May 2023 arXiv papers — page 86

Jakub Kowalski, Radosław Miernik

This paper concludes five years of AI competitions based on Legends of Code and Magic (LOCM), a small Collectible Card Game (CCG), designed with the goal of supporting research and algorithm development. The game was used in a number of events, including Community Contests on the CodinGame platform, and Strategy Card Game AI Competition at the IEEE Congress

Eszter Couillard, Philipp Czerner, Javier Esparza, Rupak Majumdar

We show that interactive protocols between a prover and a verifier, a well-known tool of complexity theory, can be used in practice to certify the correctness of automated reasoning tools. Theoretically, interactive protocols exist for all $\textsf{PSPACE}$ problems. The verifier of a protocol checks the prover's answer to a problem instance in probabilistic

Samir Khan, Martin Saveski, Johan Ugander

Off-policy evaluation (OPE) is the problem of estimating the value of a target policy using historical data collected under a different logging policy. OPE methods typically assume overlap between the target and logging policy, enabling solutions based on importance weighting and/or imputation. In this work, we approach OPE without assuming either overlap or

Yang You, Vincent Thomas, Francis Colas, Olivier Buffet

Decentralized partially observable Markov decision processes (Dec-POMDPs) formalize the problem of designing individual controllers for a group of collaborative agents under stochastic dynamics and partial observability. Seeking a global optimum is difficult (NEXP complete), but seeking a Nash equilibrium -- each agent policy being a best response to the oth

Paolo Bellingeri, Anthony Genevois, Neha Nanda

In this article, we show that, for every $n \geq 2$, the pure virtual twin group $PVT_n$ can be naturally described as a symmetric diagram group, a family of groups introduced by V. Guba and M. Sapir and associated to semigroup presentations. Inspired by this observation, we prove that every finitely generated right-angled Artin group is a symmetric diagram

Vojtech Liska, Tereza Zemankova, Vojtech Svak, Petr Jakl

Methods for controlling the motion of single particles, optically levitated in vacuum, have developed rapidly in recent years. The technique of cold damping makes use of feedback-controlled, electrostatic forces to increase dissipation without introducing additional thermal fluctuations. This process has been instrumental in the ground-state cooling of indiv

Benjamin Hsu, Anna Currey, Xing Niu, Maria Nădejde

Like many other machine learning applications, neural machine translation (NMT) benefits from over-parameterized deep neural models. However, these models have been observed to be brittle: NMT model predictions are sensitive to small input changes and can show significant variation across re-training or incremental model updates. This work studies a frequent

Cuong Tran, Ferdinando Fioretto

The Private Aggregation of Teacher Ensembles (PATE) is a machine learning framework that enables the creation of private models through the combination of multiple "teacher" models and a "student" model. The student model learns to predict an output based on the voting of the teachers, and the resulting model satisfies differential privacy. PATE has been sho

Ricardo Rei, Nuno M. Guerreiro, Marcos Treviso, Luisa Coheur

Neural metrics for machine translation evaluation, such as COMET, exhibit significant improvements in their correlation with human judgments, as compared to traditional metrics based on lexical overlap, such as BLEU. Yet, neural metrics are, to a great extent, "black boxes" returning a single sentence-level score without transparency about the decision-makin

Franco Pellegrini, Ruggero Lot, Yusuf Shaidu, Emine Küçükbenli

We present the latest release of PANNA 2.0 (Properties from Artificial Neural Network Architectures), a code for the generation of neural network interatomic potentials based on local atomic descriptors and multilayer perceptrons. Built on a new back end, this new release of PANNA features improved tools for customizing and monitoring network training, bette

Peter Breiding, Marco Chiaberge, Erini Lambrides, Eileen T. Meyer

While supermassive black holes are ubiquitous features of galactic nuclei, only a small minority are observed during episodes of luminous accretion. The physical mechanism(s) driving the onset of fueling and ignition in these active galactic nuclei (AGN) are still largely unknown for many galaxies and AGN-selection criteria. Attention has focused on AGN trig

Christopher Shriver

Recent work of Barbieri and Meyerovitch has shown that, for very general spin systems indexed by sofic groups, equilibrium (i.e. pressure-maximizing) states are Gibbs. The main goal of this paper is to show that the converse fails in an interesting way: for the Ising model on a free group, the free-boundary state can fail to be equilibrium as long as it is n

Ke Huang, Xiao Li

In this work we propose a new scheme to engineer subharmonic responses via scar states in a generalized PXP model. We first show that the generalized PXP model also possesses a band of scar states like the pristine PXP model does. In addition, we reveal that a generalized forward scattering approximation (FSA) still works for these scar states. We further ar

