March 2024 arXiv papers — page 3

Krzysztof Gogol, Yaron Velner, Benjamin Kraner, Claudio Tessone

Liquid staking and restaking represent recent innovations in Decentralized Finance (DeFi) that garnered user interest and capital. Liquid Staking Tokens (LSTs), tokenized representations of staked tokens on Proof-of-Stake (PoS) blockchains, are the leading staking method. LSTs offer users the ability to earn staking rewards while maintaining liquidity, enabl

M. Zeeshan Gul, M. Sharif, Adeeba Arooj

The main objective of this article is to study the viable compact stellar structures in non-Riemannian geometry, i.e., $f(\mathbb{Q},T)$ theory, where $\mathbb{Q}$ defines the non-metricity and $T$ represents trace of the stress-energy tensor. In this perspective, we consider a static spherical metric with anisotropic matter configuration to examine the geom

Henrique C. Prates, Vladimir V. Konotop

Bloch oscillations and Landau-Zener tunneling are ubiquitous phenomena which are sustained by a band-gap spectrum of a periodic Hamiltonian and can be observed in dynamics of a quantum particle or a wavepacket in a periodic potential under action of a linear force. Such physical setting remains meaningful for aperiodic potentials too, although band-gap struc

Shai Evra, Guy Kindler, Noam Lifshitz

We prove a polynomial Bogolyubov type lemma for the special linear group over finite fields. Specifically, we show that there exists an absolute constant $C>0,$ such that if $A$ is a density $\alpha$ subset of the special linear group, then the set $AA^{-1}AA^{-1}$ contains a subgroup $H$ of density $\alpha^C$. Moreover, this subgroup is isomorphic to a spec

Shiwen Shan, Yintong Huo, Yuxin Su, Yichen Li

Configurable software systems are prone to configuration errors, resulting in significant losses to companies. However, diagnosing these errors is challenging due to the vast and complex configuration space. These errors pose significant challenges for both experienced maintainers and new end-users, particularly those without access to the source code of the

Dongsheng Zuo, Jiadong Zhu, Yikang Ouyang, Yuzhe Ma

Multiplication is a fundamental operation in many applications, and multipliers are widely adopted in various circuits. However, optimizing multipliers is challenging due to the extensive design space. In this paper, we propose a multiplier design optimization framework based on reinforcement learning. We utilize matrix and tensor representations for the com

Sunwoo Kim, Shinhwan Kang, Fanchen Bu, Soo Yong Lee

Hypergraphs are marked by complex topology, expressing higher-order interactions among multiple nodes with hyperedges, and better capturing the topology is essential for effective representation learning. Recent advances in generative self-supervised learning (SSL) suggest that hypergraph neural networks learned from generative self supervision have the pote

Xiangyu Chen, Qiang Lei

In this paper, we introduce two measures for the resource theory of imaginarity. One is induced by $\alpha$--$z$--R\'enyi relative entropy and the other, defined for positive definite density matrices, is induced by Tsallis relative operator entropy. The relationships between different imaginarity measures and their properties are also discussed.

Taekyung Ki, Dongchan Min, Gyeongsu Chae

In this paper, we present Export3D, a one-shot 3D-aware portrait animation method that is able to control the facial expression and camera view of a given portrait image. To achieve this, we introduce a tri-plane generator with an effective expression conditioning method, which directly generates a tri-plane of 3D prior by transferring the expression paramet

Oluwaleke Yusuf, Adil Rasheed, Frank Lindseth

The growth of urban areas intensifies the need for sustainable, efficient transportation infrastructure and mobility systems, driving initiatives to enhance infrastructure and public transit while reducing traffic congestion and emissions. By utilizing real-world data, a data-driven approach can provide crucial insights for urban mobility planning and decisi

Alkis Koudounas, Flavio Giobergia

The Fearless Steps APOLLO Community Resource provides unparalleled opportunities to explore the potential of multi-speaker team communications from NASA Apollo missions. This study focuses on discovering the characteristics that make Apollo recordings more or less intelligible to Automatic Speech Recognition (ASR) methods. We extract, for each audio recordin

Abhishek Chakraborty, Angelia Nedić

We consider the mirror-prox algorithm for solving monotone Variational Inequality (VI) problems. As the mirror-prox algorithm is not practically implementable, except in special instances of VIs (such as affine VIs), we consider its implementation with Popov method updates. We provide convergence rate analysis of our proposed method for a monotone VI with a

