arXiv preprints from January 1, 2026 through September 22, 2026 — 01:48:46 EST
Handwritten word retrieval is vital for digital archives but remains challenging due to large handwriting variability and cross-lingual semantic gaps. While large vision-language models offer potential solutions, their prohibitive computational costs hinder practical edge deployment. To address this, we propose a lightweight...
We present new invariants, APN-extendibility criterion and a backtracking approach to identify several numerical facts supporting the conjecture that the set of 6-bit \APN functions is limited to 14 CCZ-classes.
We introduce the rank-nullity ring of a matroid $M$, which is a subring of the Chow ring of the permutahedral toric variety. This subring contains the tautological Chern classes of $M$, a fact we deduce from a highly symmetric formula for these classes. When the matroid $M$ is a uniform matroid, the rank-nullity ring coincides with...
The rate of coherence loss is lower for a qubit under the Rabi drive than a freely evolving qubit $T_{2}^{\rm{Rabi}}>T_{2}^*$. Building on this principle, concatenated continuous driving (CCD) keeps the qubit under continuous drive to suppress noise and manipulate dressed states by either phase or amplitude modulation. In this...
This study investigates the application of modern control theory to improve the precision of spacecraft orbit maneuvers in low Earth orbit under the influence of solar radiation pressure. A full order observer based feedback control framework is developed to estimate system states and compensate for external disturbances during the...
We propose unsupervised multi-scenario (UMS) person re-identification (ReID) as a new task that expands ReID across diverse scenarios (cross-resolution, clothing change, etc.) within a single coherent framework. To tackle UMS-ReID, we introduce image-text knowledge modeling (ITKM) -- a three-stage framework that effectively exploits...
Hidden variable graphical models can sometimes imply constraints on the observable distribution that are more complex than simple conditional independence relations. These observable constraints can falsify assumptions of the model that would otherwise be untestable due to the unobserved variables and can be used to constrain...
In this article, we study the ergodic problem associated to viscous Hamilton-Jacobi equation where the diffusion is governed by the censored fractional Laplacian, a nonlocal elliptic operator restricted to a bounded domain $Ω\subset \mathbb{R}^N$. We restrict ourselves to the case in which the nonlinear gradient term has a scaling...
A graph is said to be globally rigid in $d$-dimensional space if almost all of its embeddings are unique up to isometries. If a graph has enough automorphisms to send any of its vertices into any other, then it is called vertex-transitive. We show that, in any dimension, highly regular vertex-transitive graphs are globally rigid,...
Parameter estimation of gravitational wave signals is computationally intensive and typically requires millions of likelihood evaluations to construct posterior probability distributions. This computational cost increases significantly in the time domain, which requires non-diagonal covariance matrices to compute the likelihood....
Standard agreement metrics often fail to capture systematic differences in opinion between minority and majority-group annotators, jeopardizing tasks such as hate speech and toxicity detection. Polarization has recently been proposed as a more robust way of distinguishing minor disagreements from systematic differences in opinion, but...
Query expansion is a long-standing technique to mitigate vocabulary mismatch in ad hoc Information Retrieval. Pseudo-relevance feedback methods, such as RM3, estimate an expanded query model from the top-ranked documents, but remain vulnerable to topic drift when early results include noisy or tangential content. Recent approaches...
Ventriloquism After-Effect is the phenomenon where sustained exposure to the ventriloquist illusion causes a change in unisensory auditory localization towards the location where the visual stimulus was present. We investigate the recalibration in EEG networks that causes this change and the track the timeline of changes in the...
Time series often exhibit non-ergodic behaviour that complicates forecasting and inference. This article proposes a likelihood-based approach for estimating ergodicity transformations that addresses such challenges. The method is broadly compatible with standard models, including Gaussian processes, ARMA, and GARCH. A detailed...
We apply a tag-and-probe method to precisely measure the absolute branching fraction of the decay $η_c \to γγ$ with the BESIII experiment at BEPCII. Starting with a large initial sample of $2712.4\pm 14.3$ million $ψ(3686)$ events, a sample of 0.16 million $η_c$ events are tagged via the golden channel $ψ(3686)\to π^0 h_c$, $h_c\to...
Deep learning has significantly advanced image analysis across diverse domains but often depends on large, annotated datasets for success. Transfer learning addresses this challenge by utilizing pre-trained models to tackle new tasks with limited labeled data. However, discrepancies between source and target domains can hinder...
Large Language Models (LLMs) are effective for data augmentation in classification tasks like intent detection. In some cases, they inadvertently produce examples that are ambiguous with regard to untargeted classes. We present DDAIR (Disambiguated Data Augmentation for Intent Recognition) to mitigate this problem. We use Sentence...
We define two minimum distance estimators for dependent data by minimizing some approximated Maximum Mean Discrepancy distances between the true empirical distribution of observations and their assumed (parametric) model distribution. When the latter one is intractable, it is approximated by simulation, allowing to accommodate most...
Large language models (LLMs) are widely used in knowledge-intensive applications but often generate factually incorrect responses. A promising approach to rectify these flaws is correcting LLMs using feedback. Therefore, in this paper, we introduce FactCorrector, a new post-hoc correction method that adapts across domains without...
Despite the growing prevalence of large language models (LLMs) in domain-specific applications, the challenge of query understanding in the automotive sector still remains underexplored. This domain presents unique complexities due to its specialized vocabulary and the diverse range of user intents it encompasses. Unlike...
We consider the problem of adaptively monitoring a wildfire front using a mobile agent (e.g., a drone), whose trajectory determines where sensor data is collected and thus influences the accuracy of fire propagation estimation. This is a challenging problem, as the stochastic nature of wildfire evolution requires the seamless...
In this work, we study the jet quenching parameter ${\hat q}$ by using a background field effective theory. Particular attention is paid to its behavior near the critical temperature where nonperturbative effects induced by the deconfining phase transition are taken into account through a self-consistently introduced background field...
Qualitative Comparative Analysis (QCA) requires researchers to choose calibration and dichotomization thresholds, and these choices can substantially affect truth tables, minimization, and resulting solution formulas. Despite this dependency, threshold sensitivity is often examined only in an ad hoc manner because repeated analyses...
Earthquake-induced landslides are among the most destructive cascading hazards, yet the physical mechanisms governing their spatial distribution and size remain incompletely understood. While amplification of seismic waves by local topography is well documented, the role of mountain-scale resonance has remained largely untested. Here...
Output diversity is crucial for Large Language Models as it underpins pluralism and creativity. In this work, we reveal that controlling the language used during model thinking-the language of thought-provides a novel and structural source of output diversity. Our preliminary study shows that different thinking languages occupy...