Prépublication
· 2026 arXiv
EN
Comics are one of the great visual records of the twentieth century: hundreds of thousands of pages in which a mass readership saw its leaders, its wars and its heroes. Most of this record has never been studied as a whole; comics scholarship proceeds one book...
Emilio Ferrara
#cs.AI
Prépublication
· 2026 arXiv
EN
When solving complex spatial reasoning tasks, ordinary humans naturally revisit the scenes from task-relevant viewpoints and mentally reconstruct the spatial layouts from those viewpoints. But can Large Vision-Language Models (LVLMs) proactively think in the s...
Yuhong Liu, Shenxi Wu et al.
#cs.CV
Prépublication
· 2026 arXiv
EN
A central challenge in embodied recursive self-improvement is enabling agents to convert interaction history into capabilities that persist beyond one world and transfer to later tasks. A saved memory or successful final action does not by itself establish tha...
Jingwei Song, Zhisheng Chen et al.
#cs.RO
Prépublication
· 2026 arXiv
EN
Recent advances in automatic pronunciation assessment (APA) have driven a shift from scripted to free-form assessment. However, existing methods often rely on multi-stage pipelines with forced alignment and separate feature extractors, limiting their practical...
Fu-An Chao, Bi-Cheng Yan et al.
#eess.AS
Prépublication
· 2026 arXiv
EN
Semantic query engines ask a large language model (LLM) to judge individual rows, and benchmarks compare these engines on the quality of a few executions at temperature 0. We measure how much another execution changes. We re-execute the text and tabular worklo...
Oktie Hassanzadeh, Dharmashankar Subramanian
#cs.DB
Prépublication
· 2026 arXiv
EN
A useful language model should know when to answer and when to say "I don't know." Can we improve that decision by training the model itself or by training a separate component to check its answers? We study both approaches on Qwen3-14B for factual questions,...
Juan Terven, Diana-Margarita Córdova-Esparza et al.
#cs.CL
Prépublication
· 2026 arXiv
EN
Currently available methods for processing atmospheric wave disturbances are often based on integral wavelet transform techniques, which efficiently estimate spectral data but are fundamentally limited by the uncertainty principle. To address this limitation,...
Yuriy Klymenko, Alla Fedorenko et al.
#physics.ao-ph
Prépublication
· 2026 arXiv
EN
In this report, 15 variants of nine parametric models for non-directional ocean wave spectra are reviewed. They are compared against observation-based spectra created by taking spectra measured by moored buoys, binning by wind speed, and averaging. Surface Sto...
W. Erick Rogers, Yalin Fan et al.
#physics.ao-ph
Prépublication
· 2026 arXiv
EN
Legacy Fortran physics packages in atmospheric models such as CESM, WRF, and E3SM pose a barrier to GPU modernization, while manual porting requires accelerator-programming expertise. We present LAFT (LLM-Assisted Fortran Translation), an agentic framework for...
Iris Linck, John Dennis et al.
#physics.ao-ph
Prépublication
· 2026 arXiv
EN
To search for very wide-orbit binary-lens events, we cross-match microlensing events detected by OGLE-IV and KMTNet between 2011 and 2024. After removing contaminants from variable stars, we identify OGLE-2016-BLG-0523 as a microlensing event showing two short...
Hongjing Yang, Weicheng Zang et al.
#astro-ph.EP
Prépublication
· 2026 arXiv
EN
We develop a unified description of convolution on the sphere by lifting to the rotation group. A number of definitions of spherical convolution have been proposed, differing in whether the kernel is axisymmetric or directional, whether the output is on the sp...
J. D. McEwen
#math-ph
Prépublication
· 2026 arXiv
EN
Contemporary large-scale structure analyses center around the galaxy power spectrum, modeled with one-loop perturbation theory. This description naturally breaks down at large wavenumbers, prohibiting the extraction of cosmological information from small-scale...
Oliver H. E. Philcox
#astro-ph.CO