December 2025 arXiv papers — page 55

Kyogo Murai

We prove the global existence of weak solutions to quasilinear Keller--Segel systems with nonlinear mobility by minimizing movements (JKO scheme) in the product space of the weighted Wasserstein space and $L^2$ space. In particular, we newly show the global existence of weak solutions to the Keller--Segel system with the degenerate diffusion and the sub-line

Fulton Gonzalez, Adelaide Nebeker, Katie Hallett, Andew Sailstad

By definition, a wave on a homogeneous tree $\mathfrak X$ is a solution to the discrete wave equation on $\mathfrak{X}$; that is, a family $\{f_k\}_{k\in\mathbb Z}$ of complex-valued functions on $\mathfrak X$ satisfying the partial difference equation $\mu_1 f_k=(f_{k+1}+f_{k-1})/2$ for all $k$, where $\mu_1$ is the mean value operator on $\mathfrak X$ of r

Chenghao Li, Chaoning Zhang, Yi Lu, Shuxu Chen

With the development of large language models (LLMs), particularly with the introduction of the long reasoning chain technique, the reasoning ability of LLMs in complex problem-solving has been significantly enhanced. While acknowledging the power of long reasoning chains, we cannot help but wonder: Why do different reasoning chains perform differently in re

Pengxuan Yang, Ben Lu, Zhongpu Xia, Chao Han

Latent World Models enhance scene representation through temporal self-supervised learning, presenting a perception annotation-free paradigm for end-to-end autonomous driving. However, the reconstruction-oriented representation learning tangles perception with planning tasks, leading to suboptimal optimization for planning. To address this challenge, we prop

Hisatoshi Kodani, Yuta Nozaki

The Kontsevich invariant of links is independent of the choice of associator, whereas for tangles this is not the case in general. In this paper, we focus on $2$-component string links and investigate to what extent the Kontsevich invariant depends on the choice of associator. As an application, we show that the action of the unipotent part of the Grothendie

Junhao Xiao, Shun Feng, Zhiyu Wu, Jinghan Yu

Audio-Visual Speaker Detection (AVSD) hinges on modeling both individual temporal continuity and inter-personal social context. Existing coupled architectures struggle to reconcile these tasks in shared representation spaces due to conflicting inductive biases: temporal modeling favors low-frequency smoothness, while inter-personal interaction requires high-

Yen-Ju Chen, Sheng-Hsuan Huang, Thomas Dirmeier, Kaisa Laiho

Hong-Ou-Mandel (HOM) interferometry with entangled photons exhibits distinctive quantum features. By introducing frequency entanglement (discrete-color entangled states) into HOM interference, the characteristic HOM dip is modulated by sinusoidal fringes, which significantly enhance the sensitivity of HOM sensors. The frequency-entangled photon sources demon

Samet Uzun, Dayou Luo, Behçet Açıkmeşe, Aleksandr Y. Aravkin

We introduce prox-convex for minimizing $F(x)=g(x)+h(C(x))+s(R(x))$, where $g$ and $h$ are convex, $C$ and $s$ are smooth, and each component of $R$ is convex (possibly nonsmooth). Here $g$ captures general convex objectives and indicator functions for convex constraints, while the composite template simultaneously models convex penalties on smooth features

Benjamin Brück, Jeremy Miller, Kevin Ivan Piterman

We show that the common basis complex of a free group of rank $n$ has the homotopy type of a wedge of spheres of dimension $2n-3$. This establishes an $\mathrm{Aut}(F_n)$-analogue of the connectivity conjecture that Rognes originally stated for $\mathrm{GL}_n(R)$. To prove this, we provide several homotopy-equivalent models of the common basis complex, both

Yuhao Chen, Boxiang He, Junshan Luo, Shilian Wang

Specific emitter identification (SEI) distinguishes emitters by utilizing hardware-induced signal imperfections. However, conventional SEI techniques are primarily designed for single-emitter scenarios. This poses a fundamental limitation in distributed wireless networks, where simultaneous transmissions from multiple emitters result in overlapping signals t

Zihan Lin, Xiaohan Wang, Hexiong Yang, Jiajun Chai

While Reinforcement Learning (RL) shows promise in training tool-use Large Language Models (LLMs) using verifiable outcome rewards, existing methods largely overlook the potential of reasoning rewards based on chain-of-thought quality for better tool utilization. Furthermore, na\"ively combining reasoning and outcome rewards may yield suboptimal performance

Tzu-Yun Lee, Ding-Yong Hong, Jan-Jan Wu

This paper introduces Syntactic Attention Pruning (SAP), a novel method for effectively pruning attention heads in Transformer models. Unlike conventional approaches that rely solely on mathematical analysis of model weights and activations, SAP incorporates both the syntactic structure and attention patterns of sentences to guide the pruning process. By lev

