October 2023 arXiv papers — page 60

Pengfei Sun, Jibin Wu, Malu Zhang, Paul Devos

Recurrent Neural Networks (RNNs) are widely recognized for their proficiency in modeling temporal dependencies, making them highly prevalent in sequential data processing applications. Nevertheless, vanilla RNNs are confronted with the well-known issue of gradient vanishing and exploding, posing a significant challenge for learning and establishing long-rang

Wei-Lin Chen, Cheng-Kuang Wu, Hsin-Hsi Chen, Chung-Chi Chen

In this paper, we address the hallucination problem commonly found in natural language generation tasks. Language models often generate fluent and convincing content but can lack consistency with the provided source, resulting in potential inaccuracies. We propose a new decoding method called Fidelity-Enriched Contrastive Search (FECS), which augments the co

Kevin LoGrande, M. Ravi Shankar, Kaushik Dayal

Liquid Crystalline Elastomers (LCEs) are active materials that are of interest due to their programmable response to various external stimuli such as light and heat. When exposed to these stimuli, the anisotropy in the response of the material is governed by the nematic director, which is a continuum parameter that is defined as the average local orientation

Xinpeng Wang, Barbara Plank

Label aggregation such as majority voting is commonly used to resolve annotator disagreement in dataset creation. However, this may disregard minority values and opinions. Recent studies indicate that learning from individual annotations outperforms learning from aggregated labels, though they require a considerable amount of annotation. Active learning, as

Qu Yang, Malu Zhang, Jibin Wu, Kay Chen Tan

The biological neurons use precise spike times, in addition to the spike firing rate, to communicate with each other. The time-to-first-spike (TTFS) coding is inspired by such biological observation. However, there is a lack of effective solutions for training TTFS-based spiking neural network (SNN). In this paper, we put forward a simple yet effective netwo

Dingyu Wang

Traditionally in the turnstile model of data streams, there is a state vector $x=(x_1,x_2,\ldots,x_n)$ which is updated through a stream of pairs $(i,k)$ where $i\in [n]$ and $k\in \Z$. Upon receiving $(i,k)$, $x_i\gets x_i + k$. A distinct count algorithm in the turnstile model takes one pass of the stream and then estimates $\norm{x}_0 = |\{i\in[n]\mid x_i

Nathan Phelps, Stephanie Marrocco, Stephanie Cornell, Dalton L. Wolfe

Reinforcement learning (RL) has helped improve decision-making in several applications. However, applying traditional RL is challenging in some applications, such as rehabilitation of people with a spinal cord injury (SCI). Among other factors, using RL in this domain is difficult because there are many possible treatments (i.e., large action space) and few

Fabiana Fournier, Lior Limonad, Inna Skarbovsky, Yuval David

Unraveling the causal relationships among the execution of process activities is a crucial element in predicting the consequences of process interventions and making informed decisions regarding process improvements. Process discovery algorithms exploit time precedence as their main source of model derivation. Hence, a causal view can supplement process disc

Jefferson D. S. Silva, Thiago Melo D. Azevedo, Israel F. Araujo, Adenilton J. da Silva

We provide a method for compiling approximate multi-controlled single qubit gates into quantum circuits without ancilla qubits. The total number of elementary gates to decompose an n-qubit multi-controlled gate is proportional to 32n, and the previous best approximate approach without auxiliary qubits requires 32nk elementary operations, where k is a functio

Ioannis Giagkiozis, Emilio Said

Perpetual swaps are derivative contracts that allow traders to speculate on, or hedge, the price movements of cryptocurrencies. Unlike futures contracts, perpetual swaps have no settlement or expiration in the traditional sense. The funding rate acts as the mechanism that tethers the perpetual swap to its underlying with the help of arbitrageurs. Open intere

Caleb Widstrand, Xiaoming Mao, Stefano Gonella

Recent developments in topological mechanics have demonstrated the ability of Maxwell lattices to effectively focus stress along domain walls between differently polarized domains. The focusing ability can be exploited to protect the lattice bulk from accidental stress concentration -- and eventually onset and propagation of fracture -- at structural hot spo

Wenhong Zhu, Hongkun Hao, Rui Wang

The decoding algorithm is critical for open-ended text generation, transforming latent representations into coherent and meaningful outputs. This paper investigates the self-reinforcement effect in text generation and the effectiveness of a repetition penalty to mitigate it. However, determining the optimal repetition penalty value is challenging. To tackle

