May 2023 arXiv papers — page 79

Erfan Fatehi, Manish Thadani, Gabriel Birsan, Robert W Black

This work highlights the potential of earth-abundant mixed-metal oxide catalysts for the acid-based oxygen evolution reaction. These catalysts offer numerous combinations of metal-centre compositions, which can enhance catalytic activity and stability compared to precious-metal-based catalysts commonly used today. Despite substantial research in this field,

Lokesh Bansal, S. Pavankumar Dubagunta, Malolan Chetlur, Pushpak Jagtap

New-age conversational agent systems perform both speech emotion recognition (SER) and automatic speech recognition (ASR) using two separate and often independent approaches for real-world application in noisy environments. In this paper, we investigate a joint ASR-SER multitask learning approach in a low-resource setting and show that improvements are obser

Peyman Alipour, Ali Foroush Bastani

Designing dynamic portfolio insurance strategies under market conditions switching between two or more regimes is a challenging task in financial economics. Recently, a promising approach employing the value-at-risk (VaR) measure to assign weights to risky and riskless assets has been proposed in [Jiang C., Ma Y. and An Y. "The effectiveness of the VaR-based

Zeki Eker, Volkan Bakis

Main-sequence bolometric corrections (BC) and a standard BC-Teff relation are produced for TESS wavelengths using published physical parameters and light ratios from SED models of 209 detached double-lined eclipsing binaries. This and previous five-band (Johnson B, V, Gaia G, GBP, GRP) standard BC-Teff relations are tested by recovering luminosity (L) of the

Larry S. Liebovitch, William Powers, Lin Shi, Allegra Chen-Carrel

Language is both a cause and a consequence of the social processes that lead to conflict or peace. Hate speech can mobilize violence and destruction. What are the characteristics of peace speech that reflect and support the social processes that maintain peace? This study used existing peace indices, machine learning, and on-line, news media sources to ident

Jiashi Yang

The Landau-Lifshitz-Gilbert equation for rigid and saturated ferromagnets is derived using a two-continuum model constructed by H.F. Tiersten for elastic and saturated ferromagnets. The relevant basic laws of physics are applied systematically to the two continua or their combination. The exchange interaction is introduced into the model through surface dist

A. Castro, W. de Paula, E. Ydrefors, T. Frederico

The Bethe-Salpeter equation for a pseudoscalar bound-system, with i) a ladder kernel with massive gluons, ii) dynamically-dressed quark mass function and iii) an extended quark-gluon vertex, is solved in Minkowski space by using the Nakanishi integral representation of the Bethe-Salpeter amplitude. The quark dressing is implemented through a phenomenological

Javier Ferrando, Gerard I. Gállego, Ioannis Tsiamas, Marta R. Costa-jussà

Language Generation Models produce words based on the previous context. Although existing methods offer input attributions as explanations for a model's prediction, it is still unclear how prior words affect the model's decision throughout the layers. In this work, we leverage recent advances in explainability of the Transformer and present a procedure to an

Piyush Jha, Joseph Scott, Jaya Sriram Ganeshna, Mudit Singh

We present a novel tool BertRLFuzzer, a BERT and Reinforcement Learning (RL) based fuzzer aimed at finding security vulnerabilities for Web applications. BertRLFuzzer works as follows: given a set of seed inputs, the fuzzer performs grammar-adhering and attack-provoking mutation operations on them to generate candidate attack vectors. The key insight of Bert

Ranjan Kumar Das, Harish K. Pillai

Linearization is a widely used method for solving polynomial eigenvalue problems (PEPs) and rational eigenvalue problem (REPs) in which the PEP/REP is transformed to a generalized eigenproblem and then solve this generalized eigenproblem with algorithms available in the literature. Fiedler-like pencils (Fiedler pencils (FPs), generalized Fiedler pencils (GFP

Sebastian Joseph, Kathryn Kazanas, Keziah Reina, Vishnesh J. Ramanathan

Automated text simplification aims to produce simple versions of complex texts. This task is especially useful in the medical domain, where the latest medical findings are typically communicated via complex and technical articles. This creates barriers for laypeople seeking access to up-to-date medical findings, consequently impeding progress on health liter

Deepak Pachattu

In this short paper, we demonstrate using irreducible tensorial techniques and in a model-independent way, why tensor interactions and also orbital-angular momentum-changing vector interactions are absent in the singlet unpolarized differential cross section for the reaction $\overline{\mathrm{p}} \mathrm{p} \rightarrow \bar{\Lambda} \Lambda$.