Wentang Song, Jinqiang Li, Kele Huang, Junhui Lin

The versatility of Large Language Models (LLMs) in vertical domains has spurred the development of numerous specialized evaluation benchmarks. However, these benchmarks often suffer from significant semantic redundancy and impose high computational costs during evaluation. Existing compression methods, such as tinyBenchmarks depend critically on correctness

Haotian Deng, Mengxuan Liu, Chuan Zhang, Wei Huang

Online harassment, incitement to violence, racist behavior, and other harmful content on social media can damage social harmony and even break the law. Traditional blocklisting technologies can block malicious users, but this comes at the expense of identity privacy. The anonymous blocklisting has emerged as an effective mechanism to restrict the abuse of fr

Xinyu Li, Qian Tang, Guoxin Yin, Gang Zheng

Continuum robots (CRs), owing to their compact structure, inherent compliance, and flexible deformation, have been widely applied in various fields. By coordinating multiple CRs to form collaborative continuum robots (CCRs), task adaptability, workspace, flexibility, load capacity, and operational stability can be further improved, thus offering significant

Francesco Carzaniga, Michael Hersche, Kaspar Schindler, Abbas Rahimi

Objective: We develop a channel-adaptive (CA) architecture that seamlessly processes multi-variate time-series with an arbitrary number of channels, and in particular intracranial electroencephalography (iEEG) recordings. Methods: Our CA architecture first processes the iEEG signal using state-of-the-art models applied to each single channel independently. T

Pedro Bargueño

One evening, a father tells his three daughters, Luc\'ia, In\'es, and Ana, a bedtime story unlike any other. It is a tale of four silent architects ($c$, $\hbar$, $G$, and $\Lambda$) whose presence or absence shapes the very fabric of reality. By imagining worlds where each constant is removed, they explore realms from the quantum gravity of the Planck scale

Mahir Labib Dihan, Sadif Ahmed, Md Nafiu Rahman

Bangla is a low-resource language for code generation, lacking large-scale annotated datasets and tools to transform natural language specifications into executable programs. This makes Bangla-to-code generation a challenging task requiring innovative solutions. To address this, we introduce BanglaForge, a novel framework for generating code from Bangla func

Riccardo Civiero, Elena Campagna, Afonso Cerdeira Oliveira, Marvin Hartwig Zoellner

The strain-relaxation mechanism of a set of Si$_{0.6}$Ge$_{0.4}$ linearly graded buffers (LGBs), grown following different temperature profiles, has been investigated by means of defect-etching and variable-temperature high-resolution X-ray diffraction (VT-HRXRD). Defect-etching experiments demonstrate that a sharp increase of threading dislocation density (

Djunes Janssens, Antonija Utrobicic, Marinko Kovacic, Marta Lisowska

The PICOSEC Micromegas detector is a Micro-Pattern Gaseous Detector concept developed to achieve tens of picosecond timing resolution for charged particle detection by combining a Cherenkov radiator with a two-stage Micromegas amplification structure. To improve operational robustness, a resistive anode has been implemented using a DLC layer deposited on a K

Junfeng Cheng, Xiao-Song Yang

In this paper, we revisit the well-known perturbed Duffing system and investigate its chaotic dynamics by means of numerical Runge--Kutta method based on topological horseshoe theory. Precisely, we investigate chaos through the topological horseshoes associated with the first, second, and third return maps, obtained by varying the amplitude of an external fo

Xikai Shan, Huan Yang, Shude Mao

The unusual properties of GW231123, including component masses within the pair-instability mass gap ($137^{+22}_{-17}\mathrm{M}_\odot$ and $103^{+20}_{-52}\mathrm{M}_\odot$ at 90\% credible intervals) and extremely large spins near the Kerr limit, have challenged standard formation scenarios. While gravitational lensing has been proposed as an explanation, c

Jun Jie Miao, Tianrui Wang

We study the generalized q-dimensions of measures supported on non-autonomous conformal attractors, which are the generalizations of Moran sets and the attractors of iterated function systems. We first prove that the critical values of generalized upper and lower pressure functions are always the upper bounds for the upper and lower generalized q-dimensions

Amar Lakel

This paper proposes an epistemological shift in the analysis of large generative models, replacing the category ''Large Language Models'' (LLM) with that of ''Large Discourse Models'' (LDM), and then with that of Artificial Discursive Agent (ADA). The theoretical framework is based on an ontological triad distinguishing three regulatory instances: the appreh