Samuel Aleksander Sánchez Olszewski

AI is redefining how humans interact with technology, leading to a synergetic collaboration between the two. Nevertheless, the effects of human cognition on this collaboration remain unclear. This study investigates the implications of two cognitive biases, anthropomorphism and framing effect, on human-AI collaboration within a hiring setting. Subjects were

Zhijun Tu, Kunpeng Du, Hanting Chen, Hailing Wang

Recent advances have demonstrated the powerful capability of transformer architecture in image restoration. However, our analysis indicates that existing transformerbased methods can not establish both exact global and local dependencies simultaneously, which are much critical to restore the details and missing content of degraded images. To this end, we pre

Koki Suetsugu

The disjunctive sum of impartial games is analyzed by Sprague-Grundy theory. The theory has been extended to loopy games and entailing games by early results. In this study, we consider further extension of this theory and show partial algebraic structure of the sum of loopy positions and entailing positions.

Qingrui Fan, Yu Zhang, Jiamin Li, Dongming Wang

This paper investigates the network-assisted full-duplex (NAFD) cell-free millimeter-wave (mmWave) networks, where the distribution of the transmitting access points (T-APs) and receiving access points (R-APs) across distinct geographical locations mitigates cross-link interference, facilitating the attainment of a truly flexible duplex mode. To curtail depl

Qingwen Zhang, Wenjia Wang

Calibration refers to the statistical estimation of unknown model parameters in computer experiments, such that computer experiments can match underlying physical systems. This work develops a new calibration method for imperfect computer models, Sobolev calibration, which can rule out calibration parameters that generate overfitting calibrated functions. We

Utsha Roy, Mst. Sazia Tahosin, Md. Mahedi Hassan, Taminul Islam

The rise of fake news has made the need for effective detection methods, including in languages other than English, increasingly important. The study aims to address the challenges of Bangla which is considered a less important language. To this end, a complete dataset containing about 50,000 news items is proposed. Several deep learning models have been tes

Lizhi Lin, Honglin Mu, Zenan Zhai, Minghan Wang

Generative models are rapidly gaining popularity and being integrated into everyday applications, raising concerns over their safe use as various vulnerabilities are exposed. In light of this, the field of red teaming is undergoing fast-paced growth, highlighting the need for a comprehensive survey covering the entire pipeline and addressing emerging topics.

Ruopeng Xu, Yixuan Chen, Jiawen Kang, Minrui Xu

In this paper, we investigate the problem of resource allocation for fluid antenna relay (FAR) system with antenna location optimization. In the considered model, each user transmits information to a base station (BS) with help of FAR. The antenna location of the FAR is flexible and can be adapted to dynamic location distribution of the users. We formulate a

Imed Basdouri, Sami Benabdelhafidh, Mohamed Amin Sadraoui, Ripan Saha

This paper presents a cohomological study of modified Rota-Baxter associative algebras in the presence of derivations. The Modified Rota-Baxter operator, which is a modified version and closely related to the classical Rota-Baxter operator, has garnered significant attention due to its applications in various mathematical and physical contexts. In this study

Minyoung Oh, Duhyun Kim, Jae-Young Sim

Collecting and labeling real datasets to train the person search networks not only requires a lot of time and effort, but also accompanies privacy issues. The weakly-supervised and unsupervised domain adaptation methods have been proposed to alleviate the labeling burden for target datasets, however, their generalization capability is limited. We introduce a

Jiamin Wang, Jian Liu, Feng Xiao, Ning Xi

Motivated by widespread dominance hierarchy, growth of group sizes, and feedback mechanisms in social species, we are devoted to exploring the scalable second-order consensus of hierarchical groups. More specifically, a hierarchical group consists of a collection of agents with double-integrator dynamics on a directed acyclic graph with additional reverse ed

Tapas Chatterjee, Sagar Mandal, Sourav Mandal

Solitary numbers are shrouded with mystery. A folklore conjecture assert that 10 is a solitary number i.e. it has no friends. In this article, we establish that if $N$ is a friend of $10$ then it must be odd square with at least seven distinct prime factors, with $5$ being the least one. Moreover there exists a prime factor $p$ of $N$ such that $2a+1\equiv 0

Thomas Nakken Larsen, Eirik Runde Barlaug, Adil Rasheed

Modern control systems are increasingly turning to machine learning algorithms to augment their performance and adaptability. Within this context, Deep Reinforcement Learning (DRL) has emerged as a promising control framework, particularly in the domain of marine transportation. Its potential for autonomous marine applications lies in its ability to seamless