Yujie Feng, Zexin Lu, Bo Liu, Liming Zhan

Dialogue State Tracking (DST) is of paramount importance in ensuring accurate tracking of user goals and system actions within task-oriented dialogue systems. The emergence of large language models (LLMs) such as GPT3 and ChatGPT has sparked considerable interest in assessing their efficacy across diverse applications. In this study, we conduct an initial ex

Angelo Bassi, Mauro Dorato, Hendrik Ulbricht

n this paper, we review and connect the three essential conditions needed by the collapse model to achieve a complete and exact formulation, namely the theoretical, the experimental, and the ontological ones. These features correspond to the three parts of the paper. In any empirical science, the first two features are obviously connected but, as is well kno

Sabina J. Sloman, Ayush Bharti, Julien Martinelli, Samuel Kaski

In many settings, such as scientific inference, optimization, and transfer learning, the learner has a well-defined objective, which can be treated as estimation of a target parameter, and no intrinsic interest in characterizing the entire data-generating process. Usually, the learner must also contend with additional sources of uncertainty or variables -- w

Evgeny A. Karashtin, Tatiana V. Murzina

We theoretically consider magnetization dynamics in a ferromagnetic slab induced by the magnetic field of a strong femtosecond laser pulse. The longitudinal geometry, in which the initial magnetization lies in both the plane of incidence and the sample plane, is studied. The magnetization oscillations at the optical wave frequency are calculated with the use

Jue Hou, Yunfeng Jiang, Yuan Miao

The solution of Bethe ansatz equations for XXZ spin chain with the parameter $q$ being a root of unity is infamously subtle. In this work, we develop the rational $Q$-system for this case, which offers a systematic way to find all physical solutions of the Bethe ansatz equations at root of unity. The construction contains two parts. In the first part, we imp

Gabriele Casagrande, Emilian Dudas, Marco Peloso

It is well-known that the number of particles produced in cosmology, commonly defined in the literature from the Fock space of the instantaneous hamiltonian of the canonically normalized fields, is ambiguous. On the other hand, the energy computed from the energy-momentum tensor should be physical. We compare the corresponding Fock spaces and relate them thr

Ross M. Clarke, José Miguel Hernández-Lobato

Research into optimisation for deep learning is characterised by a tension between the computational efficiency of first-order, gradient-based methods (such as SGD and Adam) and the theoretical efficiency of second-order, curvature-based methods (such as quasi-Newton methods and K-FAC). Noting that second-order methods often only function effectively with th

Hui Lin, Tom Liu, Aggelos Katsaggelos, Adrienne Kline

Coronary angiography continues to serve as the primary method for diagnosing coronary artery disease (CAD), which is the leading global cause of mortality. The severity of CAD is quantified by the location, degree of narrowing (stenosis), and number of arteries involved. In current practice, this quantification is performed manually using visual inspection a

Kaituo Zhang, Wei Huang, Bingyang Zhang, Jinshan Xu

By now, most outlier-detection algorithms struggle to accurately detect both point anomalies and cluster anomalies simultaneously. Furthermore, a few K-nearest-neighbor-based anomaly-detection methods exhibit excellent performance on many datasets, but their sensitivity to the value of K is a critical issue that needs to be addressed. To address these challe

Hans-Peter Lehmann, Peter Sanders, Stefan Walzer

A minimal perfect hash function (MPHF) maps a set S of n keys to the first n integers without collisions. There is a lower bound of n*log(e)=1.44n bits needed to represent an MPHF. This can be reached by a brute-force algorithm that tries e^n hash function seeds in expectation and stores the first seed leading to an MPHF. The most space-efficient previous al

Xiaohui Liu, Zhilu Zhang, Xiaohe Wu, Chaoyu Feng

Real-world image de-weathering aims at removing various undesirable weather-related artifacts. Owing to the impossibility of capturing image pairs concurrently, existing real-world de-weathering datasets often exhibit inconsistent illumination, position, and textures between the ground-truth images and the input degraded images, resulting in imperfect superv

Jacqueline Höllig, Steffen Thoma, Florian Grimm

Despite the growing body of work on explainable machine learning in time series classification (TSC), it remains unclear how to evaluate different explainability methods. Resorting to qualitative assessment and user studies to evaluate explainers for TSC is difficult since humans have difficulties understanding the underlying information contained in time se

Ilia Smilga

In this note, we present an algorithm that allows to answer any individual instance of the following question. Let $G_{\mathbb{R}}$ be a semisimple real Lie group, and $V$ an irreducible representation of $G_{\mathbb{R}}$. How does the longest element $w_0$ of the restricted Weyl group $W$ act on the subspace $V^L$ of $V$ formed by vectors that are invariant

