arXiv preprints from January 1, 2026 through September 16, 2026 — 09:54:50 EST
In an era where cyber threats are rapidly evolving, the reliability of cyber forensic analysis has become increasingly critical for effective digital investigations and cybersecurity responses. AI agents are being adopted across digital forensic practices due to their ability to automate processes such as anomaly detection, evidence...
The Shapley value provides a principled framework for fairly distributing rewards among participants according to their individual contributions. While prior work has applied this concept to data valuation in machine learning, existing formulations overwhelmingly assume that each participant contributes a fixed, deterministic dataset....
Understanding the connection between active galactic nuclei and star-formation (the AGN-SF connection) is one of the longest standing problems in modern astrophysics. In the age of large Integral Field Unit (IFU) surveys, studies of the AGN-SF connection greatly benefit from spatially resolving AGN and SF contributions to study the...
This report distills the discussions and recommendations from the NSF Workshop on AI for Electronic Design Automation (EDA), held on December 10, 2024 in Vancouver alongside NeurIPS 2024. Bringing together experts across machine learning and EDA, the workshop examined how AI-spanning large language models (LLMs), graph neural networks...
IGR J17091-3624 is a distinctive black hole X-ray binary exhibiting exotic variability, including complex "heartbeat" oscillations in its X-ray light curves, similar to those observed in GRS 1915+105, a system renowned for its structured, rapid X-ray variability but heavily obscured at optical wavelengths. In contrast, IGR J17091-3624...
The paper presents the results of long-term homogeneous spectroscopic studies of the Herbig Ae/Be star HD 141569A obtained in the optical range. We detect spectral variability on timescales of months to years, including changes in the spectrophotometric parameters of the Halpha emission line, as well as other hydrogen absorption...
I study the simplest model of revenue management with reusable resources: admission control of two customer classes into a loss queue. This model's long-run average collected reward has two natural upper bounds: the deterministic relaxation and the full-information offline problem. With these bounds, we can decompose the costs faced...
Scanning tunneling microscopy (STM) and spectroscopy (STS) with $s$-wave superconducting tips has been widely applied to probe exotic superconductors, but its potential for investigating topological superconductors remains unclear. In junctions between an $s$-wave superconductor and a topological superconductor, the dominant tunneling...
Omics data, such as transcriptomics, proteomics, and metabolomics, provide critical insights into disease mechanisms and clinical outcomes. However, their high dimensionality, small sample sizes, and intricate biological networks pose major challenges for reliable prediction and meaningful interpretation. Graph Neural Networks (GNNs)...
A total prime labeling of a graph of order $n$ is an extension of a prime labeling in which we distinctly label the vertices and edges. The goal of the labeling is for adjacent vertex labels to be relatively prime, and for each vertex of degree at least two, the greatest common divisor of the labels on its incident edges is equal to...
The United States labor market has entered a period in which high job vacancy rates and prolonged unemployment persist together. Classical theory attributes such conditions to skills mismatch or geographic immobility, but neither fully explains a pattern now widely reported: qualified candidates are rejected at the earliest, automated...
Transcranial ultrasound must overcome the significant challenge of the human skull, limiting both imaging and therapeutic applications. While high-fidelity numerical simulations can compensate for skull-induced distortions, they require precise skull templates (typically derived from Computed Tomography, CT) and spatial alignment to...
Many LLM-based open-ended search systems freeze the foundation model that proposes improvements to existing solutions, which may bottleneck long-run progress. Recent work has explored updating the proposal model at test time [arXiv:2511.23473], but the update strategy is still typically hand-specified. Therefore, this study...
High-contrast imaging systems using active control with adaptive optics (AO) are often limited by non-common path (NCP) aberrations that are seen only at the final science image. AO systems employing focal-plane wavefront sensors (FP-WFSs) are able to simultaneously correct NCP aberrations and measure science images, but they...
Joint feature modeling in both the spatial and frequency domains has become a mainstream approach in MRI reconstruction. However, existing methods generally treat the frequency domain as a whole, neglecting the differences in the information carried by its internal components. According to Fourier transform theory, phase and amplitude...
This work develops a unified, dimensionless framework for comparing geometrically similar reacting porous-flow systems across scale, with emphasis on hydrometallurgical heap leaching, when particle size distribution (PSD) and intraparticle pore structure differ. Under dynamic similarity, the dimensionless liquid residence-time...
In this study, we propose a homotopy-inspired prompt obfuscation framework to enhance understanding of security and safety vulnerabilities in Large Language Models (LLMs). By systematically applying carefully engineered prompts, we demonstrate how latent model behaviors can be influenced in unexpected ways. Our experiments encompassed...
HIV is a retrovirus that attacks the human immune system and can lead to death without proper treatment. In collaboration with the WHO and the University of Witwatersrand, we study how to improve the efficiency of HIV testing with the goal of eventual deployment, directly supporting progress toward UN Sustainable Development Goal 3.3....
Semiconductor-s-type superconductor nanowires host spinful fermions and cannot be reduced to a single spinless Kitaev chain hosting single Majorana zero mode. Instead, such systems can be converted into two coupled p-wave Kitaev-like chains associated with different spin sectors. Using the bond Fermion transformation and exact...
Electronic phases of matter, such as magnetism and superconductivity, are defined and distinguished by their order parameters quantifying the spontaneous symmetry breaking underlying each phase. Simple cases include the uniform magnetisation of ferromagnets and isotropic gap function of conventional superconductors. Unconventional...
Automated AI research holds great potential to accelerate scientific discovery. However, current LLMs often generate plausible-looking but ineffective ideas. Execution grounding may help, but it is unclear whether automated execution is feasible and whether LLMs can learn from the execution feedback. To investigate these, we first...
Recent research suggests the possibility of the two-dimensional breathing-Kagome magnet Nb$_3$Cl$_8$ hosting a quantum spin liquid state, warranting further study into its magnetic properties. Using ab initio calculations, we show that monolayer Nb$_3$Cl$_8$ has short-range antiferromagnetic correlations among Nb$_3$ trimers with S =...
Optimizing scientific computing algorithms for modern GPUs is a labor-intensive and iterative process involving repeated code modification, benchmarking, and tuning across complex hardware and software stacks. Recent work has explored large language model (LLM)-assisted evolutionary methods for automated code optimization, but these...
Time series encountered in practice are rarely stationary. When the data distribution changes, a forecasting model trained on past observations can lose accuracy. We study a small-footprint test-time adaptation (TTA) framework for causal timeseries forecasting and direction classification. The backbone is frozen, and only...
In decoder-only (causal) transformers, the computation graph created by causal masking routes information through both direct-path attention and indirect paths formed by intermediate tokens. We denote these indirect paths between token pairs as their runways. We argue that certain failure modes of causal transformers as observed by a...