Shi Meng, Bin Tian, Xiaotong Zhang, Shuangying Qi

Mine fleet management algorithms can significantly reduce operational costs and enhance productivity in mining systems. Most current fleet management algorithms are evaluated based on self-implemented or proprietary simulation environments, posing challenges for replication and comparison. This paper models the simulation environment for mine fleet managemen

Qijiong Liu, Jieming Zhu, Yanting Yang, Quanyu Dai

Personalized recommendation serves as a ubiquitous channel for users to discover information tailored to their interests. However, traditional recommendation models primarily rely on unique IDs and categorical features for user-item matching, potentially overlooking the nuanced essence of raw item contents across multiple modalities such as text, image, audi

Deborah N. Jakobi, Daniel G. Krakowczyk, Lena A. Jäger

Eye-tracking datasets are often shared in the format used by their creators for their original analyses, usually resulting in the exclusion of data considered irrelevant to the primary purpose. In order to increase re-usability of existing eye-tracking datasets for more diverse and initially not considered use cases, this work advocates a new approach of sha

Shengxuan Zhou

Let $n\geq 3$, $\lambda \in \mathbb{R} $, and $(X,h)$ be an $n$-dimensional smooth complete Riemannian manifold with ${\rm Ric}_h > \lambda $. In this paper, we construct, for each given $\epsilon >0$, a sequence of $(n+2)$-dimensional manifolds $(M_{i} ,g_i ) \stackrel{GH}{\longrightarrow} (X_\epsilon ,d_\epsilon ) $ with ${\rm Ric}_{g_i} > \lambda $, such

Aarush Sinha

In this study, we propose a multi branched network approach to predict the dynamics of a physics attractor characterized by intricate and chaotic behavior. We introduce a unique neural network architecture comprised of Radial Basis Function (RBF) layers combined with an attention mechanism designed to effectively capture nonlinear inter-dependencies inherent

A de Oliveira Junior

In this thesis, I investigate various aspects of one of the most fundamental questions in thermodynamics: what state transformations can quantum systems undergo while interacting with a thermal bath under specific constraints? These constraints may involve total energy conservation, memory effects, or finite-size considerations. Addressing this question lead

Eric Madge, Gilad Perez, Ziv Meir

The nature of dark matter (DM) and its interaction with the Standard Model (SM) is one of the biggest open questions in physics nowadays. The vast majority of theoretically-motivated Ultralight-DM (ULDM) models predict that ULDM couples dominantly to the SM strong/nuclear sector. This coupling leads to oscillations of nuclear parameters that are detectable b

Ritwick Sarkar, Ion Santra, Urna Basu

Characterizing the properties of an extended system driven by active reservoirs is a question of increasing importance. Here we address this question in two steps. We start by investigating the dynamics of a probe particle connected to an `active Rubin bath' -- a linear chain of overdamped run-and-tumble particles. We derive exact analytical expressions for

Nathan Cornille, Marie-Francine Moens, Florian Mai

By training to predict the next token in an unlabeled corpus, large language models learn to perform many tasks without any labeled data. However, their next-token-prediction objective arguably limits their performance in scenarios that require planning, such as writing a coherent article. In this paper, we train a module for planning the future writing proc

Awadhesh Kumar Shukla, Sachin Pathak, Om Prakash Pandey, Vipul Mishra

Let $\mathbb F_q$ be a finite field, where $q$ is an odd prime power. Let $R=\mathbb{F}_q+u\mathbb{F}_q+v\mathbb{F}_q+uv\mathbb F_q$ with $u^2=u,v^2=v,uv=vu$. In this paper, we study the algebraic structure of $(\theta, \Theta)$-cyclic codes of block length $(r,s )$ over $\mathbb{F}_qR.$ Specifically, we analyze the structure of these codes as left $R[x:\The

Ruopeng Xu, Zhaohui Yang, Zhouxiang Zhao, Qianqian Yang

In this paper, the energy efficient design for probabilistic semantic communication (PSC) system with rate splitting multiple access (RSMA) is investigated. Basic principles are first reviewed to show how the PSC system works to extract, compress and transmit the semantic information in a task-oriented transmission. Subsequently, the process of how multiuser

Jingyu Wang, Niantai Jing, Ziyao Liu, Jie Nie

In copy-move tampering operations, perpetrators often employ techniques, such as blurring, to conceal tampering traces, posing significant challenges to the detection of object-level targets with intact structures. Focus on these challenges, this paper proposes an Object-level Copy-Move Forgery Image Detection based on Inconsistency Mining (IMNet). To obtain