Alan Rios Fukelman, Matías Sempé, Guillermo A. Silva

In this note we discuss features of the simplest spinning Discrete Series Unitary Irreducible Representations (UIR) of SO(1,4). These representations are known to be realised in the single particle Hilbert space of a free gauge field propagating in a four dimensional fixed de Sitter background. They showcase distinct features as compared to the more common P

Peng Fan, Changhao Shan, Sining Sun, Qing Yang

Recently, Conformer as a backbone network for end-to-end automatic speech recognition achieved state-of-the-art performance. The Conformer block leverages a self-attention mechanism to capture global information, along with a convolutional neural network to capture local information, resulting in improved performance. However, the Conformer-based model encou

Wesley Fussner, George Metcalfe, Simon Santschi

It was proved by Maksimova in 1977 that exactly eight varieties of Heyting algebras have the amalgamation property, and hence exactly eight axiomatic extensions of intuitionistic propositional logic have the deductive interpolation property. The prevalence of the deductive interpolation property for axiomatic extensions of substructural logics and the amalga

Emmanouil Karystinaios, Francesco Foscarin, Florent Jacquemard, Masahiko Sakai

This paper focuses on the nominal durations of musical events (notes and rests) in a symbolic musical score, and on how to conveniently handle these in computer applications. We propose the usage of a temporal unit that is directly related to the graphical symbols in musical scores and pair this with a set of operations that cover typical computations in mus

Rana Ghazali, Douglas G. Down

Nowadays distributed computing environments, large amounts of data are generated from different resources with a high velocity, rendering the data difficult to capture, manage, and process within existing relational databases. Hadoop is a tool to store and process large datasets in a parallel manner across a cluster of machines in a distributed environment.

Marylou Fournier-Tondreau, Ryan J. MacDonald, Michael Radica, David Lafrenière

The JWST Early Release Observations (ERO) included a NIRISS/SOSS (0.6-2.8$\,\mu$m) transit of the $\sim\,$850$\,$K Saturn-mass exoplanet HAT-P-18$\,$b. Initial analysis of these data reported detections of water, escaping helium, and haze. However, active K dwarfs like HAT-P-18 possess surface heterogeneities $-$ starspots and faculae $-$ that can complicate

Muhammad Reza Qorib, Hwee Tou Ng

Quality estimation models have been developed to assess the corrections made by grammatical error correction (GEC) models when the reference or gold-standard corrections are not available. An ideal quality estimator can be utilized to combine the outputs of multiple GEC systems by choosing the best subset of edits from the union of all edits proposed by the

Joanna Hong, Se Jin Park, Yong Man Ro

We present a novel approach to multilingual audio-visual speech recognition tasks by introducing a single model on a multilingual dataset. Motivated by a human cognitive system where humans can intuitively distinguish different languages without any conscious effort or guidance, we propose a model that can capture which language is given as an input speech b

Dimitrios Gazoulis, George Zacharopoulos

In this work we establish a gradient bound and Liouville-type theorems for solutions to Quasi-linear elliptic equations on compact Riemannian Manifolds with nonnegative Ricci curvature. Also, we provide a local splitting theorem when the inequality in the gradient bound becomes equality at some point. Moreover, we prove a Harnack-type inequality and an ABP e

Ireneusz Szcześniak, Ireneusz Olszewski, Bożena Woźna-Szcześniak

Intractable is the problem of finding two link-disjoint paths of minimal cost if the path cost is limited since it can be a special case of the partition problem. In optical networks, this limit can be introduced by the signal modulation reach. Even without this limit, the existing literature suggested the problem intractable because of the spectrum continui

Sanjeev Kumar Ramkumar Sudha, Md Shadab Alam, Bindusara Reddy, Abhilash Sharma Somayajula

Vessel navigation is difficult in restricted waterways and in the presence of static and dynamic obstacles. This difficulty can be attributed to the high-level decisions taken by humans during these maneuvers, which is evident from the fact that 85% of the reported marine accidents are traced back to human errors. Artificial intelligence-based methods offer

Timotheus Kampik, Cem Okulmus

With the increased adoption of process mining, there is also a need for practical solutions that work at industry scales. In this context, process querying methods (PQMs) have emerged as an important tool for drawing inferences from event logs. Here, it can be expected that industry approaches differ from academic ones, due to practical engineering and busin

Md Shadab Alam, Sanjeev Kumar Ramkumar Sudha, Abhilash Somayajula

Human decision-making errors cause a majority of globally reported marine accidents. As a result, automation in the marine industry has been gaining more attention in recent years. Obstacle avoidance becomes very challenging for an autonomous surface vehicle in an unknown environment. We explore the feasibility of using Deep Q-Learning (DQN), a deep reinforc