Jialu Li, Mark Hasegawa-Johnson, Nancy L. McElwain

To perform automatic family audio analysis, past studies have collected recordings using phone, video, or audio-only recording devices like LENA, investigated supervised learning methods, and used or fine-tuned general-purpose embeddings learned from large pretrained models. In this study, we advance the audio component of a new infant wearable multi-modal d

Yukun Huang, Jianan Wang, Ailing Zeng, He Cao

We present DreamWaltz, a novel framework for generating and animating complex 3D avatars given text guidance and parametric human body prior. While recent methods have shown encouraging results for text-to-3D generation of common objects, creating high-quality and animatable 3D avatars remains challenging. To create high-quality 3D avatars, DreamWaltz propos

Moksh Shukla, Nitik Jain, Shubham Gupta

This research study investigates the efficiency of different information retrieval (IR) systems in accessing relevant information from the scientific literature during the COVID-19 pandemic. The study applies the TREC framework to the COVID-19 Open Research Dataset (CORD-19) and evaluates BM25, Contriever, and Bag of Embeddings IR frameworks. The objective i

Xiaolong Yang, Jun Yang

We study radio and X-ray emissions from IMBHs and explore the unified model for accretion and ejection processes. The radio band survey of IMBH (candidate) hosted galaxies indicates that only a small fraction ($\sim$0.6\%) of them are radio-band active. In addition, very long baseline interferometry observations reveal parsec-scale radio emission of IMBHs, f

Xiaolong Yang, Ziwei Ou

We present radio very long baseline interferometry (VLBI) and X-ray studies of the starburst galaxy NGC 3628. The VLBI observation at 1.5 GHz reveals seven compact (0.7$-$7 parsec) radio sources in the central $\sim$250 parsec region of NGC 3628. Based on their morphology, high radio brightness temperatures ($10^5-10^7$ K), and steep radio spectra, none of t

Xiaolong Yang, Su Yao, Luigi C. Gallo, Jun Yang

Accretion of black holes at near-Eddington or super-Eddington rates is the most powerful episode that drives black hole growth, and it may work in several types of objects. However, the physics of accretion and jet-disc coupling in such a state remains unclear, mainly because the associated jets are not easily detectable due to the extremely weak emission or

Wenhu Chen, Ming Yin, Max Ku, Pan Lu

The recent LLMs like GPT-4 and PaLM-2 have made tremendous progress in solving fundamental math problems like GSM8K by achieving over 90% accuracy. However, their capabilities to solve more challenging math problems which require domain-specific knowledge (i.e. theorem) have yet to be investigated. In this paper, we introduce TheoremQA, the first theorem-dri

Zinat Behdad, Özlem Tuğfe Demir, Ki Won Sung, Emil Björnson

This paper studies an integrated sensing and communication (ISAC) system within a centralized cell-free massive MIMO (multiple-input multiple-output) network for target detection. ISAC transmit access points serve the user equipments in the downlink and optionally steer a beam toward the target in a multi-static sensing framework. A maximum a posteriori rati

Lucas David, Helio Pedrini, Zanoni Dias

Weakly Supervised Semantic Segmentation (WSSS) techniques explore individual regularization strategies to refine Class Activation Maps (CAMs). In this work, we first analyze complementary WSSS techniques in the literature, their segmentation properties, and the conditions in which they are most effective. Based on these findings, we devise two new techniques

Matthias Ludewig

We give a construction of the spinor bundle of the loop space of a string manifold together with its fusion product, inspired by ideas from Stolz and Teichner. The spinor bundle is a super bimodule bundle for a bundle of Clifford von Neumann algebras over the free path space, and the fusion product is defined using Connes fusion of such bimodules. As the mai

Jordi Armengol-Estapé, Jackson Woodruff, Chris Cummins, Michael F. P. O'Boyle

Decompilation is a well-studied area with numerous high-quality tools available. These are frequently used for security tasks and to port legacy code. However, they regularly generate difficult-to-read programs and require a large amount of engineering effort to support new programming languages and ISAs. Recent interest in neural approaches has produced por

Xiao Yu, Yuang Qi, Kejiang Chen, Guoqiang Chen

Large language models (LLMs) have the potential to generate texts that pose risks of misuse, such as plagiarism, planting fake reviews on e-commerce platforms, or creating inflammatory false tweets. Consequently, detecting whether a text is generated by LLMs has become increasingly important. Existing high-quality detection methods usually require access to