Natalia Cardona-Tobón, Arturo Jaramillo, Sandra Palau

A Galton-Watson process in a varying environment is a discrete time branching process where the offspring distributions vary among generations. It is known that in the critical case, these processes have a Yaglom limit, that is, a suitable normalization of the process conditioned on non-extinction converges in distribution to a standard exponential random va

Jesse Campion Loth, Michael Levet, Kevin Liu, Sheila Sundaram

In this paper, we consider the moments of statistics on conjugacy classes of the colored permutation groups $\mathfrak{S}_{n,r}=\mathbb{Z}_r\wr \mathfrak{S}_n$. We first show that any fixed moment coincides on all conjugacy classes where all cycles have sufficiently long length. Additionally, for permutation statistics that can be realized via a process we c

Victor Medina-Olivares, Raffaella Calabrese

This paper examines whether repeated payday loan use, commonly known as the debt trap, harms borrowers' financial wellbeing. Using Open Banking data from 1,815 UK borrowers observed between 2017 and 2018, we model borrowing intensity using a two-state hidden Markov model (HMM). The HMM outperforms single-regime alternatives and identifies two distinct borrow

Corentin Léna, Jonathan Rohleder

We prove sharp upper bounds for the first and second non-trivial eigenvalues of the Neumann Laplacian in two classes of domains: parallelograms and domains of constant width. This gives in particular a new proof of an isoperimetric inequality for parallelograms recently obtained by A. Henrot, A. Lemenant and I. Lucardesi.

Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li

We provide the first polynomial-time convergence guarantees for the probability flow ODE implementation (together with a corrector step) of score-based generative modeling. Our analysis is carried out in the wake of recent results obtaining such guarantees for the SDE-based implementation (i.e., denoising diffusion probabilistic modeling or DDPM), but requir

Xhek Turkeshi, Marco Schirò, Piotr Sierant

Universal quantum computing requires nonstabilizer (magic) quantum states. Quantifying the nonstabilizerness and relating it to other quantum resources is vital for characterizing the complexity of quantum many-body systems. In this work, we prove that a quantum state is a stabilizer if and only if all states belonging to its Clifford orbit have a flat proba

Joel N. Johnson, Danielle R. Haverkamp, Yi-Hsin Ou, Khanh Kieu

In recent years, optical control of mechanical oscillators has emerged as a critical tool for everything from information processing to laser cooling. While traditional forms of optomechanical cooling utilize systems comprised of discrete optical and mechanical modes, it has recently been shown that cooling can be achieved in a chip-based system that possess

Lydia Abady, Giovanna Maria Dimitri, Mauro Barni

The highly realistic image quality achieved by current image generative models has many academic and industrial applications. To limit the use of such models to benign applications, though, it is necessary that tools to conclusively detect whether an image has been generated synthetically or not are developed. For this reason, several detectors have been dev

Eugenio Pozzoli

We consider a bilinear control problem for the wave equation on a torus of arbitrary dimension. We show that the system is globally approximately controllable in arbitrarily small times from a dense family of initial states. The control strategy is explicit, and based on a small-time limit of conjugated dynamics to move along non-directly accessible directio

Maxim Emelin, Stefano Massai

We study the dynamics of certain string configurations in a class of fivebrane supertube backgrounds. In the decoupling limit of the fivebranes, these solutions are known to admit an exact description in worldsheet string theory and string propagation is integrable. For the asymptotically flat solutions, we prove, by using analytic tools of classical Hamilto

Hongru Wang, Rui Wang, Fei Mi, Yang Deng

Large Language Models (LLMs), such as \texttt{ChatGPT}, greatly empower dialogue systems with strong language understanding and generation capabilities. However, most of the previous works prompt the LLMs to directly generate a response based on the dialogue context, overlooking the underlying linguistic cues about the user status exhibited in the context. S

Huiming Wang, Liying Cheng, Wenxuan Zhang, De Wen Soh

Recently, data augmentation (DA) methods have been proven to be effective for pre-trained language models (PLMs) in low-resource settings, including few-shot named entity recognition (NER). However, conventional NER DA methods are mostly aimed at sequence labeling models, i.e., token-level classification, and few are compatible with unified autoregressive ge

Mayank Mishra, Prince Kumar, Riyaz Bhat, Rudra Murthy

Prompting with natural language instructions has recently emerged as a popular method of harnessing the capabilities of large language models. Given the inherent ambiguity present in natural language, it is intuitive to consider the possible advantages of prompting with less ambiguous prompt styles, such as the use of pseudo-code. In this paper we explore if