Chaoyang Hu, Mingyong Jing, Zongkai Liu, Shaoxin Yuan

Non-invasive microwave field imaging--accurately mapping field distributions without perturbing them--is essential in areas such as aerospace engineering, biomedical imaging and integrated-circuit diagnostics. Conventional metal probes, however, inevitably perturb reactive near fields: they act as strong scatterers that drive induced currents and secondary r

Hengyi Feng, Zeang Sheng, Meiyi Qiang, Yang Li

Despite the remarkable success of multimodal large language models (MLLMs) in generative tasks, we observe that they exhibit a counterintuitive deficiency in the zero-shot multimodal retrieval task. In this work, we investigate the underlying mechanisms that hinder MLLMs from being effective retrievers. With the help of sparse autoencoders (SAEs), we decompo

Haoyu Jiang, Boan Qu, Junjie Zhu, Fanjie Zeng

The rapid growth of artificial intelligence is exponentially escalating computational demand, inflating data center energy use and carbon emissions, and spurring rapid deployment of green data centers to relieve resource and environmental stress. Achieving sub-minute orchestration of renewables, storage, and loads, while minimizing PUE and lifecycle carbon i

Daniel Erman, Andrew Hanlon, Gaku Liu, Hailun Zheng

We show that a strong version of the geometric Merkurjev-Panin conjecture holds for the Cox category of a projective toric variety. That is, we prove that the full strong exceptional collection of Bondal-Thomsen line bundles is invariant under the group of lattice automorphisms that permute the rays of the toric variety's fan. Our result is meant to further

Tao Li, Zhenbao Yu, Banglei Guan, Jianli Han

This work presents two novel solvers for estimating the relative poses among views with known vertical directions. The vertical directions of camera views can be easily obtained using inertial measurement units (IMUs) which have been widely used in autonomous vehicles, mobile phones, and unmanned aerial vehicles (UAVs). Given the known vertical directions, o

Sai Zhao, Fanjin Kong, Dong Tang, Tuo Wu

Low-altitude economy (LAE) has become a key driving force for smart cities and economic growth. To address spectral efficiency and communication security challenges in LAE, this paper investigates secure energy efficiency (SEE) maximization using intelligent sky mirrors, UAV-mounted multifunctional reconfigurable intelligent surfaces (MF-RIS) assisting nonor

Tiantian Li, Xinjie Zhang, Xingtong Ge, Tongda Xu

Implicit neural representations (INRs) have achieved remarkable success in image representation and compression, but they require substantial training time and memory. Meanwhile, recent 2D Gaussian Splatting (GS) methods (\textit{e.g.}, GaussianImage) offer promising alternatives through efficient primitive-based rendering. However, these methods require exc

Zhe Yang, Xiaoshuang Sheng, Zhengnan Zhang, Jidong Wu

Identifying user intent from mobile UI operation trajectories is critical for advancing UI understanding and enabling task automation agents. While Multimodal Large Language Models (MLLMs) excel at video understanding tasks, their real-time mobile deployment is constrained by heavy computational costs and inefficient redundant frame processing. To address th

Soto Hisakawa, Shizuo Kaji, Ryo Kawai

Topology and geometry are deeply intertwined in the study of surfaces, though their interaction manifests differently in smooth and discrete settings. In the smooth category, a classical result asserts that any closed smooth surface embedded in $\mathbb{R}^3$ with constant Gaussian curvature must be a sphere, reflecting the strong rigidity of differential ge

Haishan Ye

Zeroth-order (ZO) optimization with ordinal feedback has emerged as a fundamental problem in modern machine learning systems, particularly in human-in-the-loop settings such as reinforcement learning from human feedback, preference learning, and evolutionary strategies. While rank-based ZO algorithms enjoy strong empirical success and robustness properties,

Jiaqi Zhu, Zhongyuan Zhao, Xiao Li, Ruihao Du

Incorporating over-the-air computations (OAC) into the model training process of federated learning (FL) is an effective approach to alleviating the communication bottleneck in FL systems. Under OAC-FL, every client modulates its intermediate parameters, such as gradient, onto the same set of orthogonal waveforms and simultaneously transmits the radio signal

Hironobu Nakata, Shunsuke Adachi, Kyohei Yamada, Michael Randall

Improved measurements of $B$-modes in the cosmic microwave background can be obtained through accurate calibration of the orientation of detector antennas as projected onto the sky. Miscalibration of the detector polarization angle leads to a leakage of $E$-modes into $B$-modes, which can bias the detection of the latter. To achieve a $\sigma(r)$ of 0.003, t

Ryota Hatami, Nozomu Tominaga, Takashi Yoshida, Hideyuki Umeda

We present the results of simulations of nucleosynthesis in a core-collapse supernova (CCSN) including the neutrino process. Using the Si layer of $13M_\odot$ zero-metal progenitor as the initial composition, we calculate the nucleosynthesis by adopting the temperature, density, neutrino flux, and duration of nucleosynthesis as arbitrary parameters and compa

