% CVPR 2026 Paper Template; see https://github.com/cvpr-org/author-kit

\documentclass[10pt,twocolumn,letterpaper]{article}

%%%%%%%%% PAPER TYPE  - PLEASE UPDATE FOR FINAL VERSION
% Use exactly one of the following (loading cvpr twice causes an option clash):
\usepackage{cvpr}                 % Camera-ready (submission: no page numbers)
% \usepackage[review]{cvpr}         % Review version
% \usepackage[pagenumbers]{cvpr}      % Camera-ready + page numbers (e.g. arXiv)
\usepackage{multicol}
\usepackage{multirow}
\usepackage{makecell}

% Import additional packages in the preamble file, before hyperref
\input{preamble}

% It is strongly recommended to use hyperref, especially for the review version.
% hyperref with option pagebackref eases the reviewers' job.
% Please disable hyperref *only* if you encounter grave issues, 
% e.g. with the file validation for the camera-ready version.
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% If you comment hyperref and then uncomment it, you should delete *.aux before re-running LaTeX.
% (Or just hit 'q' on the first LaTeX run, let it finish, and you should be clear).
\definecolor{cvprblue}{rgb}{0.21,0.49,0.74}
\usepackage[pagebackref,breaklinks,colorlinks,allcolors=cvprblue]{hyperref}

%%%%%%%%% PAPER ID  - PLEASE UPDATE
\def\paperID{51} % *** Enter the Paper ID here
\def\confName{CVPR}
\def\confYear{2026}

%%%%%%%%% TITLE - PLEASE UPDATE
\title{Layout-Aware Representation Learning for Open-Set ID Fraud Discovery}

%%%%%%%%% AUTHORS - PLEASE UPDATE
\author{Jinxing Li$^*$, Nicholas Ren, Cathy Chang, Hongkai Pan, Daniel George\\
Persona Identities\\
{\tt\small jinxing.li@withpersona.com}
}

\begin{document}
\maketitle
\input{sec/0_abstract}    
\input{sec/1_intro}
\input{sec/2_related}
\input{sec/3_methodology}
\input{sec/4_results}
\input{sec/5_fraud}
\input{sec/6_conclusions}

\section*{Acknowledgements}
We acknowledge the support from Charles Yeh, Dan Lee, James Chang and Saatvik Billa. 

\section*{Data Statement}
All data used for model training is properly sourced and obtained with appropriate consent for identity verification and fraud prevention purposes. Canada has strict privacy regulations governing the processing of personal data. Accordingly, no data originating from Canadian individuals was used in the training of these models.

{
    \small
    \bibliographystyle{ieeenat_fullname}
    \bibliography{id_rep}
}

% WARNING: do not forget to delete the supplementary pages from your submission 
% \input{sec/X_suppl}

\end{document}