Zhiguang Xiao, Zhi-Yong Zhou

In this study, we present several improvements of the non-relativistic Friedrichs-Lee model with multiple discrete and continuous states and still retain its solvability. Our findings establish a solid theoretical basis for the exploration of resonance phenomena in scenarios involving multiple interfering states across various channels. The scattering amplit

C. Papageorgakis, M. Y. Aamir, A. Belloni, T. K. Edberg

Plastic scintillators are a versatile and inexpensive option for particle detection, which is why the largest particle physics experiments, CMS and ATLAS, use them extensively in their calorimeters. One of their challenging aspects, however, is their relatively low radiation hardness, which might be inadequate for very high luminosity future projects like th

Alejandro Tejada-Lapuerta, Paul Bertin, Stefan Bauer, Hananeh Aliee

Advances in single-cell omics allow for unprecedented insights into the transcription profiles of individual cells. When combined with large-scale perturbation screens, through which specific biological mechanisms can be targeted, these technologies allow for measuring the effect of targeted perturbations on the whole transcriptome. These advances provide an

Junpeng Tan, Chunmei Qing, Xiangmin Xu

Compressed Sensing (CS) significantly speeds up Magnetic Resonance Image (MRI) processing and achieves accurate MRI reconstruction from under-sampled k-space data. According to the current research, there are still several problems with dynamic MRI k-space reconstruction based on CS. 1) There are differences between the Fourier domain and the Image domain, a

Krzysztof Pachucki

We derive finite nuclear mass and finite nuclear size corrections to the magnetic shielding in light ions. These corrections are important for the accurate determination of nuclear magnetic moments. We correct several previous formulas for the nuclear mass corrections and present improved results for the magnetic shielding in $^1$H, $^3$He$^+$, and $^3$He. F

Joel Jose, Md Shadab Alam, Abhilash Sharma Somayajula

Human error is a substantial factor in marine accidents, accounting for 85% of all reported incidents. By reducing the need for human intervention in vessel navigation, AI-based methods can potentially reduce the risk of accidents. AI techniques, such as Deep Reinforcement Learning (DRL), have the potential to improve vessel navigation in challenging conditi

Théo Laurent, Meven Lennon-Bertrand, Kenji Maillard

Dependently typed proof assistant rely crucially on definitional equality, which relates types and terms that are automatically identified in the underlying type theory. This paper extends type theory with definitional functor laws, equations satisfied propositionally by a large class of container-like type constructors $F : \mathrm{Type} \to \mathrm{Type}$,

Jun Zhao, Zhihao Zhang, Yide Ma, Qi Zhang

Brain localization, which describes the association between specific regions of the brain and their corresponding functions, is widely accepted in the field of cognitive science as an objective fact. Today's large language models (LLMs) possess human-level linguistic competence and can execute complex tasks requiring abstract knowledge and reasoning. To deep

Matthias Keller, Florentin Münch, Radosław K. Wojciechowski

We study heat kernel convergence of induced subgraphs with Neumann boundary conditions. We first establish convergence of the resulting semigroups to the Neumann semigroup in $\ell^2$. While convergence to the Neumann semigroup always holds, convergence to the Dirichlet semigroup in $\ell^2$ turns out to be equivalent to the coincidence of the Dirichlet and

Luca Castri, Sariah Mghames, Nicola Bellotto

Using robots for automating tasks in environments shared with humans, such as warehouses, shopping centres, or hospitals, requires these robots to comprehend the fundamental physical interactions among nearby agents and objects. Specifically, creating models to represent cause-and-effect relationships among these elements can aid in predicting unforeseen hum

Robert Lösch, Mark Sastuba, Jonas Toth, Bernhard Jung

In recent years, depth sensors have become more and more affordable and have found their way into a growing amount of robotic systems. However, mono- or multi-modal sensor registration, often a necessary step for further processing, faces many challenges on raw depth images or point clouds. This paper presents a method of converting depth data into images ca

Alessandro Cataldo, Pinaka Pani Tummala, Christian Martella, Carlo Spartaco Casari

In the last years, transition metal dichalcogenides (TMDs), especially at the two-dimensional (2D) limit, gained a large interest due to their unique optical and electronic properties. Among them, MoS2 received great attention from the scientific community due to its versatility, workability, and applicability in a large number of fields such as electronics,

Dino Pitoski, Ana Meštrović, Hans Schmeets

Migration's influence in shaping population dynamics in times of impending climate and population crises exposes its crucial role in upholding societal cohesion. As migration impacts virtually all aspects of life, it continues to require attention across scientific disciplines. This study delves into two distinctive substrates of Migration Studies: the "why"