Alireza Moayedikia, Sara Fin, Uffe Kock Wiil

Disease modifying therapies for Alzheimer's disease demand precise timing decisions, yet current predictive models require longitudinal observations and provide no uncertainty quantification, rendering them impractical at the critical first visit when treatment decisions must be made. We developed PROGRESS (PRognostic Generalization from REsting Static Signa

Anatolii A. Puhalskii

This paper proves a large deviation principle (LDP) for the stationary distribution of queue lengths in a subcritical generalised Jackson network assuming a Cramer condition on the interarrival and service times. The deviation function is given by the quasipotential.

Kathelijne Coussement, Gert de Cooman, Keano De Vos

We discuss conditionalisation for Accept-Desirability models in an abstract decision-making framework, where uncertain rewards live in a general linear space, and events are special projection operators on that linear space. This abstract setting allows us to unify classical and quantum probabilities, and extend them to an imprecise probabilities context. We

Weiyi Lyu, Xinming Fang, Jun Wang, Jun Shi

Magnetic resonance imaging (MRI) is a cornerstone of modern clinical diagnosis, offering unparalleled soft-tissue contrast without ionizing radiation. However, prolonged scan times remain a major barrier to patient throughput and comfort. Existing accelerated MRI techniques often struggle with two key challenges: (1) failure to effectively utilize inherent K

Mengqi Guo, Ji Zhou, Haide Wang, Changyuan Yu

To meet the high-speed, low-latency, and low-complexity demand for optical interconnects, simplified maximum likelihood sequence estimation (MLSE) is proposed in this paper. Simplified MLSE combines computational simplification and reduced state in MLSE. MLSE with a parallel sliding block architecture reduces latency from linear order to logarithmic order. C

Peiqing Lu, Yuan Zhang, Haoyun Zhang, Jiasen Zheng

Bilingual mathematical problem solving needs a clear link between language reasoning and symbolic calculation. Large language models often handle language well but are weak in accurate computation. This paper presents HERALD (Hybrid Ensemble Reasoning with Adaptive Learning and Distillation), a framework that joins reasoning and calculation using NuminaMath-

Ziyan Zhang, Chao Wang, Zhuo Chen, Lei Chen

Reasoning over knowledge graphs (KGs) with first-order logic (FOL) queries is challenging due to the inherent incompleteness of real-world KGs and the compositional complexity of logical query structures. Most existing methods rely on embedding entities and relations into continuous geometric spaces and answer queries via differentiable set operations. While

Ariel Lubonja, Pedro R. A. S. Bassi, Wenxuan Li, Hualin Qiao

Open challenges have become the de facto standard for comparative ranking of medical AI methods. Despite their importance, medical AI leaderboards exhibit three persistent limitations: (1) score gaps are rarely tested for statistical significance, so rank stability is unknown; (2) single averaged metrics are applied to every organ, hiding clinically importan

Fan Yu, Tao Wang, You Wu, Lin Zhu

Large speech generation models are evolving from single-speaker, short sentence synthesis to multi-speaker, long conversation geneartion. Current long-form speech generation models are predominately constrained to dyadic, turn-based interactions. To address this, we introduce JoyVoice, a novel anthropomorphic foundation model designed for flexible, boundary-

Marie Jose Perez Peralta, Daniela Flores Casillas, Benjamin Wilson, Cristian Aviles Medina

This work presents the design and implementation of a wireless, wearable system that combines surface electromyography (sEMG) and inertial measurement units (IMUs) to analyze a single lower-limb functional task: the free bodyweight squat in a healthy adult. The system records bipolar EMG from one agonist and one antagonist muscle of the dominant leg (vastus

Khanh Nguyen, Dasith de Silva Edirimuni, Ghulam Mubashar Hassan, Ajmal Mian

Locating and retrieving objects from scene-level point clouds is a challenging problem with broad applications in robotics and augmented reality. This task is commonly formulated as open-vocabulary 3D instance segmentation. Although recent methods demonstrate strong performance, they depend heavily on SAM and CLIP to generate and classify 3D instance masks f

Haiming Yuan, Xian-Hui Ge, Keun-Young Kim

We study the pole-skipping structure of incoming waves near the cosmic horizon $r=r_c$ in de Sitter (dS) spacetime. We find that the scalar field with spin-0, the Dirac field with spin-1/2, the Maxwell field with spin-1, the Rarita-Schwinger field with spin-3/2, and the gravitational field with spin-2 exhibit the same frequencies $\omega_\star$ of pole-skipp