Shivam Mhaskar, Vineet Bhat, Akshay Batheja, Sourabh Deoghare

In this work, we present our deployment-ready Speech-to-Speech Machine Translation (SSMT) system for English-Hindi, English-Marathi, and Hindi-Marathi language pairs. We develop the SSMT system by cascading Automatic Speech Recognition (ASR), Disfluency Correction (DC), Machine Translation (MT), and Text-to-Speech Synthesis (TTS) models. We discuss the chall

Shauli Ravfogel, Valentina Pyatkin, Amir DN Cohen, Avshalom Manevich

Identifying texts with a given semantics is central for many information seeking scenarios. Similarity search over vector embeddings appear to be central to this ability, yet the similarity reflected in current text embeddings is corpus-driven, and is inconsistent and sub-optimal for many use cases. What, then, is a good notion of similarity for effective re

Yu-Qi Dong, Yu-Qiang Liu, Yu-Xiao Liu

In this paper, we study polarization modes of gravitational waves in generalized Proca theory in the homogeneous and isotropic Minkowski background. The results show that the polarizations of gravitational waves depend on the parameter space of this gravity theory and can be divided into quite rich cases by parameters. In some parameter space, it only allows

Robert Connelly, Steven J. Gortler, Louis Theran

Let $G$ be a graph with $n$ vertices, and $d$ be a target dimension. In this paper we study the set of rank $n-d-1$ matrices that are equilibrium stress matrices for at least one (unspecified) $d$-dimensional framework of $G$ in general position. In particular, we show that this set is algebraically irreducible. Likewise, we show that the set of frameworks w

Judith Dineley, Ewan Carr, Faith Matcham, Johnny Downs

Speech is promising as an objective, convenient tool to monitor health remotely over time using mobile devices. Numerous paralinguistic features have been demonstrated to contain salient information related to an individual's health. However, mobile device specification and acoustic environments vary widely, risking the reliability of the extracted features.

Luca-Maxim Meinhardt, Jan-Henry Belz, Michael Rietzler, Enrico Rukzio

This position paper discusses the negative effects of excessive smartphone usage on mental health and well-being. Despite efforts to limit smartphone usage, users become desensitized to reminders and limitations. The paper proposes the use of Push & Pull Factors to contextualize intervention strategies promoting digital well-being. Further, alternative metri

Sabyasachi Chatterjee, Partha S. Dey, Subhajit Goswami

We prove a central limit theorem for the Horvitz-Thompson estimator based on the Gram-Schmidt Walk (GSW) design, recently developed in Harshaw et al.(2022). In particular, we consider the version of the GSW design which uses randomized pivot order, thereby answering an open question raised in the same article. We deduce this under minimal and global assumpti

Hang Lou, Siran Li, Hao Ni

Generating high-fidelity time series data using generative adversarial networks (GANs) remains a challenging task, as it is difficult to capture the temporal dependence of joint probability distributions induced by time-series data. Towards this goal, a key step is the development of an effective discriminator to distinguish between time series distributions

Yoav Tulpan, Oren Tsur

Online social platforms provide a bustling arena for information-sharing and for multi-party discussions. Various frameworks for dialogic discourse parsing were developed and used for the processing of discussions and for predicting the productivity of a dialogue. However, most of these frameworks are not suitable for the analysis of contentious discussions

Kyle Gannon

As consequence of the VC theorem, any pseudo-finite measure over an NIP ultraproduct is generically stable. We demonstrate a converse of this theorem and prove that any finitely approximable measure over an ultraproduct is itself pseudo-finite (even without the NIP assumption). We also analyze the connection between the Morley product and the pseudo-finite p

Zhiyu Dong, Olumakinde Ogunnaike, Leonid Levitov

We argue that spin and valley-polarized metallic phases recently observed in graphene bilayers and trilayers support chiral edge modes that allow spin waves to propagate ballistically along system boundaries without backscattering. The chiral edge behavior originates from the interplay between the momentum-space Berry curvature in Dirac bands and the geometr

Siqi Zhao, Huirong Yan, Terry Z. Liu, Ka Ho Yuen

Plasma turbulence is a ubiquitous dynamical process that transfers energy across many spatial and temporal scales and affects energetic particle transport. Recent advances in the understanding of compressible magnetohydrodynamic (MHD) turbulence demonstrate the important role of damping in shaping energy distributions on small scales, yet its observational e

Xiaoguang Li

Dendrite core is the center point of the dendrite. The information of dendrite core is very helpful for material scientists to analyze the properties of materials. Therefore, detecting the dendrite core is a very important task in the material science field. Meanwhile, because of some special properties of the dendrites, this task is also very challenging. D