Tong Zheng, Bei Li, Huiwen Bao, Jiale Wang

The design choices in Transformer feed-forward neural networks have resulted in significant computational and parameter overhead. In this work, we emphasize the importance of hidden dimensions in designing lightweight FFNs, a factor often overlooked in previous architectures. Guided by this principle, we introduce PartialFormer, a parameter-efficient Transfo

Ruodi Yan, Yun Kau Lau

A certain class of exact solutions of Einstein Maxwell spacetime in general relativity is discussed which demonstrates at the level of theory that, when certain parametric resonance condition is met, the interaction of electromagnetic field with a gravitational wave will display certain Liapounov instability and lead to exponential amplification of a gravita

Jan Warchocki, Mikhail Vlasenko, Yke Bauke Eisma

Hand gesture recognition systems provide a natural way for humans to interact with computer systems. Although various algorithms have been designed for this task, a host of external conditions, such as poor lighting or distance from the camera, make it difficult to create an algorithm that performs well across a range of environments. In this work, we presen

Yang Liu, Xiang Li, Jian Wu

The China Spallation Neutron Source (CSNS) beam power was successfully reached 125 kW with a low beam loss in February 2022. In order to increase beam power, during the summer in 2022, we employ magnetic-alloy (MA) cavity in the rapid cycling synchrotron (RCS). It is a wideband cavity (Q=2), allows the second harmonic rf (h= 4) operation, with the existing f

Hazem Youssef, Frederik Polachowski, Jérôme Rutinowski, Moritz Roidl

Object localization, and more specifically object pose estimation, in large industrial spaces such as warehouses and production facilities, is essential for material flow operations. Traditional approaches rely on artificial artifacts installed in the environment or excessively expensive equipment, that is not suitable at scale. A more practical approach is

Chuanhuan Li, Yi Li, Kairui Xu, Jichun Zhu

In this paper, we consider the parabolic frequency for positive solutions of two nonlinear parabolic equations under the Ricci flow on closed manifolds. We obtain the monotonicity of parabolic frequency for the solution of two nonlinear parabolic equations with bounded Ricci curvature, then we apply the parabolic frequency monotonicity to get some integral t

Zhiyang Li, Fabian Göttsch, Siyao Li, Ming Chen

We consider scalable cell-free massive multiple-input multiple-output networks under an open radio access network paradigm comprising user equipments (UEs), radio units (RUs), and decentralized processing units (DUs). UEs are served by dynamically allocated user-centric clusters of RUs. The corresponding cluster processors (implementing the physical layer fo

Gorjan Radevski, Kiril Gashteovski, Chia-Chien Hung, Carolin Lawrence

Open Information Extraction (OIE) methods extract facts from natural language text in the form of ("subject"; "relation"; "object") triples. These facts are, however, merely surface forms, the ambiguity of which impedes their downstream usage; e.g., the surface phrase "Michael Jordan" may refer to either the former basketball player or the university profess

H. L. M. Osborne, V. Van Eylen, E. Goffo, D. Gandolfi

We report on the precise radial velocity follow-up of TOI-544 (HD 290498), a bright K star (V=10.8), which hosts a small transiting planet recently discovered by the Transiting Exoplanet Survey Satellite (TESS). We collected 122 high-resolution HARPS and HARPS-N spectra to spectroscopically confirm the transiting planet and measure its mass. The nearly 3-yea

Chunzhi Gu, Chao Zhang, Shigeru Kuriyama

The task of action-driven human motion prediction aims to forecast future human motion based on the observed sequence while respecting the given action label. It requires modeling not only the stochasticity within human motion but the smooth yet realistic transition between multiple action labels. However, the fact that most datasets do not contain such tran

Yaru Liu, Zeqing Wang, Chao Yang, Jianwen Jie

Mobility edge (ME), representing the critical energy that distinguishes between extended and localized states, is a key concept in understanding the transition between extended (metallic) and localized (insulating) states in disordered and quasiperiodic systems. Here we explore the impact of dissipation on a quasiperiodic system featuring MEs by calculating

Hikmet Çakmak

Determining the electron density is a challenging task in solar corona studies, as it requires certain assumptions to be made, such as symmetric, homogeneous and radial distribution, thermal equilibrium, etc. In such studies, the observed $K$ corona brightness is based on the coronal electron density. An important paper on the calculation of electron density