Chi-Min Chan, Chunpu Xu, Ruibin Yuan, Hongyin Luo

Large Language Models (LLMs) exhibit remarkable capabilities but are prone to generating inaccurate or hallucinatory responses. This limitation stems from their reliance on vast pretraining datasets, making them susceptible to errors in unseen scenarios. To tackle these challenges, Retrieval-Augmented Generation (RAG) addresses this by incorporating external

Victor Atanasov, Avadh Saxena

The conditions required by quantum matter to modify space-time geometry are explored within the framework of the general theory of relativity. The required characteristics for space-time modification in solid state structures, are met in either (a) massive photon Bose-Einstein condensate in a waveguide, or (b) the massive photons in superconductor's bulk, or

Huaiyu Jian, Xushan Tu

In this paper, we investigate the strong maximum principle for generalized solutions of Monge-Amp\`ere type equations. We prove that the strong maximum principle holds at points where the function is strictly convex but not necessarily $C^{1,1}$ smooth, and show that it fails at non-strictly convex points. The results we obtain can be applied to various Mink

Apurv Shukla, Qian Zhang, Le Xie

We study the scenario approach for solving chance-constrained optimization in time-coupled dynamic environments. Scenario generation methods approximate the true feasible region from scenarios generated independently and identically from the actual distribution. In this paper, we consider this problem in a dynamic environment, where the scenarios are assumed

Lora R. Du, Kathy Q. Ji

The note is dedicated to refining a theorem by Diaconis, Evans, and Graham concerning successions and fixed points of permutations. This refinement specifically addresses non-adjacent successions, predecessors, excedances, and drops of permutations.

Richard Y. Chen

This paper resolves a pivotal open problem on nonparametric inference for nonlinear functionals of volatility matrix. Multiple prominent statistical tasks can be formulated as functionals of volatility matrix, yet a unified statistical theory of general nonlinear functionals based on noisy data remains challenging and elusive. Nonetheless, this paper shows i

Ahmad Mousavi, Maziar Salahi, Zois Boukouvalas

This paper introduces a novel penalty decomposition algorithm customized for addressing the non-differentiable and nonconvex problem of extended mean-variance-CVaR portfolio optimization with short-selling and cardinality constraints. The proposed algorithm solves a sequence of penalty subproblems using a block coordinate descent (BCD) method while striving

Xiao Liu, Xixuan Song, Yuxiao Dong, Jie Tang

Reinforcement learning from human feedback (RLHF) has been a central technique for recent large language model (LLM) alignment. However, its heavy dependence on costly human or LLM-as-Judge preference feedback could stymie its wider applications. In this work, we introduce Self-Contrast, a feedback-free large language model alignment method via exploiting ex

Kun Ding, Haojian Zhang, Qiang Yu, Ying Wang

We propose a generalized method for boosting the generalization ability of pre-trained vision-language models (VLMs) while fine-tuning on downstream few-shot tasks. The idea is realized by exploiting out-of-distribution (OOD) detection to predict whether a sample belongs to a base distribution or a novel distribution and then using the score generated by a d

Masayuki Tezuka, Keisuke Tanaka

1-out-of-n oblivious signature by Chen (ESORIC 1994) is a protocol between the user and the signer. In this scheme, the user makes a list of n messages and chooses the message that the user wants to obtain a signature from the list. The user interacts with the signer by providing this message list and obtains the signature for only the chosen message without

Lichen Wang, Yuyuan Liu, Ruqiang Guo, Liang Zhang

In contemporary society, the effective utilization of public resources remains a subject of significant concern. A common issue arises from defectors seeking to obtain an excessive share of these resources for personal gain, potentially leading to resource depletion. To mitigate this tragedy and ensure sustainable development of resources, implementing mecha

Nicola Fabiano

The imposing evolution of artificial intelligence systems and, specifically, of Large Language Models (LLM) makes it necessary to carry out assessments of their level of risk and the impact they may have in the area of privacy, personal data protection and at an ethical level, especially on the weakest and most vulnerable. This contribution addresses human o

Jia Li, Ge Li, Xuanming Zhang, Yihong Dong

How to evaluate Large Language Models (LLMs) in code generation is an open question. Existing benchmarks demonstrate poor alignment with real-world code repositories and are insufficient to evaluate the coding abilities of LLMs. This paper proposes a new benchmark - EvoCodeBench to address the preceding problems, which has three primary advances. (1) EvoCode