Masahiro Kaneko, Graham Neubig, Naoaki Okazaki

Humans work together to solve common problems by having discussions, explaining, and agreeing or disagreeing with each other. Similarly, if a system can have discussions with humans when solving tasks, it can improve the system's performance and reliability. In previous research on explainability, it has only been possible for the system to make predictions

Jingfeng Wu, Vladimir Braverman, Jason D. Lee

Recent research has observed that in machine learning optimization, gradient descent (GD) often operates at the edge of stability (EoS) [Cohen, et al., 2021], where the stepsizes are set to be large, resulting in non-monotonic losses induced by the GD iterates. This paper studies the convergence and implicit bias of constant-stepsize GD for logistic regressi

Mohammad Hussein, Agnes Angerud, Jordi Saez, Evelien Bogaert

Robust fine tuning of multi-leaf collimator (MLC) Treatment Planning System (TPS) modeling parameters is crucial for creating an optimal beam model, particularly with the ever-increasing accuracy required for advancing techniques. Challenges arise from balancing the trade-off between multiple parameters and therefore the quality of tuning depends on the expe

S. P. de Alwis

We revisit the formalism for tunneling in quantum field theory developed by Coleman and collaborators. In particular using the generalization of WKB methods for tunneling in quantum mechanics we avoid the problems with negative eigenvalues and convexity issues associated with Coleman's approach. While the exponential factor is the same, we find differences i

George Manolakos, Pantelis Manousselis, Danai Roumelioti, Stelios Stefas

Here we present an overview on the various works, in which many collaborators have contributed, regarding the interesting dipole of noncommutativity and physics. In brief, we present the features that noncommutativity triggers both in the fields of gravity and particle physics, from a matrix-realized perspective, with the notion of noncommutative gauge theor

Gaylor Wafflard-Fernandez, Geoffroy Lesur

Models of planet-disk interaction are mainly based on 2D and 3D viscous hydrodynamical simulations. Accretion is classically prescribed by an alpha parameter which characterizes the turbulent radial transport of angular momentum (AM) in the disk. This accretion scenario has been questioned for a few years and an alternative paradigm has been proposed that in

Filip Broćić, Dylan Cant

For each representative $\mathfrak{B}$ of a bordism class in the free loop space of a manifold, we associate a moduli space of finite length Floer cylinders in the cotangent bundle. The left end of the Floer cylinder is required to be a lift of one of the loops in $\mathfrak{B}$, and the right end is required to lie on the zero section. Under certain assumpt

Mingxuan Li, Yen Hang Zhou, Liemin Li, Yao Jiang

Visuotactile sensing technology has received much attention in recent years. This article proposes a feature detection method applicable to visuotactile sensors based on continuous marker patterns (CMP) to measure 3-d deformation. First, we construct the feature model of checkerboard-like corners under contact deformation, and design a novel double-layer cir

Qingkai Shi, Junyang Shao, Yapeng Ye, Mingwei Zheng

Inferring protocol formats is critical for many security applications. However, existing format-inference techniques often miss many formats, because almost all of them are in a fashion of dynamic analysis and rely on a limited number of network packets to drive their analysis. If a feature is not present in the input packets, the feature will be missed in t

Huitong Pan, Qi Zhang, Eduard Dragut, Cornelia Caragea

The recognition of dataset names is a critical task for automatic information extraction in scientific literature, enabling researchers to understand and identify research opportunities. However, existing corpora for dataset mention detection are limited in size and naming diversity. In this paper, we introduce the Dataset Mentions Detection Dataset (DMDD),

Andrea Schioppa, Xavier Garcia, Orhan Firat

The recent rapid progress in pre-training Large Language Models has relied on using self-supervised language modeling objectives like next token prediction or span corruption. On the other hand, Machine Translation Systems are mostly trained using cross-lingual supervision that requires aligned data between source and target languages. We demonstrate that pr

Maria Aloni, Aleksi Anttila, Fan Yang

We study the mathematical properties of bilateral state-based modal logic (BSML), a modal logic employing state-based semantics (also known as team semantics), which has been used to account for free choice inferences and related linguistic phenomena. This logic extends classical modal logic with a nonemptiness atom which is true in a state if and only if th

Allen Weitsman

We give the lower bound for the growth of the maximum value for a solution to the minimal surface equation with 0 boundary values over an unbounded simply connected domain.