Liu Tao, Paul Fulda

Higher-order spatial laser modes have recently been investigated as candidates for reducing test-mass thermal noise in ground-based gravitational-wave detectors such as advanced LIGO. In particular, higher-order Hermite-Gauss (HG) modes have gained attention within the community for their more robust behaviors against random test-mass surface deformations an

Elre T. Oldewage, Ross M. Clarke, José Miguel Hernández-Lobato

Despite their popularity in the field of continuous optimisation, second-order quasi-Newton methods are challenging to apply in machine learning, as the Hessian matrix is intractably large. This computational burden is exacerbated by the need to address non-convexity, for instance by modifying the Hessian's eigenvalues as in Saddle-Free Newton methods. We pr

Jin-Cheng He, Jian Xing, Jian-Xin Shen, Dan Su

The PZT/FeGa thin film memtranstor was prepared and the modulation of the magnetoelectric coefficient by external magnetic and electric fields was studied. The magnetoelectric coefficient of the PZT/FeGa memtranstor can be reversed by flipping the direction of magnetization of FeGa or ferroelectric polarization of PZT. Notably, the sign of the magnetoelectri

N'Dah Jean Kouagou, Caglar Demir, Hamada M. Zahera, Adrian Wilke

A variety of knowledge graph embedding approaches have been developed. Most of them obtain embeddings by learning the structure of the knowledge graph within a link prediction setting. As a result, the embeddings reflect only the structure of a single knowledge graph, and embeddings for different knowledge graphs are not aligned, e.g., they cannot be used to

Ahmad Barhoumi, Pavel Bleher, Alfredo Deaño, Maxim L. Yattselev

We show that the one-parameter family of special solutions of P$_\mathrm{II}$, the second Painlev\'e equation, constructed from the Airy functions, as well as associated solutions of P$_\mathrm{XXXIV}$ and S$_\mathrm{II}$, can be expressed via the recurrence coefficients of orthogonal polynomials that appear in the analysis of the Hermitian random matrix ens

Gowtham Krishnan Murugesan, Diana McCrumb, Mariam Aboian, Tej Verma

The National Cancer Institute (NCI) Image Data Commons (IDC) offers publicly available cancer radiology collections for cloud computing, crucial for developing advanced imaging tools and algorithms. Despite their potential, these collections are minimally annotated; only 4% of DICOM studies in collections considered in the project had existing segmentation a

Marius Lemm, Carla Rubiliani, Jingxuan Zhang

We consider the time-dependent Schr\"odinger equation that is generated on the bosonic Fock space by a long-range quantum many-body Hamiltonian. We derive the first bound on the maximal speed of particle transport in these systems that is thermodynamically stable and holds all the way down to microscopic length scales. For this, we develop a novel multiscale

Szymon Bobek, Grzegorz J. Nalepa

Explainable artificial intelligence (XAI) is one of the most intensively developed area of AI in recent years. It is also one of the most fragmented with multiple methods that focus on different aspects of explanations. This makes difficult to obtain the full spectrum of explanation at once in a compact and consistent way. To address this issue, we present L

Tianqi Zhong, Quan Wang, Jingxuan Han, Yongdong Zhang

Controllable text generation (CTG) aims to generate text with desired attributes, and decoding-time-based methods have shown promising performance on this task. However, in this paper, we identify the phenomenon of Attribute Collapse for the first time. It causes the fluency of generated text to rapidly decrease when the control strength exceeds a critical v

Merek Johnson

In one and two dimensions, the first-passage time for a diffusing particle in the presence of a radial potential flow to hit a sphere, conditioned on actually hitting the sphere, is independent of the sign of the drift. Moreover, the first-passage distribution for an inward (negative) drift is identical to the first-passage distribution for outward (positive

Tim Reichelt, Luke Ong, Tom Rainforth

The posterior in probabilistic programs with stochastic support decomposes as a weighted sum of the local posterior distributions associated with each possible program path. We show that making predictions with this full posterior implicitly performs a Bayesian model averaging (BMA) over paths. This is potentially problematic, as BMA weights can be unstable

Xiang Li, Yang Liu

The upgrade plan of the China Spallation Neutron Source aims to enhance the beam power from 100 kW to 500 kW. To achieve this, the plan involves incorporating three new magnetic alloy cavities while maintaining the existing system to enable double harmonic acceleration. As a consequence of the increased current intensity, the beam loading effect will be sign

Christian Berger, Beatriz Cabrero-Daniel, M. Cagri Kaya, Maryam Esmaeili Darestani

Identifying driving maneuvers plays an essential role on-board vehicles to monitor driving and driver states, as well as off-board to train and evaluate machine learning algorithms for automated driving for example. Maneuvers can be characterized by vehicle kinematics or data from its surroundings including other traffic participants. Extracting relevant man

