikov and Lifshitz (BKL) proposal, which suggests that the structure o

Xiaoxiao Long, Yuhang Zheng, Yupeng Zheng, Beiwen Tian

We introduce a novel approach to learn geometries such as depth and surface normal from images while incorporating geometric context. The difficulty of reliably capturing geometric context in existing methods impedes their ability to accurately enforce the consistency between the different geometric properties, thereby leading to a bottleneck of geometric es

Sam Lin, Wenyue Hua, Zhenting Wang, Mingyu Jin

Cloud-based Large Language Models (LLMs) such as ChatGPT have become increasingly integral to daily operations. Nevertheless, they also introduce privacy concerns: firstly, numerous studies underscore the risks to user privacy posed by jailbreaking cloud-based LLMs; secondly, the LLM service providers have access to all user data, which deters individuals fr

Ergon Cugler de Moraes Silva

In the realm of statistical exploration, the manipulation of pseudo-random values to discern their impact on data distribution presents a compelling avenue of inquiry. This article investigates the question: Is it possible to add pseudo-random values without compelling a shift towards a normal distribution?. Employing Python techniques, the study explores th

Joshua Lackman

We formalize Feynman's construction of the quantum mechanical path integral. To do this, we shift the emphasis in differential geometry from the tangent bundle onto the pair groupoid. This allows us to use the van Est map and the piecewise linear structure of manifolds to develop a coordinate-free, partition of unity-free approach to integration of different

Xuandong Zhao, Lei Li, Yu-Xiang Wang

In this paper, we propose a new decoding method called Permute-and-Flip (PF) decoder. It enjoys stability properties similar to the standard sampling decoder, but is provably up to 2x better in its quality-stability tradeoff than sampling and never worse than any other decoder. We also design a cryptographic watermarking scheme analogous to Aaronson (2023)'s

Federico Bianchi, Patrick John Chia, Mert Yuksekgonul, Jacopo Tagliabue

Negotiation is the basis of social interactions; humans negotiate everything from the price of cars to how to share common resources. With rapidly growing interest in using large language models (LLMs) to act as agents on behalf of human users, such LLM agents would also need to be able to negotiate. In this paper, we study how well LLMs can negotiate with e

Bryan Perozzi, Bahare Fatemi, Dustin Zelle, Anton Tsitsulin

How can we best encode structured data into sequential form for use in large language models (LLMs)? In this work, we introduce a parameter-efficient method to explicitly represent structured data for LLMs. Our method, GraphToken, learns an encoding function to extend prompts with explicit structured information. Unlike other work which focuses on limited do

Ivana Balažević, Yuge Shi, Pinelopi Papalampidi, Rahma Chaabouni

Most transformer-based video encoders are limited to short temporal contexts due to their quadratic complexity. While various attempts have been made to extend this context, this has often come at the cost of both conceptual and computational complexity. We propose to instead re-purpose existing pre-trained video transformers by simply fine-tuning them to at

Mengya Xu, Mobarakol Islam, Long Bai, Hongliang Ren

Deep Neural Networks (DNNs) based semantic segmentation of the robotic instruments and tissues can enhance the precision of surgical activities in robot-assisted surgery. However, in biological learning, DNNs cannot learn incremental tasks over time and exhibit catastrophic forgetting, which refers to the sharp decline in performance on previously learned ta

Mohammed Muqeeth, Haokun Liu, Yufan Liu, Colin Raffel

Recently, there has been a widespread proliferation of "expert" language models that are specialized to a specific task or domain through parameter-efficient fine-tuning. How can we recycle large collections of expert language models to improve zero-shot generalization to unseen tasks? In this work, we propose Post-Hoc Adaptive Tokenwise Gating Over an Ocean