Luca Nanni

Recently, a number of experimental observations on the superluminal group velocities of pulses propagating in dispersive media have led to reconsidering electromagnetism theory in an unconventional framework. To consider faster-than-light phenomena, it is not necessary to replace the current relativistic theory, but it is sufficient to extend it to superlumi

Raffaella Schneider, Rosa Valiante, Alessandro Trinca, Luca Graziani

JWST is unveiling for the first time accreting black holes (BHs) with masses of 10^6 - 10^7 Msun at z > 4, with the most distant residing in GNz11 at z = 10.6. Are we really surprised to find them in the nuclei of z = 5 - 11 galaxies? Here we predict the properties of 4 < z < 11 BHs and their host galaxies considering an Eddington-limited (EL) and a super-Ed

Riyaz Ahmad, Amit M. Joshi, Dharmendra Boolchandani

For glucose electrochemical sensors, a comprehensive electronics interface is designed and constructed in 0.18 um, CMOS process technology, and 1.5 V supply voltage. This interface includes a programmable readout amplifier and bandgap reference voltage potentiostat circuit. The programmable transimpedance amplifier (PTIA), the proposed readout circuit, provi

Yugeng Liu, Zheng Li, Michael Backes, Yun Shen

The availability and accessibility of diffusion models (DMs) have significantly increased in recent years, making them a popular tool for analyzing and predicting the spread of information, behaviors, or phenomena through a population. Particularly, text-to-image diffusion models (e.g., DALLE 2 and Latent Diffusion Models (LDMs) have gained significant atten

Jingyi Chen, Micha Elsner

This paper explores how Generative Adversarial Networks (GANs) learn representations of phonological phenomena. We analyze how GANs encode contrastive and non-contrastive nasality in French and English vowels by applying the ciwGAN architecture (Begus 2021a). Begus claims that ciwGAN encodes linguistically meaningful representations with categorical variable

John L. Heilbron, Carlo Rovelli

We examine evaluations of the contributions of Matrix Mechanics and Max Born to the formulation of quantum mechanics from Heisenberg's Helgoland paper of 1925 to Born's Nobel Prize of 1954. We point out that the process of evaluation is continuing in the light of recent interpretations of the theory that deemphasize the importance of the wave function.

Sanju Mandal, Partha Pratim Roy, Molla Basir Ahamed

The Hankel determinant $H_{2,2}(F_{f}/2)$ is defined as: \begin{align*} H_{2,2}(F_{f}/2):= \begin{vmatrix} \gamma_2 & \gamma_3 \gamma_3 & \gamma_4 \end{vmatrix}, \end{align*} where $\gamma_2, \gamma_3,$ and $\gamma_4$ are the second, third, and fourth logarithmic coefficients of functions belonging to the class $\mathcal{S}$ of normalized univalent functions

Abdul Khaliq, Sabina Lewinska, Roman Minikaev, Monika Arciszewska

We report the structural and magnetic results of polar {\alpha}-GeTe doped with Sn and Mn from x = 0.185 to 0.841 and y = 0.02 to 0.086, respectively. The magnetic results of Ge1-x-y(SnxMny)Te (GSMT) crystals identify Mn-clustering effect with scaling parameter, R = 0.033 for x ~ 0.2 and y = 0.06. The excessive Sn ions are assumed to drive the inception of s

Yassir Fathullah, Chunyang Wu, Yuan Shangguan, Junteng Jia

State space models (SSMs) have recently shown promising results on small-scale sequence and language modelling tasks, rivalling and outperforming many attention-based approaches. In this paper, we propose a multi-head state space (MH-SSM) architecture equipped with special gating mechanisms, where parallel heads are taught to learn local and global temporal

Yuan Dong, Chuan Fang, Liefeng Bo, Zilong Dong

Panoramic image enables deeper understanding and more holistic perception of $360^\circ$ surrounding environment, which can naturally encode enriched scene context information compared to standard perspective image. Previous work has made lots of effort to solve the scene understanding task in a bottom-up form, thus each sub-task is processed separately and

Juhi Jang, Pranava Chaitanya Jayanti, Igor Kukavica

We investigate a micro-scale model of superfluidity derived by Pitaevskii in 1959 to describe the interacting dynamics between the superfluid and normal fluid phases of Helium-4. The model involves the nonlinear Schr\"odinger equation (NLS) and the Navier-Stokes equations (NSE), coupled to each other via a bidirectional nonlinear relaxation mechanism. Depend

Gaurav Maheshwari, Aurélien Bellet, Pascal Denis, Mikaela Keller

In this work, we consider the problem of intersectional group fairness in the classification setting, where the objective is to learn discrimination-free models in the presence of several intersecting sensitive groups. First, we illustrate various shortcomings of existing fairness measures commonly used to capture intersectional fairness. Then, we propose a

Alexander Mang

The first quantum group cohomology with trivial coefficients of the discrete dual of any unitary easy quantum group is computed. That includes those potential quantum groups whose associated categories of two-colored partitions have not yet been found.