Qinyu Wu, Zhixing Ling, Chen Zhang, Shuang-Nan Zhang

In recent years, tremendous progress has been made on scientific Complementary Metal Oxide Semiconductor (sCMOS) sensors, making them a promising device for future space X-ray missions. We have customized a large-format sCMOS sensor, G1516BI, dedicated for X-ray applications. In this work, a 200 nm thick aluminum layer is successfully sputtered on the surfac

Julian Quast

We define a deformation space of V. Lafforgue's $G$-valued pseudocharacters of a profinite group $\Gamma$ for a possibly disconnected reductive group $G$. We show, that this definition generalizes Chenevier's construction. We show that the universal pseudodeformation ring is noetherian and that the functor of continuous $G$-pseudocharacters on affinoid $\mat

Robert P. Cameron, Emmanouil I. Alexakis, Aidan S. Arnold, Duncan McArthur

It has long been understood that dilute samples of chiral molecules such as rarefied gases should exhibit Rayleigh optical activity. We extend the existing theory by accounting for molecular dynamics and correlations, thus obtaining a more general theory of Rayleigh-Brillouin optical activity applicable to dense samples such as neat liquids.

Aneet Kumar Dutta, Sebastian Brandt, Mridula Singh

The availability of cheap GNSS spoofers can prevent safe navigation and tracking of road users. It can lead to loss of assets, inaccurate fare estimation, enforcing the wrong speed limit, miscalculated toll tax, passengers reaching an incorrect location, etc. The techniques designed to prevent and detect spoofing by using cryptographic solutions or receivers

Yunke Qu, Tong Chen, Quoc Viet Hung Nguyen, Hongzhi Yin

At the heart of contemporary recommender systems (RSs) are latent factor models that provide quality recommendation experience to users. These models use embedding vectors, which are typically of a uniform and fixed size, to represent users and items. As the number of users and items continues to grow, this design becomes inefficient and hard to scale. Recen

Zhengrui Ma, Shaolei Zhang, Shoutao Guo, Chenze Shao

Simultaneous machine translation (SiMT) models are trained to strike a balance between latency and translation quality. However, training these models to achieve high quality while maintaining low latency often leads to a tendency for aggressive anticipation. We argue that such issue stems from the autoregressive architecture upon which most existing SiMT mo

Linglong Yuan

Kingman's coalescent is a widely used process to model sample genealogies in population genetics. Recently there have been studies on the inference of quantities related to the genealogy of additional individuals given a known sample. This paper explores the recursive (or sequential) construction which is a natural way of enlarging the sample size by adding

Yuanrong Wang, Antonio Briola, Tomaso Aste

Modern portfolio optimization is centered around creating a low-risk portfolio with extensive asset diversification. Following the seminal work of Markowitz, optimal asset allocation can be computed using a constrained optimization model based on empirical covariance. However, covariance is typically estimated from historical lookback observations, and it is

Xiaoxi Kang, Lizhen Qu, Lay-Ki Soon, Adnan Trakic

Large Language Models (LLMs), such as ChatGPT, have drawn a lot of attentions recently in the legal domain due to its emergent ability to tackle a variety of legal tasks. However, it is still unknown if LLMs are able to analyze a legal case and perform reasoning in the same manner as lawyers. Therefore, we constructed a novel corpus consisting of scenarios p

Vincent Bagayoko, Joris van der Hoeven

Surreal numbers form the ultimate extension of the field of real numbers with infinitely large and small quantities and in particular with all ordinal numbers. Hyperseries can be regarded as the ultimate formal device for representing regular growth rates at infinity. In this paper, we show that any surreal number can naturally be regarded as the value of a

Victor J. W. Guo

Employing the $q$-Lucas theorem and some known $q$-supercongruences, we give some Dwork-type $q$-congruences, confirming three conjectures in [J. Combin. Theory, Ser. A 178 (2021), Art.~105362]. As conclusions, we obtain the following supercongruences: for any prime $p\equiv 1\pmod{4}$ and positive integer $r$, \begin{align*} \sum_{k=0}^{(p^r-1)/2} \frac{(\f

Shi-Zhen Liu, Ze-Yu Tao, Ze-Chun Hu

Let $(\epsilon_i)$ be a Rademacher sequence, i.e., a sequence of independent and identically distributed random variables satisfying $P(\epsilon_i=1)=P(\epsilon_i=-1)=1/2$. Set $S_n=a_1\epsilon_1+\cdots+a_n\epsilon_n$ for $a=(a_1,\dots,a_n)\in \mathbb{R}^n$. The Hitczenko-Kwapien conjecture says that $P\left(\left|S_n\right|\geq\|a\|\right)\geq {7}/{32}$ for