Byung Gyu Chae

Reentrant computation-recursive self-coupling in which a network continuously reinjects and reinterprets its own internal state-plays a central role in biological cognition but remains poorly characterized in neural network architectures. We introduce a minimal continuous-time formulation of a homeostatically regulated reentrant network (FHRN) and show that

Chun-Qiu Zhao, Xu Cao, Jian-Ping Dai

In the center-of-mass frame, the spin density matrix for octet baryon-antibaryon pairs produced in polarized electron-positron annihilation is unambiguously determined within the one-photon-exchange approximation. The formalism simultaneously incorporates parity ($P$) and combined parity-charge conjugation ($CP$) violation arising from the coupling of the in

Takashi Ushio, Kazuhiro Onishi, Hideyoshi Yanagisawa

Emotional responses during advertising video viewing are recognized as essential for understanding media effects because they have influenced attention, memory, and purchase intention. To establish a methodological basis for explainable emotion estimation without relying on external information such as physiological signals or subjective ratings, we have qua

Mark Burgess

The semantics and dynamics of `attention' are closely related to promise theoretic notions developed for autonomous agents and can thus easily be written down in promise framework. In this way one may establish a bridge between vectorized Machine Learning and Knowledge Graph representations without relying on language models implicitly. Our expectations for

Pengyu Chen, Tao Ouyang, Ke Luo, Weijie Hong

Autonomous navigation for Unmanned Aerial Vehicles faces key challenges from limited onboard computational resources, which restrict deployed deep neural networks to shallow architectures incapable of handling complex environments. Offloading tasks to remote edge servers introduces high latency, creating an inherent trade-off in system design. To address the

Jiawei Hou, Peng Yang, Xiangxiang Dai, Mingliu Liu

Bird's-Eye-View (BEV) is critical to connected and automated vehicles (CAVs) as it can provide unified and precise representation of vehicular surroundings. However, quality of the raw sensing data may degrade in occluded or distant regions, undermining the fidelity of constructed BEV map. In this paper, we propose BEVCooper, a novel collaborative perception

Yanzhi Zhang, Yitong Duan, Zhaoxi Zhang, Jiyan He

Test-time scaling has emerged as a promising direction for enhancing the reasoning capabilities of Large Language Models in last few years. In this work, we propose Population-Evolve, a training-free method inspired by Genetic Algorithms to optimize LLM reasoning. Our approach maintains a dynamic population of candidate solutions for each problem via paralle

Søren Eilers, Rune Johansen, Rasmus Veber Rasmussen, Carsten Thomassen

We initiate the study of chromatic numbers for contact graphs of configurations of integer-sized cuboids in three dimensions, all of which are mutually congruent. Disallowing rotations, we show a global upper bound of 8 for the chromatic numbers, which implies that there is a global upper bound of 48 when the cuboids may be rotated freely. Specializing furth

Yuming Qin, Hongli Wang

This paper delves into the long-time dynamics of a non-autonomous viscoelastic Kirchhoff plate equation with memory effects, described by $$ u_{t t}-\Delta u_{t t}+a_\epsilon(t) u_t+\alpha \Delta^2 u-\int_0^{\infty} \mu(s) \Delta^2 u(t-s) \mathrm{d} s-\Delta u_t+f(u)=g(x,t), $$ in bounded domain $\Omega \subset \mathbb{R}^N$ with smooth boundary and nonlinea

Michał Marczenko

We discuss a constraint on the speed of sound, $c_s^2$, derived from relativistic kinetic theory and show how it can be expressed in terms of the average sound speed, $\langle c_s^2 \rangle$. This reformulation highlights the interplay between instantaneous and integrated stiffness of the equation of state and allows the kinetic-theory bound to be visualized

Jia-Rui Xu, Zhan Xiong, Kai Deng, Hai-Xiao Wang

Antichiral surface states, characterized by unidirectional propagation on parallel surfaces, offer unique potential for controlling classical waves. However, their realization typically relies on complex implementations of the two-dimensional modified Haldane model, limiting practical applications. Here, we propose a simplified scheme to realize such states

Aniruddha Chakraborty, Suvodip Mukherjee

The recently discovered gravitational wave event, GW231123, is the most massive binary black hole merger detected to date. The inferred source masses of the event fall within the pair-instability supernova mass gap, where black holes formed directly from stellar progenitors are expected to be rare, making alternative formation scenarios for such massive blac

Yiming Gao, Yansong Feng, Honggang Hu, Yanbin Pan

We propose a deterministic algorithm based on Coppersmith's method that employs a rank-3 lattice to address factoring-related problems. An interesting aspect of our approach is that we utilize the second vector in the LLL-reduced basis to avoid trivial collisions in the Baby-step Giant-step method, rather than the shortest vector as is commonly used in the l