Kaixun Huang, Ao Zhang, Zhanheng Yang, Pengcheng Guo

Contextual information plays a crucial role in speech recognition technologies and incorporating it into the end-to-end speech recognition models has drawn immense interest recently. However, previous deep bias methods lacked explicit supervision for bias tasks. In this study, we introduce a contextual phrase prediction network for an attention-based deep bi

Roberto Maiolino, Jan Scholtz, Joris Witstok, Stefano Carniani

Multiple theories have been proposed to describe the formation of black hole seeds in the early Universe and to explain the emergence of very massive black holes observed in the first billion years after Big Bang. Models consider different seeding and accretion scenarios, which require the detection and characterisation of black holes in the first few hundre

Ilya Ernston, Arsenii Onuchin, Timofey Adamovich

The functional network of the brain continually adapts to changing environmental demands. The environmental changes closely connect with changes of active cognitive processes. In recent years, the network approach has emerged as a promising method for analyzing the neurophysiological mechanisms that underlie psychological functions. The present study examine

Meijian Li, Tuomas Lappi, Xingbo Zhao, Carlos A. Salgado

Following the non-perturbative light-front Hamiltonian formalism developed in our preceding work [Phys.Rev.D 104 (2021) 5, 056014], we investigate the momentum broadening of a quark jet inside a SU(3) colored medium. We perform the numerical simulation of the real-time jet evolution in Fock spaces of a single quark, a quark-gluon state, and coupled quark- an

Maria Clara Fittipaldi, Adrián González Casanova, Julio Ernesto Nava

We present a lookdown construction for a Moran seed-bank model with variable active and inactive population sizes and we show that the empirical measure of our model coincides with that of the Seed-Bank-Moran Model with latency of Greven, den Hollander and Oomen, 2022. Furthermore, we prove that the time to the most recent common ancestor, starting from $N$

Thoma Zoto, John C. Bowman

A quantitative definition of numerical stiffness for initial value problems is proposed. Exponential integrators can effectively integrate linearly stiff systems, but they become expensive when the linear coefficient is a matrix, especially when the time step is adapted to maintain a prescribed local error. Schur decomposition is shown to avoid the need for

Cédric Colas, Laetitia Teodorescu, Pierre-Yves Oudeyer, Xingdi Yuan

Humans learn to master open-ended repertoires of skills by imagining and practicing their own goals. This autotelic learning process, literally the pursuit of self-generated (auto) goals (telos), becomes more and more open-ended as the goals become more diverse, abstract and creative. The resulting exploration of the space of possible skills is supported by

Vladimir Kanovei

It was established by Jensen in 1970 that there is a generic extension $L[a]$ of the constructible universe $L$ by a real $a\not\in L$ such that $a$ is $\varDelta^1_3$ in $L[a]$. Jensen's forcing construction has found a number of applications in modern set theory. A problem has been recently discussed whether Jensen's construction can be reproduced entirely

Limao Xiong, Jie Zhou, Qunxi Zhu, Xiao Wang

Existing models for named entity recognition (NER) are mainly based on large-scale labeled datasets, which always obtain using crowdsourcing. However, it is hard to obtain a unified and correct label via majority voting from multiple annotators for NER due to the large labeling space and complexity of this task. To address this problem, we aim to utilize the

Yibo Wu, Luca Sanguinetti, Ulf Gustavsson, Alexandre Graell i Amat

Cell-Free massive MIMO networks provide huge power gains and resolve inter-cell interference by coherent processing over a massive number of distributed instead of co-located antennas in access points (APs). Cost-efficient hardware is preferred but imperfect local oscillators in both APs and users introduce multiplicative phase noise (PN), which affects the

Konstantinos Papakostas, Irene Papadopoulou

Ambiguous questions are a challenge for Question Answering models, as they require answers that cover multiple interpretations of the original query. To this end, these models are required to generate long-form answers that often combine conflicting pieces of information. Although recent advances in the field have shown strong capabilities in generating flue

Florio M. Ciaglia, Fabio Di Cosmo, Laura González-Bravo

We discuss how to exploit the recent formulation of classical and quantum information geometry in terms of normal states on $W^{*}$-algebras to formulate a problem that unifies Cencov's theorem and Petz's theorem.