T. Y. S. S Santosh, Hassan Sarwat, Ahmed Abdou, Matthias Grabmair

Rhetorical Role Labeling (RRL) of legal judgments is essential for various tasks, such as case summarization, semantic search and argument mining. However, it presents challenges such as inferring sentence roles from context, interrelated roles, limited annotated data, and label imbalance. This study introduces novel techniques to enhance RRL performance by

Jintao Wang, Binggui Zhou, Chengzhi Ma, Shiqi Gong

In this paper, we propose a dynamic hybrid active-passive reconfigurable intelligent surface (HRIS) to enhance multiple-input-single-output (MISO) communications, leveraging the property of dynamically placing active elements. Specifically, considering the impact of hardware impairments (HWIs), we investigate channel-aware configurations of the receive anten

Aryan Garg

We present a simple, highly parameter, and data-efficient adversarial network for unconditional face generation. Our method: Spectral Style-DCGAN or SSD utilizes only 6.574 million parameters and 4739 dog faces from the Animal Faces HQ (AFHQ) dataset as training samples while preserving fidelity at low resolutions up to 64x64. Code available at https://githu

T. Y. S. S Santosh, Rashid Gustav Haddad, Matthias Grabmair

In common law jurisdictions, legal practitioners rely on precedents to construct arguments, in line with the doctrine of \emph{stare decisis}. As the number of cases grow over the years, prior case retrieval (PCR) has garnered significant attention. Besides lacking real-world scale, existing PCR datasets do not simulate a realistic setting, because their que

T. Y. S. S Santosh, Elvin Quero Hernandez, Matthias Grabmair

Legal professionals often grapple with navigating lengthy legal judgements to pinpoint information that directly address their queries. This paper focus on this task of extracting relevant paragraphs from legal judgements based on the query. We construct a specialized dataset for this task from the European Court of Human Rights (ECtHR) using the case law gu

T. Y. S. S Santosh, Mahmoud Aly, Matthias Grabmair

Legal professionals frequently encounter long legal judgments that hold critical insights for their work. While recent advances have led to automated summarization solutions for legal documents, they typically provide generic summaries, which may not meet the diverse information needs of users. To address this gap, we introduce LexAbSumm, a novel dataset des

Jacek Kałużny, Yannik Schreckenberg, Karol Cyganik, Peter Annighöfer

We introduce LAESI, a Synthetic Leaf Dataset of 100,000 synthetic leaf images on millimeter paper, each with semantic masks and surface area labels. This dataset provides a resource for leaf morphology analysis primarily aimed at beech and oak leaves. We evaluate the applicability of the dataset by training machine learning models for leaf surface area predi

Tengjiao Wang

The Cabibbo-Kobayashi-Maskawa (CKM) matrix elements $|V_{cd}|$ and $|V_{cs}|$ are essential to test the unitary of CKM matrix. Before 2014, many results of $|V_{cd}|$ and $|V_{cs}|$ had been reported at BaBar, Belle, and CLEO experiments. The precisions of the most accurate results of $|V_{cd}|$ and $|V_{cs}|$ are 4.4\% and 3.3\%, respectively. After that, b

Shunpeng Yang, Zejun Hong, Sen Li, Patrick Wensing

This manuscript primarily aims to enhance the performance of whole-body controllers(WBC) for underactuated legged locomotion. We introduce a systematic parameter design mechanism for the floating-base feedback control within the WBC. The proposed approach involves utilizing the linearized model of unactuated dynamics to formulate a Linear Quadratic Regulator

T. Y. S. S Santosh, Kristina Kaiser, Matthias Grabmair

In this paper, we introduce CuSINeS, a negative sampling approach to enhance the performance of Statutory Article Retrieval (SAR). CuSINeS offers three key contributions. Firstly, it employs a curriculum-based negative sampling strategy guiding the model to focus on easier negatives initially and progressively tackle more difficult ones. Secondly, it leverag

Zhenyu Qian, Yiming Qian, Yuting Song, Fei Gao

Handling graph data is one of the most difficult tasks. Traditional techniques, such as those based on geometry and matrix factorization, rely on assumptions about the data relations that become inadequate when handling large and complex graph data. On the other hand, deep learning approaches demonstrate promising results in handling large graph data, but th

Yitian Tao, Liyan Ma, Jing Yu, Han Zhang

Generating radiology reports automatically reduces the workload of radiologists and helps the diagnoses of specific diseases. Many existing methods take this task as modality transfer process. However, since the key information related to disease accounts for a small proportion in both image and report, it is hard for the model to learn the latent relation b