Zhenguo Gao, Hui Li, Yiqin Chen, Qingyu Gao

The high mobility and flexible deployment capability of UAVs make them an impressive option for charging nodes in Wireless Rechargeable Sensor Networks (WRSNs) using Directional Wireless Power Transfer (WPT) technology. However, existing studies largely focus on 2D-WRSNs, lacking designs catering to real 3D-WRSNs. The spatial distribution characteristics of

Joanne Hughes, Andrea Kunder, Kevin Covey, Kathryn Devine

We present spectroscopic evidence for tidal debris associated with the bulge globular cluster NGC 6569, based on medium-resolution (R ~ 11,000) Anglo-Australian Telescope spectra of 303 stars. Targets were selected using Blanco DECam Bulge Survey (BDBS) photometry and Gaia DR3 astrometry, spanning 7-30 arcmin (~1-5 rt, where rt is the King-model tidal radius

ATLAS Collaboration

Inclusive dijet cross-sections have been measured in proton-proton collisions at a centre-of-mass energy of 13 TeV using data with an integrated luminosity of 140 fb$^{-1}$, recorded by the ATLAS detector at the Large Hadron Collider during 2015-2018. Jets are identified using the anti-$k_{t}$ algorithm with a radius parameter of $R = 0.4$. The inclusive dij

Andrii Torchylo, Hunter Swan, Lucas Tellez, Jason M. Hogan

Optimal transport methods have recently established state of the art accuracy and efficiency for holographic laser beam shaping. However, use of such methods is hindered by severe $\mathcal{O}(N^2)$ memory and $\mathcal{O}(N^2)$ time requirements for large scale input or output images with $N$ total pixels. Here we leverage the dual formulation of the optima

Jinjin Liang, Yixi Liao, Erxiao Wang

By computing all cyclotomic points on some algebraic varieties, we get an independent and efficient way to find all rational $a^3b$-monotiles for the sphere, thereby completing the classification of edge-to-edge monohedral quadrilateral tilings. Both of the previous classifications \cite{lw2} and \cite{cl} depended on many old works of different authors whil

Ruiqi Ma, Yu Yan, Chunhong Zhang, Minghao Yin

Large Vision-Language Models (LVLMs) bridge the gap between visual and linguistic modalities, demonstrating strong potential across a variety of domains. However, despite significant progress, LVLMs still suffer from severe hallucination issues in object recognition tasks. These models often fail to accurately identify certain objects, leading to text genera

Siddharth Tandon

Large language models (LLMs) excel at diverse tasks, but their deployment on resource-constrained devices remains challenging. Existing methods like quantization, pruning, and distillation can reduce memory footprint but often demand extensive experimentation and careful infrastructure design. Leveraging existing techniques for extracting high-level concepts

Ashoke Sen

Are duality transformations symmetries of string theory? For AdS space-time the answer is no for generic asymptotic values of the moduli, since the duality symmetry is broken explicitly in the dual conformal field theory. In contrast, in string theory in flat space-time, monodromies around codimension two exotic branes show that duality transformations are s

George Vershinin, Asaf Cohen, Omer Gurewitz

We introduce Cost-Aware (CA) Sequential Hypothesis Testing (CASHT), in which an active decision-maker selects sensing actions with differing, random costs to identify the true hypothesis under an average-error constraint $δ$ while minimizing the expected total cost rather than the number of samples. For fixed costs, we prove that the optimal expected total c

Ami Mi Shirai, Kota Aikyo, Yuta Murotani, Tomohiro Fujimoto

We investigated the anomalous Hall conductivity induced in silicon by circularly polarized light at room temperature using near-infrared (NIR) pump-terahertz (THz) probe spectroscopy. The time-resolved detection scheme eliminates the large nonlinear current generated by the field-induced circular photogalvanic effect, allowing exclusive observation of a long

Nicole Fontana, Francesca Ieva, Luisa Zuccolo, Emanuele Di Angelantonio

Mendelian Randomization is a widely used instrumental variable method for assessing causal effects of lifelong exposures on health outcomes. Many exposures, however, have causal effects that vary across the life course and often influence outcomes jointly with other exposures or indirectly through mediating pathways. Existing approaches to multivariable Mend

Victor H. de la Pena, Heyuan Yao, Demissie Alemayehu

Both complete decoupling and tangent decoupling are classical tools aiming to compare two random processes where one has a weaker dependence structure. We give a new proof for the complete decoupling inequality, which provides a lower bound for the sum of dependent square-integrable nonnegative random variables $\sum\limits^n_{i=1} d_i$ \[ \frac{1}{2} \mathb