Rinku Maji, Wan-Il Park, Qaisar Shafi

We explore the gravitational wave spectrum generated by string-wall structures in an $SO(10)$ ($Spin(10)$) based scenario of pseudo-Goldstone boson dark matter (pGDM) particle. This dark matter candidate is a linear combination of the Standard Model (SM) singlets present in the 126 and 16 dimensional Higgs fields. The Higgs $126$-plet vacuum expectation valu

Ben Tu, Nikolas Kantas, Robert M. Lee, Behrang Shafei

The goal of multi-objective optimisation is to identify a collection of points which describe the best possible trade-offs between the multiple objectives. In order to solve this vector-valued optimisation problem, practitioners often appeal to the use of scalarisation functions in order to transform the multi-objective problem into a collection of single-ob

Mohsen Dastpak, Fausto Errico, Ola Jabali, Federico Malucelli

We study EVs traveling from origin to destination in the shortest time, focusing on long-distance settings with energy requirements exceeding EV autonomy. The EV may charge its battery at public Charging Stations (CSs), which are subject to uncertain waiting times. We model CSs using appropriately defined queues, whose status is revealed upon the EV arrival.

Aran Nayebi, Rishi Rajalingham, Mehrdad Jazayeri, Guangyu Robert Yang

Humans and animals have a rich and flexible understanding of the physical world, which enables them to infer the underlying dynamical trajectories of objects and events, plausible future states, and use that to plan and anticipate the consequences of actions. However, the neural mechanisms underlying these computations are unclear. We combine a goal-driven m

Stefano Gherardini, Lorenzo Buffoni, Nicolò Defenu

Quasi-static transformations, or slow quenches, of many-body quantum systems across quantum critical points create topological defects. The Kibble-Zurek mechanism regulates the appearance of defects in a local quantum system through a classical combinatorial process. However, long-range interactions disrupt the conventional Kibble-Zurek scaling and lead to a

Michael Bate, Benjamin Martin, Gerhard Roehrle

Given a semisimple linear algebraic $k$-group $G$, one has a spherical building $\Delta_G$, and one can interpret the geometric realisation $\Delta_G(\mathbb R)$ of $\Delta_G$ in terms of cocharacters of $G$. The aim of this paper is to extend this construction to the case when $G$ is an arbitrary connected linear algebraic group; we call the resulting objec

Zikang Liu, Sihan Chen, Longteng Guo, Handong Li

Large pre-trained multimodal models have demonstrated significant success in a range of downstream tasks, including image captioning, image-text retrieval, visual question answering (VQA), etc. However, many of these methods rely on image-text pairs collected from the web as pre-training data and unfortunately overlook the need for fine-grained feature align

Yu Zhao, Hao Fei, Wei Ji, Jianguo Wei

Visual spatial description (VSD) aims to generate texts that describe the spatial relations of the given objects within images. Existing VSD work merely models the 2D geometrical vision features, thus inevitably falling prey to the problem of skewed spatial understanding of target objects. In this work, we investigate the incorporation of 3D scene features f

Ryotaro Kosuge

The Chillingworth subgroup of the mapping class group of a compact oriented surface of genus $g$ with one boundary component is defined as the subgroup whose elements preserve nonvanishing vector fields on the surface up to homotopy. In this work, we determine the rational abelianization of the Chillingworth subgroup as a full mapping class group module. The

Stefan Klus, Maia Trower

Graphs and networks play an important role in modeling and analyzing complex interconnected systems such as transportation networks, integrated circuits, power grids, citation graphs, and biological and artificial neural networks. Graph clustering algorithms can be used to detect groups of strongly connected vertices and to derive coarse-grained models. We d

Aravind Gollakota, Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan

We give the first tester-learner for halfspaces that succeeds universally over a wide class of structured distributions. Our universal tester-learner runs in fully polynomial time and has the following guarantee: the learner achieves error $O(\mathrm{opt}) + \epsilon$ on any labeled distribution that the tester accepts, and moreover, the tester accepts whene

Takashi Arima, Tommaso Ruggeri, Masaru Sugiyama

We present a complete analysis of the dispersion relations for longitudinal and transverse waves in a rarefied polyatomic gas based on Rational Extended Thermodynamics (RET), which describes the evolution of a non-polytropic gas in nonequilibrium. Observability of the second mode of the longitudinal wave and the transverse wave is discussed although these wa