ATLAS Collaboration

This paper presents the reconstruction of missing transverse momentum ($p_{\text{T}}^{\text{miss}}$) in proton-proton collisions, at a center-of-mass energy of 13 TeV. This is a challenging task involving many detector inputs, combining fully calibrated electrons, muons, photons, hadronically decaying $\tau$-leptons, hadronic jets, and soft activity from rem

Nathan K Lysne, Justin F Niedermeyer, Andrew C Wilson, Daniel H Slichter

Excess "micromotion" of trapped ions due to the residual radio-frequency (rf) trapping field at their location is often undesirable and is usually carefully minimized. Here, we induce precise amounts of excess micromotion on individual ions by adjusting the local static electric field they experience. Micromotion modulates the coupling of an ion to laser fie

M. W. Healy-Kalesh, M. J. Darnley, E. J. Harvey, A. M. Newsam

The prototypical nova super-remnant (NSR) was uncovered around the most rapidly recurring nova (RN), M31N 2008-12a. Simulations of the growth of NSRs revealed that these large structures should exist around all novae, whether classical or recurrent. NSRs consist of large shell-like structures surrounding excavated cavities. Predictions, informed by these sim

Lê Thành Dũng Nguyên, Gabriele Vanoni

We investigate the tree-to-tree functions computed by "affine $\lambda$-transducers": tree automata whose memory consists of an affine $\lambda$-term instead of a finite state. They can be seen as variations on Gallot, Lemay and Salvati's Linear High-Order Deterministic Tree Transducers. When the memory is almost purely affine ($\textit{\`a la}$ Kanazawa), w

Marios-Nektarios Stamatopoulos, Avijit Banerjee, George Nikolakopoulos

This article introduces an experimental emulation of a novel chunk-based flexible multi-DoF aerial 3D printing framework. The experimental demonstration of the overall autonomy focuses on precise motion planning and task allocation for a UAV, traversing through a series of planned space-filling paths involved in the aerial 3D printing process without physica

L. Ya. Glozman

In this talk we overview main results indicating existence in QCD of three qualitatively different regimes connected by smooth crossovers upon heating: a hadron gas, a stringy fluid and a quark-gluon plasma. In the combined large N_c and chiral limit these regimes likely become distinct phases separated by phase transitions: a chiral restoration phase transi

Margalit Glasgow, Matthew Kwan, Ashwin Sah, Mehtaab Sawhney

In 1981, Karp and Sipser proved a law of large numbers for the matching number of a sparse Erd\H{o}s-R\'enyi random graph, in an influential paper pioneering the so-called differential equation method for analysis of random graph processes. Strengthening this classical result, and answering a question of Aronson, Frieze and Pittel, we prove a central limit t

Francesco Sannino

I review and improve on how two-index SU(N) gauge-fermion theories help access salient information about the large $N$ vacuum and spectrum of QCD, super Yang Mills and meson-meson scattering. The interplay with recent lattice simulations will be employed to deduce the size of $1/N^2$ corrections. Through the meson-meson scattering analysis I will honor Steve

Ryosuke Uematsu, Yoshihiro Ueda, Kotaro Kohno, Yoshiki Toba

Sub/millimeter galaxies are a key population for the study of galaxy evolution because the majority of star formation at high redshifts occurred in galaxies deeply embedded in dust. To search for this population, we have performed an extensive survey with ALMA, called the ALMA Lensing Cluster Survey (ALCS). This survey covers 133 arcmin^2 area and securely d

Mariusz Kwiatkowski, Andrzej Matraś, Mark Pankov, Adam Tyc

We consider the induced subgraph of the corresponding Grassmann graph formed by $q$-ary simplex codes of dimension $2$, $q\ge 5$. This graph contains precisely two types of maximal cliques. If $q=5$, then for any two maximal cliques of the same type there is a monomial linear automorphism transferring one of them to the other. Examples concerning the cases $

