Related papers: Updates of PDFs in the MSTW framework
Scientific writing builds upon already published papers. Manual identification of publications to read, cite or consider as related papers relies on a researcher's ability to identify fitting keywords or initial papers from which a…
In this proceeding contribution we discuss the status and progress towards a modernised and extended International Lattice Data Grid (ILDG), which has seen major developments, updates, and upgrades over the last year. In particular,…
Recently, automatically extracting information from visually rich documents (e.g., tickets and resumes) has become a hot and vital research topic due to its widespread commercial value. Most existing methods divide this task into two…
Given the non-negligible interplay between parton distribution functions (PDFs) at large x and potential New Physics (NP) effects in the high-energy tails of hadron collider observables, a central question is which PDFs can be reliably…
In an earlier publication, we introduced the software package, {\tt \texttt{ePump}} (error PDF Updating Method Package), that can be used to update or optimize a set of parton distribution functions (PDFs), including the best-fit PDF set…
Heavy quark parton distribution functions (PDFs) play an important role in several Standard Model and New Physics processes. Most PDF analyses rely on the assumption that the charm and bottom PDFs are generated perturbatively by gluon…
We scrutinize the recent LHCb data for D$^0$-meson production in p+Pb collisions within a next-to-leading order QCD framework. Our calculations are performed in the SACOT-$m_{\rm T}$ variant of the general-mass variable-flavour-number…
Data collected by the LHCb experiment allow proton structure functions to be probed in a kinematic region beyond the reach of other experiments, both at the LHC and further afield. In these proceedings the significant impact of LHCb Run 1…
This paper introduces an abductive framework for updating knowledge bases represented by extended disjunctive programs. We first provide a simple transformation from abductive programs to update programs which are logic programs specifying…
Deep neural networks have achieved significant improvements in information retrieval (IR). However, most existing models are computational costly and can not efficiently scale to long documents. This paper proposes a novel End-to-End neural…
Large language models (LLMs) are becoming useful in many domains due to their impressive abilities that arise from large training datasets and large model sizes. However, research on LLM-based approaches to document inconsistency detection…
We review basic ideas and recent developments on the determination of the parton substructure of the nucleon, in view of applications to precision hadron collider physics. We review the way information on parton distributions (PDFs) is…
Authors seeking to communicate with broader audiences often share their ideas in various document formats, such as slide decks, newsletters, reports, and posters. Prior work on document generation has generally tackled the creation of each…
We describe the inclusion of the photon as an additional component of the proton's Parton Distribution Functions (PDFs) in the MMHT framework. The input for the photon is adopted from the recent LUXqed determination. We describe the…
This article aims at reengineering of PDF-based complex documents, where specifications of the Object Management Group (OMG) are our initial targets. Our motivation is that such specifications are dense and intricate to use, and tend to…
We study the impact of the inclusion of Neutral Current (NC) DY data from LHC mapped in the Forward-Backward Asymmetry ($A_{\rm FB}$) observable on PDF uncertainties, using the open source platform \texttt{xFitter}. We find that $A_{\rm…
The machine learning publication process is broken, of that there can be no doubt. Many of these flaws are attributed to the current workflow: LaTeX to PDF to reviewers to camera ready PDF. This has understandably resulted in the desire for…
We present a novel system providing summaries for Computer Science publications. Through a qualitative user study, we identified the most valuable scenarios for discovery, exploration and understanding of scientific documents. Based on…
Large language models (LLMs) have been applied to a wide range of tasks, including text summarization, web navigation, and chatbots. They have benefitted from supervised fine-tuning (SFT) and reinforcement learning from human feedback…
Precision electroweak tests are a powerful probe of physics beyond the Standard Model, but the sensitivity is limited by the precision with which the $W$ boson mass ($M_W$) has been measured. The Parton Distribution Function (PDF)…