Yang Yu, Huiwen Jia, Xiaoyun Wang

This work aims to improve the practicality of gadget-based cryptosystems, with a focus on hash-and-sign signatures. To this end, we develop a compact gadget framework in which the used gadget is a square matrix instead of the short and fat one used in previous constructions. To work with this compact gadget, we devise a specialized gadget sampler, called sem

Lei Shen, Shuai Yu, Xiaoyu Shen

Cross-lingual transfer is important for developing high-quality chatbots in multiple languages due to the strongly imbalanced distribution of language resources. A typical approach is to leverage off-the-shelf machine translation (MT) systems to utilize either the training corpus or developed models from high-resource languages. In this work, we investigate

Florio M. Ciaglia aand Fabio Di Cosmo

In this paper some reflections on the concept of transition are presented: groupoids are introduced as models for the construction of a ``generalized logic'' whose basic statements involve pairs of propositions which can be conditioned. In this sense, we could distinguish between classical probability theory where propositions can be conditioned if they have

Yesid Ospitia Medina

This article discusses the importance of sound for virtual reality systems. For this, the emotional effects generated by sound are analyzed, and its contribution to the effect of immersion.

Jinchuan Cui, Xiaoya Li

The airplane refueling problem is a nonlinear combinatorial optimization problem, and its equivalent problem the $n$-vehicle exploration problem is proved to be NP-complete (arXiv:2304.03965v1, The $n$-vehicle exploration problem is NP-complete). In Article (arXiv:2210.11634v2, A polynomial-time algorithm to solve the aircraft refueling problem: the sequenti

Jessica López Espejel, El Hassane Ettifouri, Mahaman Sanoussi Yahaya Alassan, El Mehdi Chouham

Large Language Models (LLMs) have exhibited remarkable performance on various Natural Language Processing (NLP) tasks. However, there is a current hot debate regarding their reasoning capacity. In this paper, we examine the performance of GPT-3.5, GPT-4, and BARD models, by performing a thorough technical evaluation on different reasoning tasks across eleven

Lin Li, Jun Xiao, Guikun Chen, Jian Shao

Pretrained vision-language models, such as CLIP, have demonstrated strong generalization capabilities, making them promising tools in the realm of zero-shot visual recognition. Visual relation detection (VRD) is a typical task that identifies relationship (or interaction) types between object pairs within an image. However, naively utilizing CLIP with preval

Junchi Yang, Xiang Li, Ilyas Fatkhullin, Niao He

The classical analysis of Stochastic Gradient Descent (SGD) with polynomially decaying stepsize $\eta_t = \eta/\sqrt{t}$ relies on well-tuned $\eta$ depending on problem parameters such as Lipschitz smoothness constant, which is often unknown in practice. In this work, we prove that SGD with arbitrary $\eta > 0$, referred to as untuned SGD, still attains an

Xiaotian Zhang, Chunyang Li, Yi Zong, Zhengyu Ying

Large Language Models(LLMs) have demonstrated remarkable performance across various natural language processing tasks; however, how to comprehensively and accurately assess their performance becomes an urgent issue to be addressed. This paper introduces GAOKAO-Bench, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test sa

Ge Gao, Hung-Ting Chen, Yoav Artzi, Eunsol Choi

We study continually improving an extractive question answering (QA) system via human user feedback. We design and deploy an iterative approach, where information-seeking users ask questions, receive model-predicted answers, and provide feedback. We conduct experiments involving thousands of user interactions under diverse setups to broaden the understanding

Tommaso Bertapelle, Marco Avesani, Alberto Santamato, Alberto Montanaro

A wide range of applications require, by hypothesis, to have access to a high-speed, private, and genuine random source. Quantum Random Number Generators (QRNGs) are currently the sole technology capable of producing true randomness. However, the bulkiness of current implementations significantly limits their adoption. In this work, we present a high-perform

Jingyang Ma, Songting Li, Douglas Zhou

Dendrites are crucial structures for computation of an individual neuron. It has been shown that the dynamics of a biological neuron with dendrites can be approximated by artificial neural networks (ANN) with deep structure. However, it remains unclear whether a neuron can be further captured by a simple, biologically plausible ANN. In this work, we develop

Isaac Reid, Krzysztof Choromanski, Adrian Weller

We present a novel mechanism to improve the accuracy of the recently-introduced class of graph random features (GRFs). Our method induces negative correlations between the lengths of the algorithm's random walks by imposing antithetic termination: a procedure to sample more diverse random walks which may be of independent interest. It has a trivial drop-in i