Tianhao Ni, Jun Lai

The phase-field system is a nonlinear model that has significant applications in material sciences. In this paper, we are concerned with the uniqueness of determining the nonlinear energy potential in a phase-field system consisting of Cahn-Hilliard and Allen-Cahn equations. This system finds widespread applications in the development of alloys engineered to

Ao Lv, Guige Ouyang, Yongzhong Huang, Yue Chen

Temporal Knowledge Graph (TKG) reasoning involves predicting future events based on historical information. However, due to the unpredictability of future events, this task is highly challenging. To address this issue, we propose a multi-scale hybrid architecture model based on ensemble learning, called RLGNet (Repeating-Local-Global History Network). Inspir

Jingzhe Shi, Jialuo Li, Qinwei Ma, Zaiwen Yang

Businesses and software platforms are increasingly turning to Large Language Models (LLMs) such as GPT-3.5, GPT-4, GLM-3, and LLaMa-2 for chat assistance with file access or as reasoning agents for customer service. However, current LLM-based customer service models have limited integration with customer profiles and lack the operational capabilities necessa

Aleksei Kulikov

We prove that for the functions of the form $g(x) = h(x) + \frac{C}{x+i}$, where $h$ belongs to the continuous Wiener algebra $W_0$, the intersection of the frame set $\mathcal{F}_g$ with every hyperbola $\{\alpha, \beta > 0 \mid \alpha\beta = c\}$ is open in the relative topology. In particular, this applies to all rational functions $g$.

Arghya Maity, Paranjoy Chaki, Ahana Ghoshal, Ujjwal Sen

We propose a quantum heat transformer (QHT), a quantum thermodynamic device that modulates temperature gradients between two thermal junctions in quantum systems. Functionally, the QHT is analogous to classical absorption heat transformers in its ability to redistribute thermal energy without external work input. Moreover, we show that its performance ratio

Zeraoulia Rafik, Pedro Caceres

This work develops an operator-theoretic and dynamical framework inspired by the Riemann--von Mangoldt formula, chaotic dynamics, and random-matrix models for the Riemann zeta function, without attempting to prove the Riemann Hypothesis. Starting from the explicit zero-counting function $N(T)$, we construct a discrete map on the critical line and analyse its

Salmane Naoumi, Ahmad Bazzi, Roberto Bomfin, Marwa Chafii

Integrated sensing and communication (ISAC) in wireless systems has emerged as a promising paradigm, offering the potential for improved performance, efficient resource utilization, and mutually beneficial interactions between radar sensing and wireless communications, thereby shaping the future of wireless technologies. In this work, we present two novel me

Aloïs Rosset, Maaike Zwart, Helle Hvid Hansen, Jörg Endrullis

Composite theories are the algebraic equivalent of distributive laws. In this paper, we delve into the details of this correspondence and concretely show how to construct a composite theory from a distributive law and vice versa. Using term rewriting methods, we also describe when a minimal set of equations axiomatises the composite theory.

Vlad Smolin

Answering a question posed by Vladimir Tkachuk, we prove that every $T_1$ connected first-countable space is a continuous open image of a connected metrizable space.

Yashar Deldjoo, Zhankui He, Julian McAuley, Anton Korikov

Traditional recommender systems (RS) typically use user-item rating histories as their main data source. However, deep generative models now have the capability to model and sample from complex data distributions, including user-item interactions, text, images, and videos, enabling novel recommendation tasks. This comprehensive, multidisciplinary survey conn

Fan Bai, Yuxin Du, Tiejun Huang, Max Q. -H. Meng

Medical image analysis is essential to clinical diagnosis and treatment, which is increasingly supported by multi-modal large language models (MLLMs). However, previous research has primarily focused on 2D medical images, leaving 3D images under-explored, despite their richer spatial information. This paper aims to advance 3D medical image analysis with MLLM

Sai Swagat Mishra, Aaqid Bhat, P. K. Sahoo

The origin of matter domination in the Universe is one of the most exciting open puzzles in particle physics and cosmology. Despite many theoretical developments, the actual reason behind baryon-antibaryon asymmetry is still unknown. Our aim here is to examine this phenomenon in the framework of modified gravity theories, which have impressively elucidated t

Ichio Kikuchi, Akihito Kikuchi

This article shows a proof of concept regarding the feasibility of ab initio molecular simulation, wherein the wavefunctions and the positions of nuclei are simultaneously determined by the quantum algorithm, as is realized by the so-called Car-Parrinello method by classical computing. The approach used in this article is of a hybrid style, which shall be re