Yasheng Jin, Hong Ren, Cunhua Pan, Zhiyuan Yu

In this paper, we investigate an reconfigurable intelligent surface (RIS)-aided integrated sensing and communication (ISAC) system. Our objective is to maximize the achievable sum rate of the multi-antenna communication users through the joint active and passive beamforming. {Specifically}, the weighted minimum mean-square error (WMMSE) method is { first} us

Matthew Brookes, Craig Miller

Given a semigroup $S$, for each Green's relation $\mathcal{K}\in\{\mathcal{L},\mathcal{R},\mathcal{J},\mathcal{H}\}$ on $S,$ the $\mathcal{K}$-height of $S,$ denoted by $H_{\mathcal{K}}(S),$ is the height of the poset of $\mathcal{K}$-classes of $S.$ More precisely, if there is a finite bound on the sizes of chains of $\mathcal{K}$-classes of $S,$ then $H_{\

Imam Makhfudz, Mikhail Cherkasskii, Mohammad Alipourzadeh, Yaser Hajati

The possibility of quantum anomalous Hall effect (QAHE) in two-dimensional kagome systems with $d$-orbital electrons is studied within a multi-orbital tight-binding model. We concentrate on the case of isotropic Slater-Koster integrals which is realized in a recently discovered class of metal-organic frameworks TM$_3$C$_6$O$_6$ with transition metals (TM) in

Andrew Yiu

We study variants of the average treatment effect on the treated with population parameters replaced by their sample counterparts. For each estimand, we derive the limiting distribution with respect to a semiparametric efficient estimator of the population effect and provide guidance on variance estimation. Included in our analysis is the well-known sample a

Ida Ekmark, Mathias Hoppe, Tünde Fülöp, Patrik Jansson

When simulating runaway electron dynamics in tokamak disruptions, fluid models with lower numerical cost are often preferred to more accurate kinetic models. The aim of this work is to compare fluid and kinetic simulations of a large variety of different disruption scenarios in ITER. We consider both non-activated and activated scenarios; for the latter we d

Max Hausmann, Victor Chéron, Fabien Evrard, Berend van Wachem

The volume-filtering of the Navier-Stokes equations allows to consider the effect that particles have on the fluid without further assumptions, but closures arise of which the implications are not fully understood. In the present paper, we carefully study every closure in the volume-filtered fluid momentum equation and investigate their impact on the momentu

Jackie Grant

This review considers the Universities Superannuation Scheme (USS) valuations from 2014 to 2023. USS is a 70-80 billion GBP Defined Benefit pension scheme with over 500,000 members who are employed (or have been employed) at around 70 UK universities. Disputes over USS have led to a decade of industrial action. New results are presented showing the high depe

Hannes Stark, Bowen Jing, Chenyu Wang, Gabriele Corso

Discrete diffusion or flow models could enable faster and more controllable sequence generation than autoregressive models. We show that na\"ive linear flow matching on the simplex is insufficient toward this goal since it suffers from discontinuities in the training target and further pathologies. To overcome this, we develop Dirichlet flow matching on the

Farnaz Niknia, Ping Wang, Zixu Wang, Aakash Agarwal

This paper tackles the growing issue of excessive data transmission in networks. With increasing traffic, backhaul links and core networks are under significant traffic, leading to the investigation of caching solutions at edge routers. Many existing studies utilize Markov Decision Processes (MDP) to tackle caching problems, often assuming decision points at

Kshitij Sirohi, Daniel Büscher, Wolfram Burgard

The availability of a robust map-based localization system is essential for the operation of many autonomously navigating vehicles. Since uncertainty is an inevitable part of perception, it is beneficial for the robustness of the robot to consider it in typical downstream tasks of navigation stacks. In particular localization and mapping methods, which in mo

Gaston Nieuviarts

We present a connection between twisted spectral triples and pseudo-Riemannian spectral triples, rooted in the fundamental interplay between twists and Krein products. A concept of morphism of spectral triples is introduced, transforming one spectral triple into its dual. In the case of even-dimensional manifolds, we demonstrate how this construction impleme