Linquan Ma, Pham Hung Quy, Ilya Smirnov

Let $(R, \mathfrak{m})$ be a Noetherian local ring. This paper concerns several extremal invariants arising from the study of the relation between colength and (Hilbert--Samuel or Hilbert--Kunz) multiplicity of an $\mathfrak{m}$-primary ideal. We introduce versions of these invariants by restricting to various closures and ``cross-pollinate'' the two multipl

A. Ben Yehuda, O. Sefi, Y. Klein, R. H Shukrun

X-ray imaging is a prevalent technique for non-invasively visualizing the interior of the human body and opaque instruments. In most commercial x-ray modalities, an image is formed by measuring the x-rays that pass through the object of interest. However, despite the potential of scattered radiation to provide additional information about the object, it is o

Mingze Wang, Chao Ma

The training process of ReLU neural networks often exhibits complicated nonlinear phenomena. The nonlinearity of models and non-convexity of loss pose significant challenges for theoretical analysis. Therefore, most previous theoretical works on the optimization dynamics of neural networks focus either on local analysis (like the end of training) or approxim

Ziqiang Cai, Tong-Yu He, Wen-Qian Wang, Zhan-Wen Han

We consider the geodesic motions in the Kerr-Sen-AdS$_4$ spacetime. We obtain the equations of motion for light rays and test particles. Using the parametric diagrams, we shown some regions where the radial and latitudinal geodesic motions are allowed. We analyse the impact of parameter related to dilatonic scalar on the orbit and find that it will result in

Oli Liu, Hao Tang, Sharon Goldwater

Self-supervised speech representations are known to encode both speaker and phonetic information, but how they are distributed in the high-dimensional space remains largely unexplored. We hypothesize that they are encoded in orthogonal subspaces, a property that lends itself to simple disentanglement. Applying principal component analysis to representations

Renliang Sun, Wei Xu, Xiaojun Wan

Randomly masking text spans in ordinary texts in the pre-training stage hardly allows models to acquire the ability to generate simple texts. It can hurt the performance of pre-trained models on text simplification tasks. In this paper, we propose a new continued pre-training strategy to teach the pre-trained model to generate simple texts. We continue pre-t

Sachiraj Mishra, Ritesh Das, Colin Benjamin

A two-terminal quantum spin-Hall heat engine and refrigerator with embedded Majorana bound states (MBS) is analyzed for optimality in thermoelectric performance using the Landaeur-Buttiker approach. This investigation can be an effective tool to detect MBS. Furthermore, the occurrence of MBS can enhance the performance to rival, as well as outperform, some m

Wei Li, Borui Yang, Yujie Sun, Suyu Chen

Recent advances in large language models have raised wide concern in generating abundant plausible source code without scrutiny, and thus tracing the provenance of code emerges as a critical issue. To solve the issue, we propose CodeMark, a watermarking system that hides bit strings into variables respecting the natural and operational semantics of the code.

Leander Melroy Maben, Zixun Guo, Chen Chen, Utkarsh Chudiwal

The performance of speech processing models trained on clean speech drops significantly in noisy conditions. Training with noisy datasets alleviates the problem, but procuring such datasets is not always feasible. Noisy speech simulation models that generate noisy speech from clean speech help remedy this issue. In our work, we study the ability of Generativ

Mohan Shi, Zhihao Du, Qian Chen, Fan Yu

Recently, speaker-attributed automatic speech recognition (SA-ASR) has attracted a wide attention, which aims at answering the question ``who spoke what''. Different from modular systems, end-to-end (E2E) SA-ASR minimizes the speaker-dependent recognition errors directly and shows a promising applicability. In this paper, we propose a context-aware SA-ASR (C

Wenxi Tan

The prevalence of Transformer-based pre-trained language models (PLMs) has led to their wide adoption for various natural language processing tasks. However, their excessive overhead leads to large latency and computational costs. The statically compression methods allocate fixed computation to different samples, resulting in redundant computation. The dynam

Mengyin Liu, Chao Zhu, Shiqi Ren, Xu-Cheng Yin

With the prosperity of the video surveillance, multiple cameras have been applied to accurately locate pedestrians in a specific area. However, previous methods rely on the human-labeled annotations in every video frame and camera view, leading to heavier burden than necessary camera calibration and synchronization. Therefore, we propose in this paper an Uns

Emily J. Evans, Russell J. Hendel

The 2022 Fibonacci Conference held in Sarajevo introduced the Circuit Array, a two-dimensional array associated with the resistance labels of electrical circuits whose underlying graph when embedded in the Cartesian plane has the form of a triangular n-grid. The presentation used row reduction, a computational method alternative to the traditional method usi