PoTsang B. Huang, Muhammad Rizwan, Mehboob Ali

The uncontrolled and unstructured growth of brain cells is known as brain tumor, which has one of the highest mortality rates among diseases from all types of cancers. Due to limited diagnostic and treatment capabilities, they pose significant challenges, especially in third-world countries. Early diagnosis plays a vital role in effectively managing brain tu

Aditi Nethwewala, Kitae Eom, Muqing Yu, Ranjani Ramachandran

The LaAlO$_3$/SrTiO$_3$ interface hosts a plethora of gate-tunable electronic phases. Gating of LaAlO$_3$/SrTiO$_3$ interfaces are usually assumed to occur electrostatically. However, increasing evidence suggests that non-local interactions can influence and, in some cases, dominate the coupling between applied gate voltages and electronic properties. Here,

Nazlı Doğan

This paper is about the operators defined between K\"othe spaces whose associated matrix is a Hankel matrix. After demonstrating how these operators are defined, the conditions for continuity and compactness of these operators are constructed. It is shown that the backward and forward shift operators are mean ergodic and Ces\`aro bounded by establishing a re

Lirui Zhao, Yue Yang, Kaipeng Zhang, Wenqi Shao

Text-to-image (T2I) generative models have attracted significant attention and found extensive applications within and beyond academic research. For example, the Civitai community, a platform for T2I innovation, currently hosts an impressive array of 74,492 distinct models. However, this diversity presents a formidable challenge in selecting the most appropr

Yuki Hou, Haruki Tamoto, Homei Miyashita

In this study, we propose a novel human-like memory architecture designed for enhancing the cognitive abilities of large language model based dialogue agents. Our proposed architecture enables agents to autonomously recall memories necessary for response generation, effectively addressing a limitation in the temporal cognition of LLMs. We adopt the human mem

Yue Zhao, Yuxuan Li, Chenang Liu, Yinan Wang

Machine learning (ML) methods are widely used in industrial applications, which usually require a large amount of training data. However, data collection needs extensive time costs and investments in the manufacturing system, and data scarcity commonly exists. Therefore, data-sharing is widely enabled among multiple machines with similar functionality to aug

Seonjeong Hwang, Yunsu Kim, Gary Geunbae Lee

In response to the increasing use of interactive artificial intelligence, the demand for the capacity to handle complex questions has increased. Multi-hop question generation aims to generate complex questions that requires multi-step reasoning over several documents. Previous studies have predominantly utilized end-to-end models, wherein questions are decod

Xingxuan Li, Xuan-Phi Nguyen, Shafiq Joty, Lidong Bing

Large language models (LLMs) have become the norm in natural language processing (NLP), excelling in few-shot in-context learning (ICL) with their remarkable abilities. Nonetheless, the success of ICL largely hinges on the choice of few-shot demonstration examples, making the selection process increasingly crucial. Existing methods have delved into optimizin

Xiang Li, Fan Bu, Ambuj Mehrish, Yingting Li

Neural Text-to-Speech (TTS) systems find broad applications in voice assistants, e-learning, and audiobook creation. The pursuit of modern models, like Diffusion Models (DMs), holds promise for achieving high-fidelity, real-time speech synthesis. Yet, the efficiency of multi-step sampling in Diffusion Models presents challenges. Efforts have been made to int

Xunhang Sun, Xiaoyu Cao, Bo Zeng, Qiaozhu Zhai

Hydrogen-electrical microgrids are increasingly assuming an important role on the pathway toward decarbonization of energy and transportation systems. This paper studies networked hydrogen-electrical microgrids planning (NHEMP), considering a critical but often-overlooked issue, i.e., the demand-inducing effect (DIE) associated with infrastructure developmen

Edwin R. van Dam, Jack H. Koolen, Yanzhen Xiong

An association scheme is called amorphic if every possible fusion of relations gives rise to a fusion scheme. We call a pair of relations fusing if fusing that pair gives rise to a fusion scheme. We define the fusing-relations graph on the set of relations, where a pair forms an edge if it fuses. We show that if the fusing-relations graph is connected but no

Yiqing Xie, Alex Xie, Divyanshu Sheth, Pengfei Liu

To adequately test modern code generation systems, evaluation benchmarks must execute and test the code generated by the system. However, these execution and testing requirements have largely limited benchmarks to settings where code is easily executable or has human-written tests. To facilitate evaluation of code generation systems across diverse scenarios,