Dongmin Gang, Dongyeob Kim, Sungjay Lee

We introduce a novel class of two-dimensional non-unitary rational conformal field theories (RCFTs) whose modular data are identical to the generalized Haagerup-Izumi modular data. Via the bulk-boundary correspondence, they are related to the three-dimensional non-unitary Haagerup topological field theories, recently constructed by a topological twisting of

Jørgen Anker Olsen, Kostas Alexis

In recent years, robotic exploration has become increasingly important in planetary exploration. One area of particular interest for exploration is Martian lava tubes, which have several distinct features of interest. First, it is theorized that they contain more easily accessible resources such as water ice, needed for in-situ utilization on Mars. Second, l

Alexey Kupriyanov, Arthur Reis, Manuel Schilling, Vitali Müller

Twenty years of gravity observations from various satellite missions have provided unique data about mass redistribution processes in the Earth system. This paper studies the benefit of enhanced electrostatic and novel optical accelerometers and gradiometers for the future gravimetry missions. One of the limiting factors in the current space gravimetry missi

Lingzhi Wang, Maokai Hu, Lifan Wang, Yi Yang

Dust associated with various stellar sources in galaxies at all cosmic epochs remains a controversial topic, particularly whether supernovae (SNe) play an important role in dust production. We report evidence of dust formation in the cold, dense shell behind the ejecta-circumstellar medium (CSM) interaction in the Type Ia-CSM SN 2018evt three years after the

Vincent Bagayoko, Joris van der Hoeven

For any ordinal $\alpha > 0$, we show how to define a hyperexponential $E_{\omega^{\alpha}}$ and a hyperlogarithm $L_{\omega^{\alpha}}$ on the class $\mathbf{No}^{>, \succ}$ of positive infinitely large surreal numbers. Such functions are archetypes of extremely fast and slowly growing functions at infinity. We also show that the surreal numbers form a so-ca

Joaquín Domínguez-de-Tena, Aníbal Rodríguez-Bernal

In this work, we study the decay of mass for solutions to the heat equation in exterior domains, i.e., domains which are the complement of a compact set in $\mathbb{R}^N$. Different homogeneous boundary conditions are considered, including Dirichlet, Robin, and Neumann conditions. We determine the exact amount of mass loss and identify criteria for complete

Franc Forstneric, Yuta Kusakabe

Let $(E,h)$ be a semipositive hermitian holomorphic line bundle on a compact complex manifold $X$ with $\dim X>1$. Assume that for each point $x\in X$ there exists a divisor $D\in |E|$ in the complete linear system determined by $E$ whose complement $X\setminus D$ is a Stein neighbourhood of $x$ with the density property. Then, the disc bundle $\Delta_h(E)=\

Jan Philip Wahle, Terry Ruas, Mohamed Abdalla, Bela Gipp

Natural Language Processing (NLP) is poised to substantially influence the world. However, significant progress comes hand-in-hand with substantial risks. Addressing them requires broad engagement with various fields of study. Yet, little empirical work examines the state of such engagement (past or current). In this paper, we quantify the degree of influenc

R. Belhadef, H-A. Esbelin

In this paper we give an algorithm to calculate the coefficients of the p-adic expansion of a rational numbers, and we give a method to decide whether this expansion is periodic or ultimately periodic.

Mengyu Ye, Tatsuki Kuribayashi, Jun Suzuki, Goro Kobayashi

Large language models (LLMs) take advantage of step-by-step reasoning instructions, e.g., chain-of-thought (CoT) prompting. Building on this, their ability to perform CoT-style reasoning robustly is of interest from a probing perspective. In this study, we inspect the step-by-step reasoning ability of LLMs with a focus on negation, which is a core linguistic

Zixuan Guo, Wenge Xu, Jialin Zhang, Hongyu Wang

Familiarity with audiences plays a significant role in shaping individual performance and experience across various activities in everyday life. This study delves into the impact of familiarity with non-playable character (NPC) audiences on player performance and experience in virtual reality (VR) exergames. By manipulating of NPC appearance (face and body s

Rohith Teja Mittakola, Thomas Hassan

Graph data structures are widely used to store relational information between several entities. With data being generated worldwide on a large scale, we see a significant growth in the generation of knowledge graphs. Thing in the future is Orange's take on a knowledge graph in the domain of the Web Of Things (WoT), where the main objective of the platform is