Related papers: VIPCALs: A fully automated calibration pipeline fo…

We present VIPGI, an automatized human supervised reduction environment, developed within the VIRMOS project to handle VIMOS guaranteed time data. VIPGI is now offered to the international community to be used on site in Milano and…

Language has always been one of humanity's defining characteristics. Visual Language Identification (VLI) is a relatively new field of research that is complex and largely understudied. In this paper, we present a preliminary study in which…

In this paper we describe a new approach for mm-VLBI calibration that provides bona-fide astrometric alignment of the mm-wavelength images from a single source, for the measurement of frequency dependent effects, such as `core-shifts' near…

We present the results of a survey of radio continuum sources near the Galactic plane using the Very Long Baseline Array (VLBA). Our observations are designed to identify compact extragalactic sources of milliarcsecond size that can be used…

PiML (read $\pi$-ML, /`pai`em`el/) is an integrated and open-access Python toolbox for interpretable machine learning model development and model diagnostics. It is designed with machine learning workflows in both low-code and high-code…

In this document we layout a new method to achieve "bona fide" high precision Very-Long-Baseline-Interferometry (VLBI) astrometric measurements of frequency-dependent positions of celestial sources (even) in the high (mm-wavelength)…

We report on a recent 90 cm wide-field VLBI survey of two 3.1 deg^2 fields using the VLBA, Westerbork and Jodrell Bank telescopes. In-beam calibration was used to calibrate each field, the process was simplified by imaging the calibrators…

The next-generation space VLBI mission, VSOP-2, is expected to provide unprecedented spatial resolutions at 8.4, 22, and 43GHz. In this report, phase referencing with VSOP-2 is examined in detail based on a simulation tool called ARIS. The…

Automated machine learning streamlines the task of finding effective machine learning pipelines by automating model training, evaluation, and selection. Traditional evaluation strategies, like cross-validation (CV), generate one value that…

We present the results of the pilot observations of the Deep Extragalactic VLBI-Optical Survey (DEVOS). Our ultimate aim is to collect information on compact structures in a large sample of extragalactic radio sources (~10000 objects) up to…

We have obtained mas-scale resolution very long baseline interferometry (VLBI) images of a sample of Seyfert 1 and Seyfert 2 galaxies at 5 GHz (wavelength, $\lambda$ = 6 cm). The Seyferts of the two types were chosen to be matched in…

The reconstruction of the polarization of a source in radio interferometry is a challenging calibration problem since the reconstruction strongly depends on the gains and leakages that need to be inferred along with the image. This is…

{Context}. The HIFI instrument on the Herschel Space Observatory performed over 9100 astronomical observations, almost 900 of which were calibration observations in the course of the nearly four-year Herschel mission. The data from each…

Atmospheric propagation effects at millimeter wavelengths can significantly alter the phases of radio signals and reduce the coherence time, putting tight constraints on high frequency Very Long Baseline Interferometry (VLBI) observations.…

A rigorous approach to simultaneously determine a Terrestrial Reference Frame (TRF) and Earth Orientation Parameters (EOP) is now currently applied on a routine basis in a coordinated project within the Groupe de Recherches de G\'eod\'esie…

Inspired by human SYSTEM 2 thinking, LLMs excel at complex reasoning tasks via extended Chain-of-Thought. However, similar test-time scaling for diffusion models to tackle complex reasoning remains largely unexplored. From existing work,…

The ionospheric path delay impacts single-band very long baseline interferometry (VLBI) group delays, which limits their applicability for absolute astrometry. I consider two important cases: when observations are made simultaneously at two…

For many practical applications in wireless communications, we need to recover a structured sparse signal from a linear observation model with dynamic grid parameters in the sensing matrix. Conventional expectation maximization (EM)-based…

Vision-language foundation models (VLMs) show promise for diverse imaging tasks but often underperform on medical benchmarks. Prior efforts to improve performance include model finetuning, which requires large domain-specific datasets and…

Detecting bias in multimodal news requires models that reason over text--image pairs, not just classify text. In response, we present ViLBias, a VQA-style benchmark and framework for detecting and reasoning about bias in multimodal news.…