Letizia Fede, Debobrata Rajak, Chris Sparling, David Ayuso

Chiroptical effects using circularly polarized light produce signals that change sign when switching either molecular handedness (enantiosensitivity) or the light helicity (circular dichroism). Here, we break this enantiosensitive-and-dichroic paradigm by measuring a new type of chiroptical signal which is enantiosensitive but not dichroic. We photoionize ch

Chi Liu

Collaborative fraud, where multiple fraudulent accounts coordinate to exploit online payment systems, poses significant challenges due to the formation of complex network structures. Traditional detection methods that rely solely on high-confidence identity links suffer from limited coverage, while approaches using all available linkages often result in frag

R. Buompane, F. Cavanna, C. Curceanu, A. D'Onofrio

The Istituto Nazionale di Fisica Nucleare-Laboratori Nazionali del Gran Sasso (LNGS) is one of the largest underground physics laboratory, a very peculiar environment suited for experiments in Astroparticle Physics, Nuclear Physics and Fundamental Symmetries. The newly established Bellotti Ion Beam facility represents a major advance in the possibilities of

Jihui Guo, Zongmin Zhang, Zhen Sun, Yuhao Yang

Deep learning advances have enabled accurate six-degree-of-freedom (6DoF) object pose estimation, widely used in robotics, AR/VR, and autonomous systems. However, backdoor attacks pose significant security risks. While most research focuses on 2D vision, 6DoF pose estimation remains largely unexplored. Unlike traditional backdoors that only change classes, 6

Guy Schacht, Ziyad Sheebaelhamd, Riccardo De Santi, Mojmír Mutný

Preference learning from human feedback has the ability to align generative models with the needs of end-users. Human feedback is costly and time-consuming to obtain, which creates demand for data-efficient query selection methods. This work presents a novel approach that leverages optimal experimental design to ask humans the most informative preference que

Erfan Salahinejad, Avaneesh Muralidharan, Forough Azam Sayahpour, Maryam Kianpour

Addressing a critical challenge in current tissue-engineering practices, this study aims to enhance vascularization in 3D porous scaffolds by incorporating bioceramics laden with pro-angiogenic ions. Specifically, freeze-dried gelatin-based scaffolds were infused with sol-gel-derived powders of Cu-doped akermanite (Ca2MgSi2O7) and bredigite (Ca7MgSi4O16) at

Chengyong Jiang, Jiajia Guo, Yuqing Hua, Chao-Kai Wen

The Channel Quality Indicator (CQI) is a fundamental component of channel state information (CSI) that enables adaptive modulation and coding by selecting the optimal modulation and coding scheme to meet a target block error rate. While AI-enabled CSI feedback has achieved significant advances, especially in precoding matrix index feedback, AI-based CQI feed

Zhihao Chen, Pengxu Ran, Ming Dong Dong, Jiexiong Sun

Realizing non-volatile control of superconductivity is a key step toward integrating memory and quantum functionality in future information technologies. KTaO$_3$-based heterostructures uniquely host interfacial two-dimensional superconductivity and quantum paraelectric lattice background. The coupling between these two degrees of freedom potentially provide

Amir Babak Aazami

We use the totally trace-free component of Thorpe's middle curvature operator $R_{2n}\colonΛ^{2n}\to Λ^{2n}$ to define higher self-duality on oriented Riemannian $4n$-manifolds. We show that higher self-dual metrics are absolute minimizers of a natural conformal energy, whose Bach tensor is symmetric, trace-free, and divergence-free, resolving a question

Hwanhee Jung, Seunggwan Lee, Jeongyoon Yoon, SeungHyeon Kim

Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control. Existing approaches often require manually specified intermediate waypoints and place all optimization objectives on a single network, which increases complexity, reduces flexibility, and leads to errors such as

Utae Jeong, Sumin In, Hyunju Ryu, Jaewan Choi

Image watermarking supports authenticity and provenance, yet many schemes are still easy to bypass with various distortions and powerful generative edits. Deep learning-based watermarking has improved robustness to diffusion-based image editing, but a gap remains when a watermarked image is converted to video by image-to-video (I2V), in which per-frame water

Md Minhazul Islam Munna, Al Amin, Xin Wang, Hongbin Ma

Augmented Reality (AR) technology holds immense potential to transform the lives of blind and disabled individuals by offering enhanced interaction with their surroundings and providing real-time, accessible information. Globally, AR applications are being developed with features such as audio descriptions of environments, object recognition, and navigationa

Jihua Yang

Cima, Ma\~{n}osas and Villadelprat (J. Differ. Equations, 157, 373--413, 1999) proved that a cubic Hamiltonian system possesses an isochronous center at the origin if and only if its Hamiltonian function can be expressed as \begin{eqnarray*}H_1(x,y)=k_1^2x^2+(k_2y+k_3x+k_4x^2)^2, \end{eqnarray*} where $k_1,k_2,k_3,k_4\in\mathbb{R}$, $k_1k_2\neq0$. This paper