Daniel W. Cranston, Gexin Yu

Hocquard, Kim, and Pierron constructed, for every even integer $D\ge 2$, a 2-degenerate graph $G_D$ with maximum degree $D$ such that $\omega(G_D^2)=\frac52D$. We prove for (a) all 2-degenerate graphs $G$ and (b) all graphs $G$ with $\mbox{mad}(G)<4$, upper bounds on the clique number $\omega(G^2)$ of $G^2$ that match the lower bound given by this constructi

Bruce Olberding, Elaine A. Walker

Working over a field of characteristic other than $2$, we examine a relationship between quadrilaterals and the pencil of conics passing through their vertices. Asymptotically, such a pencil of conics is what we call a bisector field, a set ${\mathbb{B}}$ of paired lines such that each line $\ell$ in ${\mathbb{B}}$ simultaneously bisects each pair in ${\math

Michel Meneses, Bruno Iwami

Modern approaches for keyword spotting rely on training deep neural networks on large static datasets with i.i.d. distributions. However, the resulting models tend to underperform when presented with changing data regimes in real-life applications. This work investigates a simple but effective online continual learning method that updates a keyword spotter o

Javier García Gilabert, Carlos Escolano, Marta R. Costa-Jussà

Our proposed method, ReSeTOX (REdo SEarch if TOXic), addresses the issue of Neural Machine Translation (NMT) generating translation outputs that contain toxic words not present in the input. The objective is to mitigate the introduction of toxic language without the need for re-training. In the case of identified added toxicity during the inference process,

Francesco Giovanni Celiberto, Michael Fucilla, Dmitry Yu. Ivanov, Mohammed M. A. Mohammed

It has been recently argued that the inclusive hadroproduction at the LHC of a Higgs boson in association with a jet can be sensitive to the high-energy dynamics. Moreover, the impact of the resummation at FCC energies is expected to be large also in the inclusive cross section for the main Higgs production channel in proton-proton collisions, namely the glu

Mustafa Safa Ozdayi, Charith Peris, Jack FitzGerald, Christophe Dupuy

Large Language Models (LLMs) are known to memorize significant portions of their training data. Parts of this memorized content have been shown to be extractable by simply querying the model, which poses a privacy risk. We present a novel approach which uses prompt-tuning to control the extraction rates of memorized content in LLMs. We present two prompt tra

Orhan Aygün, Bertan Turhan

The over-and-above choice rule is the prominent selection procedure to implement affirmative action. In India, it is legally mandated to allocate public school seats and government job positions. This paper presents an axiomatic characterization of the over-and-above choice rule by rigorously stating policy goals as formal axioms. Moreover, we characterize t

Athmakoori Prashant, S. Francis Raj, M. Gokulnath

Finding families that admit a linear $\chi$-binding function is a problem that has interested researchers for a long time. Recently, the question of finding linear subfamilies of $2K_2$-free graphs has garnered much attention. In this paper, we are interested in finding a linear subfamily of a specific superclass of $2K_2$-free graphs, namely $(P_3\cup P_2)$

Ana Alonso-Serrano, Marek Liška

The thermodynamics of local causal horizons has been shown to imply gravitational dynamics. In this essay, we discuss the principles underlying this observation, and its significance in our understanding of (quantum) gravity. We also show why the local thermodynamic methods cannot by themselves recover general relativity. Instead, they lead to the so-called

Mohamed Amine Chatti, Mouadh Guesmi, Arham Muslim

Providing system-generated explanations for recommendations represents an important step towards transparent and trustworthy recommender systems. Explainable recommender systems provide a human-understandable rationale for their outputs. Over the last two decades, explainable recommendation has attracted much attention in the recommender systems research com

Caspar Groiseau, Antonio I. Fernández-Domínguez, Diego Martín-Cano, Carlos Sánchez Muñoz

We present a proposal for a tunable source of single photons operating in the terahertz (THz) regime. This scheme transforms incident visible photons into quantum THz radiation by driving a single polar quantum emitter with an optical laser, with its permanent dipole enabling dressed THz transitions enhanced by the resonant coupling to a cavity. This mechani

G. F. Benedict, B. E. McArthur, E. P. Nelan, J. L. Bean

We combine Hubble Space Telescope (HST) Fine Guidance Sensor, Hipparcos, and Gaia DR3 astrometric observations of the K0 V star 14 Her with the results of an analysis of extensive ground-based radial velocity data to determine perturbation orbits and masses for two previously known companions, 14 Her b and c. Radial velocities obtained with the Hobby-Eberly