Jiahe Pan, Kerry He, Jia Ming Ong, Akansel Cosgun

We propose enhancing trajectory optimization methods through the incorporation of two key ideas: variable-grasp pose sampling and trajectory commitment. Our iterative approach samples multiple grasp poses, increasing the likelihood of finding a solution while gradually narrowing the optimization horizon towards the goal region for improved computational effi

Juan F. Giraldo, Victor M. Calo

This paper interprets the stabilized finite element method via residual minimization as a variational multiscale method. We approximate the solution to the partial differential equations using two discrete spaces that we build on a triangulation of the domain; we denote these spaces as coarse and enriched spaces. Building on the adaptive stabilized finite el

Markus Ulbricht, Nico Potyka, Anna Rapberger, Francesca Toni

Assumption-based Argumentation (ABA) is a well-known structured argumentation formalism, whereby arguments and attacks between them are drawn from rules, defeasible assumptions and their contraries. A common restriction imposed on ABA frameworks (ABAFs) is that they are flat, i.e., each of the defeasible assumptions can only be assumed, but not derived. Whil

Yixuan Wu, Zhao Zhang, Xie Chi, Feng Zhu

Referring Expression Segmentation (RES) is a widely explored multi-modal task, which endeavors to segment the pre-existing object within a single image with a given linguistic expression. However, in broader real-world scenarios, it is not always possible to determine if the described object exists in a specific image. Typically, we have a collection of imag

Mizuki Yoshizawa, Akira Terui, Masahiko Mikawa

Methods for inverse kinematics computation and path planning of a three degree-of-freedom (DOF) manipulator using the algorithm for quantifier elimination based on Comprehensive Gr\"obner Systems (CGS), called CGS-QE method, are proposed. The first method for solving the inverse kinematics problem employs counting the real roots of a system of polynomial equ

Mohan Shi, Yuchun Shu, Lingyun Zuo, Qian Chen

For speech interaction, voice activity detection (VAD) is often used as a front-end. However, traditional VAD algorithms usually need to wait for a continuous tail silence to reach a preset maximum duration before segmentation, resulting in a large latency that affects user experience. In this paper, we propose a novel semantic VAD for low-latency segmentati

Yi Liu, Xiaohan Bi, Lei Li, Sishuo Chen

Federated Multilingual Neural Machine Translation (Fed-MNMT) has emerged as a promising paradigm for institutions with limited language resources. This approach allows multiple institutions to act as clients and train a unified model through model synchronization, rather than collecting sensitive data for centralized training. This significantly reduces the

Hiromu Nakano

We study the structure of the abelian category of modules for the triplet $W$-algebra $\mathcal{W}_{p_+,p_-}$. Using the logarithmic deformation by Fjelstad et al., we construct logarithmic $\mathcal{W}_{p_+,p_-}$-modules that have $L_0$ nilpotent rank three or two. By using the structure of these logarithmic modules and the results on logarithmic Virasoro m

Mingzhe Hu, Yuheng Li, Xiaofeng Yang

Breast cancer is one of the most common cancers among women worldwide, with early detection significantly increasing survival rates. Ultrasound imaging is a critical diagnostic tool that aids in early detection by providing real-time imaging of the breast tissue. We conducted a thorough investigation of the Segment Anything Model (SAM) for the task of intera

Robin Persoons, Mattia Sensi, Bastian Prasse, Piet Van Mieghem

We extend the N-Intertwined Mean-Field Approximation (NIMFA) for the Susceptible-Infectious-Susceptible (SIS) epidemiological process to time-varying networks. Processes on time-varying networks are often analysed under the assumption that the process and network evolution happen on different timescales. This approximation is called timescale separation. We

Detai Xin, Shinnosuke Takamichi, Hiroshi Saruwatari

We present JNV (Japanese Nonverbal Vocalizations) corpus, a corpus of Japanese nonverbal vocalizations (NVs) with diverse phrases and emotions. Existing Japanese NV corpora lack phrase or emotion diversity, which makes it difficult to analyze NVs and support downstream tasks like emotion recognition. We first propose a corpus-design method that contains two

Nai-Hui Chia, Kai-Min Chung, Yao-Ching Hsieh, Han-Hsuan Lin

Hamiltonian simulation is one of the most important problems in the field of quantum computing. There have been extended efforts on designing algorithms for faster simulation, and the evolution time $T$ for the simulation turns out to largely affect algorithm runtime. While there are some specific types of Hamiltonians that can be fast-forwarded, i.e., simul