Related papers: A new simple PDF parametrization: improved descrip…
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 standardization of the data format, for the theory…
We present a new global determination of the helicity-dependent parton distribution functions (PDFs) of the proton, based on inclusive deep-inelastic scattering (DIS) and semi-inclusive DIS (SIDIS) data within a consistent next-to-leading…
We show how to account for correlations between theoretical uncertainties incorporated in parton distribution function (PDF) fits, and the theoretical uncertainties in the predictions made using these PDFs. We demonstrate by explicit…
With the rapid scaling of large language models (LLMs), serving numerous low-rank adaptations (LoRAs) concurrently has become increasingly impractical, leading to unaffordable costs and necessitating more parameter-efficient finetuning…
This paper introduces Uniform Orthogonal Reinitialization Adaptation (UORA), a novel parameter-efficient fine-tuning (PEFT) approach for Large Language Models (LLMs). UORA achieves state-of-the-art performance and parameter efficiency by…
We propose Domain Adaptation via Feature Refinement (DAFR2), a simple yet effective framework for unsupervised domain adaptation under distribution shift. The proposed method synergistically combines three key components: adaptation of…
We discuss the current developments by the European Twisted Mass Collaboration in extracting parton distribution functions from the quasi-PDF approach. We concentrate on the non-perturbative renormalization prescription recently developed…
We validate the use of matrix factorization for the automatic identification of relevant components from atomic pair distribution function (PDF) data. We also present a newly developed software infrastructure for analyzing the PDF data…
We present an improved leading-order global DGLAP analysis of nuclear parton distribution functions (nPDFs), supplementing the traditionally used data from deep inelastic lepton-nucleus scattering and Drell-Yan dilepton production in…
We present numerical studies of the leading non-linear corrections to the Dokshitzer-Gribov-Lipatov-Altarelli-Parisi evolution equations of parton distribution functions (PDFs) resulting from gluon recombination. The effect of these…
Low-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank matrices $A$ and $B$ to represent the weight change, i.e.,…
I consider variations in the definitions, at next-to-leading order (NLO) and at next-to-next-to leading order (NNLO), of a General-Mass Variable Flavour Number Scheme (GM-VFNS) for heavy flavour structure functions. I also define a new…
We present the main results of our recent papers, where we derived an analytical solution of the QCD evolution equations for parton distribution functions. The valence and non-singlet quark components satisfy the Gross-Llewellyn-Smith and…
The use of machine learning algorithms in theoretical and experimental high-energy physics has experienced an impressive progress in recent years, with applications from trigger selection to jet substructure classification and detector…
Parameter-efficient fine-tuning (PEFT) techniques, such as adapter tuning, aim to fine-tune a pre-trained language model (PLM) using a minimal number of parameters for a specific task or profile. Although adapter tuning provides increased…
The H1 and Zeus collaborations have measured the inclusive diffractive DIS cross section ep -> eXp and these measurements are in good agreement within a normalisation uncertainty. Diffractive parton density functions (DPDFs) have been…
We present a determination of a set of polarized parton distributions (PDFs) of the nucleon, at next-to-leading order, from a global set of longitudinally polarized deep-inelastic scattering data: NNPDFpol1.0. The determination is based on…
We study the effect on the parton distribution functions (PDFs) from the inclusion of projected measurements in the Drell-Yan (DY) di-lepton production neutral channel of the angular coefficient associated to the $Z$-boson longitudinal…
Variance parameters in additive models are typically assigned independent priors that do not account for model structure. We present a new framework for prior selection based on a hierarchical decomposition of the total variance along a…
We complete the procedure of extracting parton distribution functions (PDFs) using large momentum effective theory (LaMET) at leading power accuracy in the hadron momentum. We derive a general factorization formula for the quasi PDFs in the…