Saied Alshahrani, Hesham Haroon, Ali Elfilali, Mariama Njie

Wikipedia articles (content pages) are commonly used corpora in Natural Language Processing (NLP) research, especially in low-resource languages other than English. Yet, a few research studies have studied the three Arabic Wikipedia editions, Arabic Wikipedia (AR), Egyptian Arabic Wikipedia (ARZ), and Moroccan Arabic Wikipedia (ARY), and documented issues in

Qiwen Qiu, Stephen Yue, Jun Song

Magnesium (Mg) alloys have emerged as promising materials due to their low density and high strength-to-weight ratio, offering a wide range of applications across multiple industries. Nevertheless, the inherent brittleness of Mg alloys poses a significant hurdle, necessitating innovative approaches to enhance their mechanical performance. Among the various s

Wenxiao Deng, Wenbin Li, Tianyu Ding, Lei Wang

Dataset distillation has emerged as a promising approach in deep learning, enabling efficient training with small synthetic datasets derived from larger real ones. Particularly, distribution matching-based distillation methods attract attention thanks to its effectiveness and low computational cost. However, these methods face two primary limitations: the di

Weibing Zhao

Cluster analysis plays a crucial role in database mining, and one of the most widely used algorithms in this field is DBSCAN. However, DBSCAN has several limitations, such as difficulty in handling high-dimensional large-scale data, sensitivity to input parameters, and lack of robustness in producing clustering results. This paper introduces an improved vers

Junuk Cha, Jihyeon Kim, Jae Shin Yoon, Seungryul Baek

This paper introduces the first text-guided work for generating the sequence of hand-object interaction in 3D. The main challenge arises from the lack of labeled data where existing ground-truth datasets are nowhere near generalizable in interaction type and object category, which inhibits the modeling of diverse 3D hand-object interaction with the correct p

Hang Xue, Pan Yan

Let $E/F$ be a quadratic extension of local nonarchimedean fields of characteristic zero and let $D$ be a quaternion algebra over $F$ containing $E$. In this paper, we study a relation between the existence of twisted linear models on $\mathrm{GL}_n(D)$ and the local root numbers.

Changnan Xiao, Bing Liu

Length generalization (LG) is a challenging problem in learning to reason. It refers to the phenomenon that when trained on reasoning problems of smaller lengths or sizes, the resulting model struggles with problems of larger sizes or lengths. Although LG has been studied by many researchers, the challenge remains. This paper proposes a theoretical study of

Sanghyeon Nam, Hyejin Lee, Youngki Kim, Kyoung hyun Kwak

This study proposes a novel climate control strategy for electric vehicles (EVs) by addressing door-opening interruptions, an overlooked aspect in EV thermal management. We create and validate an EV simulation model that incorporates door-opening scenarios. Three controllers are compared using the simulation model: (i) a hierarchical non-linear model predict

Nishith Ranjon Roy, Nailah Rawnaq, Tulin Kaman

Generating realistic electron microscopy (EM) images has been a challenging problem due to their complex global and local structures. Isola et al. proposed pix2pix, a conditional Generative Adversarial Network (GAN), for the general purpose of image-to-image translation; which fails to generate realistic EM images. We propose a new architecture for the discr

Weihao Zeng, Dayuan Fu, Keqing He, Yejie Wang

Language models pre-trained on general text have achieved impressive results in diverse fields. Yet, the distinct linguistic characteristics of task-oriented dialogues (TOD) compared to general text limit the practical utility of existing language models. Current task-oriented dialogue pre-training methods overlook the one-to-many property of conversations,

Diwei Shi, Fan Liu, Sisi Li, Li Chen

The K\"arger model and its derivatives have been widely used to incorporate transcytolemmal water exchange rate, an essential characteristic of living cells, into analyses of diffusion MRI (dMRI) signals from tissues. The K\"arger model consists of two homogeneous exchanging components coupled by an exchange rate constant and assumes measurements are made wi

Yu Rong, Huijie Hu, Min He, Wei Du

Ultra-diffuse galaxies, characterized by comparable effective radii to the Milky Way but possessing 100-1,000 times fewer stars, offer a unique opportunity to garner novel insights into the mechanisms governing galaxy formation. Nevertheless, the existing corpus of observational and simulation studies has not yet yielded a definitive constraint or comprehens

G. Fejos, T. Hatsuda

Renormalization group flows of the $SU(N_f)\times SU(N_f)$ symmetric Ginzburg-Landau potential are calculated for a general number of flavors, $N_f$. Our approach does not rely on the $\epsilon$ expansion, but uses the functional renormalization group, formulated directly in $d=3$ spatial dimensions, with the inclusion of all possible (perturbatively) releva