Xuechun Xu, Joakim Jaldén

Inferring a state sequence from a sequence of measurements is a fundamental problem in bioinformatics and natural language processing. The Viterbi and the Beam Search (BS) algorithms are popular inference methods, but they have limitations when applied to Hierarchical Hidden Markov Models (HHMMs), where the interest lies in the outer state sequence. The Vite

Alberto González-Sanz, Marc Hallin, Bodhisattva Sen

The contribution of this work is twofold. The first part deals with a Hilbert-space version of McCann's celebrated result on the existence and uniqueness of monotone measure-preserving maps: given two probability measures $\rm P$ and $\rm Q$ on a separable Hilbert space $\mathcal{H}$ where $\rm P$ does not give mass to "small sets" (namely, Lipschitz hypersu

John A. Schneeloch, Luke Daemen, Despina Louca

Van der Waals (vdW) Dirac magnon system CrI$_3$, a potential host of topological edge magnons, orders ferromagnetically (FM) (T$_C=61$ K) in the bulk, but antiferromagnetic (AFM) order has been observed in nanometer thick flakes, attributed to monoclinic (M) type stacking. We report neutron scattering measurements on a powder sample where the usual transitio

Hao Li, Hao Lin, Guanghui Wang, Wenling Zhou

The uniform Tur\'an density $\pi_{1}(F)$ of a $3$-uniform hypergraph $F$ is the supremum over all $d$ for which there is an $F$-free hypergraph with the property that every linearly sized subhypergraph with density at least $d$. Determining $\pi_{1}(F)$ for given hypergraphs $F$ was suggested by Erd\H{o}s and S\'os in 1980s. In particular, they raised the qu

Jorge Blanco, Stephanie Einstein, Caleb Hostetler, Jurgen Kritschgau

The zero forcing number was introduced as a combinatorial bound on the maximum nullity taken over the set of real symmetric matrices that respect the pattern of an underlying graph. The $Z_q$-forcing game is an analog to the standard zero forcing game which incorporates inertia restrictions on the set of matrices associated with a graph. This work proves an

Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, Jian-Yun Nie

Large language models (LLMs), such as ChatGPT, are prone to generate hallucinations, i.e., content that conflicts with the source or cannot be verified by the factual knowledge. To understand what types of content and to which extent LLMs are apt to hallucinate, we introduce the Hallucination Evaluation benchmark for Large Language Models (HaluEval), a large

David Dale, Elena Voita, Janice Lam, Prangthip Hansanti

Hallucinations in machine translation are translations that contain information completely unrelated to the input. Omissions are translations that do not include some of the input information. While both cases tend to be catastrophic errors undermining user trust, annotated data with these types of pathologies is extremely scarce and is limited to a few high

Jong Woong Park, Young-Kwang Jung, Aron Walsh

Thermoelectric devices can directly convert waste heat into electricity, which makes them an important clean energy technology. The underlying materials performance can be evaluated by the dimensionless figure of merit ZT. Metal halides are attractive candidates due to their chemical flexibility and ease of processing; however, the maximum ZT realized (ZT =

Revanth Gangi Reddy, Pradeep Dasigi, Md Arafat Sultan, Arman Cohan

Retrieve-and-rerank is a prevalent framework in neural information retrieval, wherein a bi-encoder network initially retrieves a pre-defined number of candidates (e.g., K=100), which are then reranked by a more powerful cross-encoder model. While the reranker often yields improved candidate scores compared to the retriever, its scope is confined to only the

Dimitra Kosta, Apostolos Thoma, Marius Vladoiu

To every simple toric ideal $I_T$ one can associate the strongly robust simplicial complex $\Delta _T$, which determines the strongly robust property for all ideals that have $I_T$ as their bouquet ideal. We show that for the simple toric ideals of monomial curves in $\mathbb{A}^{s}$, the strongly robust simplicial complex $\Delta _T$ is either $\{\emptyset

Xuesong Ye, Jun Wu, Chengjie Mou, Weinan Dai

Monitoring the health status of patients and predicting mortality in advance is vital for providing patients with timely care and treatment. Massive medical signs in electronic health records (EHR) are fitted into advanced machine learning models to make predictions. However, the data-quality problem of original clinical signs is less discussed in the litera

Jan-Christoph Kassing, Jürgen Giesl

Dependency pairs are one of the most powerful techniques to analyze termination of term rewrite systems (TRSs) automatically. We adapt the dependency pair framework to the probabilistic setting in order to prove almost-sure innermost termination of probabilistic TRSs. To evaluate its power, we implemented the new framework in our tool AProVE.