Eric Marberg

Kirillov and Naruse have constructed double Grothendieck polynomials to represent the equivariant K-theory classes of Schubert varieties in the complete flag manifolds of types B, C, and D. We derive a recursive formula for these polynomials, extending certain K-theoretic transition equations known in type A to all classical types. As an application, we obta

Zhuoyuan Qu

Russell's paradox is the most easily understandable way to illustrate the inconsistency of naïve set theory. This note proposes a direct encoding of Russell's paradox with type-in-type universe, sigma types, and either extensional identity or intensional identity with the uniqueness of identity proofs (UIP).

Tara Abrishami, Paul Knappe

A graph is locally chordal if each of its small-radius balls is chordal. In an earlier work [AKK25], the authors and Kobler proved that locally chordal graphs can be characterized by having chordal local covers, by forbidding short cycles and wheels as induced subgraphs, and by the property that each of their minimal local separators is a clique. In this pap

Chao Yang, Yingkai Sun, Peng Ye, Xin Chen

Learning a general motion tracking policy from human motions shows great potential for versatile humanoid whole-body control. Conventional approaches are not only inefficient in data utilization and training processes but also exhibit limited performance when tracking highly dynamic motions. To address these challenges, we propose EGM, a framework that enabl

Zahra Haghani, Tiberiu Harko

If dark matter is composed of massive bosons, a Bose-Einstein Condensation process must have occurred during the cosmological evolution. Therefore, galactic dark matter may be in a form of a self-gravitating condensate, in the presence of self-interactions. We consider the possibility that the self-interacting potential of the condensate dark matter is of th

Sarunas Verner

We study the minimal gravitational portal for a massive spin-2 dark matter candidate $X_{\mu\nu}$ produced during perturbative reheating. The dark sector couples to the visible sector only via gravity, and we analyze two unavoidable channels: (i) inflaton condensate annihilation, $\phi+\phi \to X+X$, and (ii) thermal scatterings, ${\rm SM}+{\rm SM}\to X+X$,

Tara Abrishami, Sandra Albrechtsen, Nathan Bowler, Paul Knappe

Circular-arc graphs are graphs that can be represented as intersection graphs of subpaths of a cycle. Interval graphs are graphs that can be represented as intersection graphs of subpaths of a path. Since cycles are locally paths, every circular-arc graph is locally interval. In this paper, we prove that the converse holds as well: every locally interval gra

Zeyi Liao, Guanqun Song, Ting Zhu

The technological transition of MacBook charging solutions from MagSafe to USB-C, followed by a return to MagSafe 3, encapsulates the dynamic interplay between technological advancement, environmental considerations, and economic factors. This study delves into the broad implications of these charging technology shifts, particularly focusing on the environme

Li Yan, Derek Teaney

We investigate hydrodynamic contributions to short-range two-particle correlations in relativistic heavy-ion collisions using the Boltzmann-Langevin equation. We derive and solve the transport equation for equal-time two-point correlations, obtaining both local and non-local contributions that scale with transport coefficients. The non-local correlations eme

Liping Sun, Yucheng Guo, Siliang Lu, Zhenzhen Li

With the press of global climate change, extreme weather and sudden weather changes are becoming increasingly common. To maintain a comfortable indoor environment and minimize the contribution of the building to climate change as much as possible, higher requirements are placed on the operation and control of HVAC systems, e.g., more energy-efficient and fle

Md Minhazul Islam Munna, Md Mahbubur Rahman, Jaroslav Frnda, Muhammad Shahid Anwar

The proliferation of IoT devices and their reliance on Wi-Fi networks have introduced significant security vulnerabilities, particularly the KRACK and Kr00k attacks, which exploit weaknesses in WPA2 encryption to intercept and manipulate sensitive data. Traditional IDS using classifiers face challenges such as model overfitting, incomplete feature extraction

Xiaoyang Li, Mingming Lu, Ruiqi Wang, Hao Li

Few-shot action recognition aims to enable models to quickly learn new action categories from limited labeled samples, addressing the challenge of data scarcity in real-world applications. Current research primarily addresses three core challenges: (1) temporal modeling, where models are prone to interference from irrelevant static background information and

Michael R. Schwob, Nicholas M. Calzada, Justin J. Van Ee, Diana Gamba

The field of landscape genomics aims to infer how landscape features affect gene flow across space. Most landscape genomic frameworks assume the isolation-by-distance and isolation-by-resistance hypotheses, which propose that genetic dissimilarity increases as a function of distance and as a function of cumulative landscape resistance, respectively. While th