Antoine Renard, Michel Rigo, Markus A. Whiteland

Gaussian binomial coefficients are q-analogues of the binomial coefficients of integers. On the other hand, binomial coefficients have been extended to finite words, i.e., elements of the finitely generated free monoids. In this paper we bring together these two notions by introducing q-analogues of binomial coefficients of words. We study their basic proper

Daniel Schiwietz, Marian Hörsting, Eva Maria Weig, Peter Degenfeld-Schonburg

Microelectromechanical systems (MEMS) gyroscopes are widely used in consumer and automotive applications. They have to fulfill a vast number of product requirements which lead to complex mechanical designs of the resonating structure. Arriving at a final design is a cumbersome process that relies heavily on human experience in conjunction with design optimiz

Sophie Marques, Luigi Pagano

In this paper, we present a functorial method to define ramification groups, identifying them as inertia groups of an induced action on composite jet algebras. This framework lays the foundation for defining higher ramification groups for actions involving group schemes. To achieve this, we introduce Taylor maps within the category of commutative unitary rin

Seongmin Lee, Marcel Böhme

The missing mass refers to the proportion of data points in an unknown population of classifier inputs that belong to classes not present in the classifier's training data, which is assumed to be a random sample from that unknown population. We find that in expectation the missing mass is entirely determined by the number $f_k$ of classes that do appear in t

Thomas Tony

A closed connected oriented Riemannian manifold $N$ with non-vanishing Euler characteristic, non-negative curvature operator and $0< 2\text{Ric}_N<\text{scal}_N$ is area-rigid in the sense that any area non-increasing spin map $f\colon M\to N$ from a closed connected oriented Riemannian manifold $M$ with non-vanishing $\hat{A}$-degree and $\text{scal}_M\geq

Mitodru Niyogi

Natural language (NL) to code suggestion systems assist developers in Integrated Development Environments (IDEs) by translating NL utterances into compilable code snippet. The current approaches mainly involve hard-coded, rule-based systems based on semantic parsing. These systems make heavy use of hand-crafted rules that map patterns in NL or elements in it

Pierre Koleják, Geoffrey Lezier, Daniel Vala, Baptiste Mathmann

Spintronic Terahertz Emitters (STE) represent a significant advancement in source technology, exploiting the ultrafast demagnetization process of spin-electrons to unveil a 30THz wide, gapless spectrum, accessible through femtosecond lasers across the full VIS-IR range. This innovation not only positions STEs as a pivotal advancement in THz source technology

Samuel Kováčik, Michaela Ďuríšková, Patrik Rusnák

The concept of a quantum structure underlying space has been proposed for quite some time, yet it has largely eluded direct observation. There is a prevailing notion that the minuscule effects stemming from quantum space could, under certain astronomical conditions, accumulate to an observable magnitude. Typically, these effects are perturbative, limited to

Sergey M. Zagorodnyuk

In this paper we study the generalized Bessel polynomials $y_n(x,a,b)$ (in the notation of Krall and Frink). Let $a>1$, $b\in(-1/3,1/3)\backslash\{ 0\}$. In this case we present the following positive continuous weights $p(\theta) = p(\theta,a,b)$ on the unit circle for $y_n(x,a,b)$: $$ 2\pi p(\theta,a,b) = -1 + 2(a-1) \int_0^1 e^{-bu\cos\theta} \cos(bu\sin\

Yanjun Zhao, Tian Zhou, Chao Chen, Liang Sun

Time series analysis is vital for numerous applications, and transformers have become increasingly prominent in this domain. Leading methods customize the transformer architecture from NLP and CV, utilizing a patching technique to convert continuous signals into segments. Yet, time series data are uniquely challenging due to significant distribution shifts a

