25 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Institut National de la Recherche Agronomique de TunisieTN12 papers
- International Society of AutomationUS12 papers
- Spectrum Scientific (United States)US12 papers
- Hellenic Petroleum (Greece)GR9 papers
- European Organization for Nuclear ResearchCH3 papers
- Deutsches Elektronen-Synchrotron DESYDE2 papers
- RIKEN Center for Computational ScienceJP2 papers
- University of BonnDE2 papers
- Archimedia (Greece)GR1 paper
- Arrow International (United States)US1 paper
- Astronomical Observatory of RomeIT1 paper
- Athena Research and Innovation Center In Information Communication & Knowledge TechnologiesGR1 paper
12 papers
Spectra for the Vacuum Cherenkov Effect in Astrophysical Electromagnetic Cascades with Lorentz Invariance Violation
Andrey Saveliev, Rafael Alves Batista, Feodor Mishin
Lorentz invariance violation is a feature of several quantum gravity models in which Lorentz symmetry is broken at high energies, possibly leading to changes in particle behavior a…
A Position Paper on the Automatic Generation of Machine Learning Leaderboards
Roelien C Timmer, Yufang Hou, Stephen Wan
An important task in machine learning (ML) research is comparing prior work, which is often performed via ML leaderboards: a tabular overview of experiments with comparable conditi…
Evaluation and Facilitation of Online Discussions in the LLM Era: A Survey
Katerina Korre, Dimitris Tsirmpas, Nikos Gkoumas +5
We present a survey of methods for assessing and enhancing the quality of online discussions, focusing on the potential of LLMs. While online discourses aim, at least in theory, to…
NNLO fits of top-quark mass using total, single-differential and double-differential cross-section data
S. Alekhin, M. V. Garzelli, J. Mazzitelli +2
We describe the fits of the top-quark mass value at NNLO using as input the double-differential distributions in rapidity and invariant mass of pairs obtained by the ATL…
Current progress on the semileptonic form factors for decay using the Oktay-Kronfeld action
Tanmoy Bhattacharya, Benjamin J. Choi, Rajan Gupta +8
We present recent progress in calculating the semileptonic form factors for the decays. We use the Oktay-Kronfeld (OK) action for the…
Chiral fermion on quantum computers
Arata Yamamoto, Tomoya Hayata, Katsumasa Nakayama
Quantum computation often suffers from artificial symmetry breaking. We should strive to suppress the artifact both by theoretical and technological improvements. The theoretical f…
A New Technique of the Virtual Reality Visualization of Complex Volume Images from the Computer Tomography and Magnetic Resonance Imaging
Iva Vasic, Roberto Pierdicca, Emanuele Frontoni +1
This paper presents a new technique for the virtual reality (VR) visu-alization of complex volume images obtained from computer tomography (CT) and Magnetic Resonance Imaging (MRI)…
Hadronic observables from master-field simulations
Marco Cè, Mattia Bruno, John Bulava +5
Substantial progress has been made recently in the generation of master-field ensembles. This has to be paired with efficient techniques to compute observables on gauge field confi…
Determination of Lee-Yang edge singularities in QCD by rational approximations
Kevin Zambello, David A. Clarke, Petros Dimopoulos +5
We report updated results on the determination of Lee-Yang edge (LYE) singularities in QCD using highly improved staggered quarks (HISQ) with physical masses on $N_τ= 4…
Theory pipeline for PDF fitting
Andrea Barontini, Alessandro Candido, Juan Cruz-Martinez +3
Fitting PDFs requires the integration of a broad range of datasets, both from data and theory side, into a unique framework. While for data the integration mainly consists in the s…
ferret: a Framework for Benchmarking Explainers on Transformers
Giuseppe Attanasio, Eliana Pastor, Chiara Di Bonaventura +1
As Transformers are increasingly relied upon to solve complex NLP problems, there is an increased need for their decisions to be humanly interpretable. While several explainable AI…
Machine Learning of Thermodynamic Observables in the Presence of Mode Collapse
Kim A. Nicoli, Christopher Anders, Lena Funcke +5
Estimating the free energy, as well as other thermodynamic observables, is a key task in lattice field theories. Recently, it has been pointed out that deep generative models can b…