Maíra Cesário Alvim Lobo, Débora Peres Menezes

In the present work we use the vector MIT bag model to describe quark matter and obtain the macroscopic properties of neutron stars. We also calculate the speed of sound of quark matter described by this model with specific parameter values and check if the results obey the conformal limit at high densities. We have seen that the vector MIT bag model produce

Tuomas Eerola, Daniel Batrakhanov, Nastaran Vatankhah Barazandeh, Kaisa Kraft

Planktonic organisms are key components of aquatic ecosystems and respond quickly to changes in the environment, therefore their monitoring is vital to understand the changes in the environment. Yet, monitoring plankton at appropriate scales still remains a challenge, limiting our understanding of functioning of aquatic systems and their response to changes.

Zhibin Gou, Zhihong Shao, Yeyun Gong, Yelong Shen

Recent developments in large language models (LLMs) have been impressive. However, these models sometimes show inconsistencies and problematic behavior, such as hallucinating facts, generating flawed code, or creating offensive and toxic content. Unlike these models, humans typically utilize external tools to cross-check and refine their initial content, lik

Tommaso Russo, Jacopo Somaglia

We investigate the question whether a scattered compact topological space $K$ such that $C(K)$ has a norming Markushevich basis (M-basis, for short) must be Eberlein. This question originates from the recent solution, due to H\'ajek, Todor\v{c}evi\'c, and the authors, to an open problem from the Nineties, due to Godefroy. Our prime tool consists in proving t

Bailey Flanigan, Ariel D. Procaccia, Sven Wang

A key promise of democratic voting is that, by accounting for all constituents' preferences, it produces decisions that benefit the constituency overall. It is alarming, then, that all deterministic voting rules have unbounded distortion: all such rules - even under reasonable conditions - will sometimes select outcomes that yield essentially no value for co

Taras Lukashiv, Igor V. Malyk, Maryna Chepeleva, Petr V. Nazarov

This article aims to investigate sufficient conditions for the stability of stochastic differential equations with a random structure, particularly in contexts involving the presence of concentration points. The proof of asymptotic stability leverages the use of Lyapunov functions, supplemented by additional constraints on the magnitudes of jumps and jump ti

Nikhil Gupt, Shuvadip Ghosh, Arnab Ghosh

We introduce a top-ranked cycle flux ranking scheme of network analysis to assess the performance of molecular junction solar cells. By mapping the Lindblad master equation to the quantum-transition network, we propose a microscopic Hamiltonian description underpinning the rate equations commonly used to characterize molecular photocells. Our approach elucid

Q. Chen

In the present paper we shall obtain a result on the image of polynomials with zero constant term on upper triangular matrix algebras over an algebraically closed field. This is a supplement to a result obtained by Panja and Prasad recently.

Rishad Shafik, Tousif Rahman, Adrian Wheeldon, Ole-Christoffer Granmo

Energy efficiency is a crucial requirement for enabling powerful artificial intelligence applications at the microedge. Hardware acceleration with frugal architectural allocation is an effective method for reducing energy. Many emerging applications also require the systems design to incorporate interpretable decision models to establish responsibility and t

Mengke Li, Yiu-ming Cheung, Yang Lu

Long-tailed data is still a big challenge for deep neural networks, even though they have achieved great success on balanced data. We observe that vanilla training on long-tailed data with cross-entropy loss makes the instance-rich head classes severely squeeze the spatial distribution of the tail classes, which leads to difficulty in classifying tail class

Jiyang Tang, William Chen, Xuankai Chang, Shinji Watanabe

Aphasia is a language disorder that affects the speaking ability of millions of patients. This paper presents a new benchmark for Aphasia speech recognition and detection tasks using state-of-the-art speech recognition techniques with the AphsiaBank dataset. Specifically, we introduce two multi-task learning methods based on the CTC/Attention architecture to

Sameer Murthy

The study of black holes in string theory has led to the discovery of deep and surprising connections between black holes and modular forms -- which are two classical, a priori unrelated, subjects. This article explains the main physical and mathematical ideas behind these connections. It is known from the pioneering work of J.Bekenstein and S.Hawking in the

Mohammad Dehghani, Heshaam Faili

Spelling correction is a remarkable challenge in the field of natural language processing. The objective of spelling correction tasks is to recognize and rectify spelling errors automatically. The development of applications that can effectually diagnose and correct Persian spelling and grammatical errors has become more important in order to improve the qua