Raymond Douglas, Jacek Karwowski, Chan Bae, Andis Draguns

There is increasing focus on adapting predictive models into agent-like systems, most notably AI assistants based on language models. We outline two structural reasons for why these models can fail when turned into agents. First, we discuss auto-suggestive delusions. Prior work has shown theoretically that models fail to imitate agents that generated the tra

Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange

Recent advancements in meta-learning have enabled the automatic discovery of novel reinforcement learning algorithms parameterized by surrogate objective functions. To improve upon manually designed algorithms, the parameterization of this learned objective function must be expressive enough to represent novel principles of learning (instead of merely recove

Xinbei Ma, Tianjie Ju, Jiyang Qiu, Zhuosheng Zhang

Large language models (LLMs) have played a pivotal role in building communicative AI, yet they encounter the challenge of efficient updates. Model editing enables the manipulation of specific knowledge memories and the behavior of language generation without retraining. However, the robustness of model editing remains an open question. This work seeks to und

Marzia Bisi, Silvia Lorenzani

In this work, we derive a system of Boltzmann-type equations to describe the spread of SARS-CoV-2 virus at the microscopic scale, that is by modeling the human-to-human mechanisms of transmission. To this end, we consider two populations, characterized by specific distribution functions, made up of individuals without symptoms (population $1$) and infected p

Age J. Tjalma, Pieter Rein ten Wolde

To successfully navigate chemical gradients, microorganisms need to predict how the ligand concentration changes in space. Due to their limited size, they do not take a spatial derivative over their body length but rather a temporal derivative, comparing the current signal with that in the recent past, over the so-called adaptation time. This strategy is per

Jeff Maki, Lorenzo Rosso, Leonardo Mazza, Alberto Biella

We show that two-body losses induce a collective excitation in a harmonically trapped one-dimensional Bose gas, even in the absence of a quench in the trap or any other external perturbation. Focusing on the dissipatively fermionized regime, we perform an exact mode expansion of the rapidity distribution function and characterize the emergence of the collect

Ziqing Ma, Wenwei Wang, Tian Zhou, Chao Chen

Accurate solar power forecasting is crucial to integrate photovoltaic plants into the electric grid, schedule and secure the power grid safety. This problem becomes more demanding for those newly installed solar plants which lack sufficient data. Current research predominantly relies on historical solar power data or numerical weather prediction in a single-

Ian M. Aberbach, Nicholas O Cox-Steib

In this paper we prove that the Watanabe-Yoshida conjecture holds up to dimension $7$. Our primary new tool is a function, $\varphi_J\left(R; z^t\right),$ that interpolates between the Hilbert-Kunz multiplicities of a base ring, $R$, and various radical extensions, $R_n$. We prove that this function is concave and show that it's rate of growth is related to

John D. Co-Reyes, Yingjie Miao, George Tucker, Aleksandra Faust

How to automatically design better machine learning programs is an open problem within AutoML. While evolution has been a popular tool to search for better ML programs, using learning itself to guide the search has been less successful and less understood on harder problems but has the promise to dramatically increase the speed and final performance of the o

César Díaz, Pablo Pérez, Julián Cabrera, Jaime Ruiz

A novel Key Quality Indicator for video delivery applications, XLR (piXel Loss Rate), is defined, characterized, and evaluated. The proposed indicator is an objective measure that captures the effects of transmission errors in the received video, has a good correlation with subjective Mean Opinion Scores, and provides comparable results with state-of-the-art

Hung-Chieh Fang, Nai-Xuan Ye, Yi-Jen Shih, Puyuan Peng

Recent advances in self-supervised speech models have shown significant improvement in many downstream tasks. However, these models predominantly centered on frame-level training objectives, which can fall short in spoken language understanding tasks that require semantic comprehension. Existing works often rely on additional speech-text data as intermediate

William Linz

Given integers $n > k > 0$, and a set of integers $L \subset [0, k-1]$, an \emph{$L$-system} is a family of sets $\mathcal{F} \subset \binom{[n]}{k}$ such that $|F \cap F'| \in L$ for distinct $F, F'\in \mathcal{F}$. $L$-systems correspond to independent sets in a certain generalized Johnson graph $G(n, k, L)$, so that the maximum size of an $L$-system is eq