Seamus P. Albion, Ilse Fischer, Hans Höngesberg, Florian Schreier-Aigner

The skew Schur functions admit many determinantal expressions. Chief among them are the (dual) Jacobi-Trudi formula and the Lascoux-Pragacz formula, which is a skew analogue of the Giambelli identity. Comparatively, the skew characters of the symplectic and orthogonal groups, also known as the skew symplectic and orthogonal Schur functions, have received les

Ioanna Diamanti, Antigoni Tsiami, Petros Koutras, Petros Maragos

We introduce ViDaS, a two-stream, fully convolutional Video, Depth-Aware Saliency network to address the problem of attention modeling ``in-the-wild", via saliency prediction in videos. Contrary to existing visual saliency approaches using only RGB frames as input, our network employs also depth as an additional modality. The network consists of two visual s

Zahra Tabatabaei, Adrian Colomer, Javier Oliver Moll, Valery Naranjo

Digital pathology has revolutionized cancer diagnosis by leveraging Content-Based Medical Image Retrieval (CBMIR) for analyzing histopathological Whole Slide Images (WSIs). CBMIR enables searching for similar content, enhancing diagnostic reliability and accuracy. In 2020, breast and prostate cancer constituted 11.7% and 14.1% of cases, respectively, as repo

Francesc Lluís, Nils Meyer-Kahlen, Vasileios Chatziioannou, Alex Hofmann

Ambisonics is a scene-based spatial audio format that has several useful features compared to object-based formats, such as efficient whole scene rotation and versatility. However, it does not provide direct access to the individual source signals, so that these have to be separated from the mixture when required. Typically, this is done with linear spherica

Yibo Wang, Wenhao Yang, Wei Jiang, Shiyin Lu

Projection-free online learning has drawn increasing interest due to its efficiency in solving high-dimensional problems with complicated constraints. However, most existing projection-free online methods focus on minimizing the static regret, which unfortunately fails to capture the challenge of changing environments. In this paper, we investigate non-stati

Fangyu Lei, Xiang Li, Yifan Wei, Shizhu He

Answering multi-hop questions over hybrid factual knowledge from the given text and table (TextTableQA) is a challenging task. Existing models mainly adopt a retriever-reader framework, which have several deficiencies, such as noisy labeling in training retriever, insufficient utilization of heterogeneous information over text and table, and deficient abilit

Koushik Chatterjee, Zsuzsanna Koczor-Benda, Xintian Feng, Anna I. Krylov

We present the theory for the evaluation of non-adiabatic couplings (NACs) involving resonance states within the complex absorbing potential equation-of-motion coupled-cluster (CAP-EOM-CC) framework implemented within the singles and doubles approximation. Resonance states are embedded in the continuum and undergo rapid decay through autodetachment. In addit

Bernard S. Kay

Hawking showed that a black hole formed by collapse will emit radiation and eventually disappear. We address the challenge to define an objective notion of physical entropy which increases throughout this process in a way consistent with unitarity. We have suggested that (instead of coarse-grained entropy) physical entropy is matter-gravity entanglement entr

Joseph Lahoud Sleiman, Filippo Conforto, Yair Augusto Gutierrez Fosado, Davide Michieletto

Knots are deeply entangled with every branch of science. One of the biggest open challenges in knot theory is to formalise a knot invariant that can unambiguously and efficiently distinguish any two knotted curves. Additionally, the conjecture that the geometrical embedding of a curve encodes information on its underlying topology is, albeit physically intui

Kun Ding, Haoshen Ye, Changyuan Su, Yu-An Xiong

Abundant chemical diversity and structural tunability make organic-inorganic hybrid perovskites (OIHPs) a rich ore for ferroelectrics. However, compared with their inorganic counterparts such as BaTiO$_3$, their ferroelectric key properties, including large spontaneous polarization ($P_s$), low coercive field ($E_c$), and strong second harmonic generation (S

Ben Craig, Peter Townsend, Carlos Ponce de Leon, Chris Kriton-Skylaris

The conducting polymer poly(3,4-ethylenedioxythiophene) (PEDOT) is one of the most researched materials. The 1980s bipolaron model remains the dominant interpretation of the electronic structure of PEDOT. Recent theoretical studies have provided updated definitions of key concepts such as bipolarons or polaron pairs, but these have not yet become widely know

Shengqiong Wu, Hao Fei, Yixin Cao, Lidong Bing

Existing research on multimodal relation extraction (MRE) faces two co-existing challenges, internal-information over-utilization and external-information under-exploitation. To combat that, we propose a novel framework that simultaneously implements the idea of internal-information screening and external-information exploiting. First, we represent the fine-