Pouria Yazdian Anari, Fiona Obiezu, Nathan Lay, Fatemeh Dehghani Firouzabadi

Introduction This study explores the use of the latest You Only Look Once (YOLO V7) object detection method to enhance kidney detection in medical imaging by training and testing a modified YOLO V7 on medical image formats. Methods Study includes 878 patients with various subtypes of renal cell carcinoma (RCC) and 206 patients with normal kidneys. A total of

A. Bouley, C. Landim

We consider a one-dimensional gradient symmetric exclusion process in mild contact with boundary reservoirs. The hydrodynamic limit of the empirical measure is given by a non-linear second-order parabolic equation with non-linear Robin boundary conditions. We prove the dynamical large deviations principle.

Konstantin Y. Kalitin, Alexander A. Spasov, Olga Y. Mukha

Introduction: Kappa-opioid receptor (KOR) signaling in the basolateral amygdala (BLA) underlies KOR agonist-induced aversion. In this study, we aimed to understand the individual and combined effects of KOR agonist U-50488 and p38 MAPK inhibitor SB203580 on the spiking activity of pyramidal neurons in the BLA to shed light on the complex interplay between KO

Daniele Sepe, Susan Tolman

In this paper we study the connectedness of the fibers of integrable systems that extend complexity one $T$-spaces with proper moment maps, assuming that every tall singular point is non-degenerate. Our main result states that if there are no tall singular points with a hyperbolic block and connected $T$-stabilizer, then each fiber is connected. Moreover, we

Lingzhi Wang, Xingshan Zeng, Jinsong Guo, Kam-Fai Wong

This paper explores Machine Unlearning (MU), an emerging field that is gaining increased attention due to concerns about neural models unintentionally remembering personal or sensitive information. We present SeUL, a novel method that enables selective and fine-grained unlearning for language models. Unlike previous work that employs a fully reversed trainin

Sahil Kale, Gautam Khaire, Jay Patankar

Frequently Asked Questions (FAQs) refer to the most common inquiries about specific content. They serve as content comprehension aids by simplifying topics and enhancing understanding through succinct presentation of information. In this paper, we address FAQ generation as a well-defined Natural Language Processing task through the development of an end-to-e

Sophie W. Ding, Michael Haas, Xinghan Guo, Kazuhiro Kuruma

Quantum information technology offers the potential to realize unprecedented computational resources via secure channels capable of distributing entanglement between quantum computers. Diamond, as a host to atom-like defects with optically-accessible spin qubits, is a leading platform to realize quantum memory nodes needed to extend the reach of quantum link

Jerome Ramos, Hossen A. Rahmani, Xi Wang, Xiao Fu

Recent state-of-the-art recommender systems predominantly rely on either implicit or explicit feedback from users to suggest new items. While effective in recommending novel options, many recommender systems often use uninterpretable embeddings to represent user preferences. This lack of transparency not only limits user understanding of why certain items ar

Qingsen Yan, Yixu Feng, Cheng Zhang, Pei Wang

Low-Light Image Enhancement (LLIE) task tends to restore the details and visual information from corrupted low-light images. Most existing methods learn the mapping function between low/normal-light images by Deep Neural Networks (DNNs) on sRGB and HSV color space. Nevertheless, enhancement involves amplifying image signals, and applying these color spaces t

Zhiheng Xi, Wenxiang Chen, Boyang Hong, Senjie Jin

In this paper, we propose R$^3$: Learning Reasoning through Reverse Curriculum Reinforcement Learning (RL), a novel method that employs only outcome supervision to achieve the benefits of process supervision for large language models. The core challenge in applying RL to complex reasoning is to identify a sequence of actions that result in positive rewards a