如图所示，由于我使用了 natbib，所以有一个缩进。如果我改用普通 bib，则不会出现这种情况，但我无法使用citet()。
\documentclass{article}
\linespread{1.5}
\usepackage{amsmath}
\usepackage{physics}
\usepackage{amssymb}
\usepackage{bm}
\usepackage{mathtools}
\usepackage{eurosym}
\usepackage{booktabs}
\usepackage{placeins}
\usepackage{graphicx}
\usepackage{float}
\usepackage{changepage}
\usepackage[toc,page]{appendix}
\usepackage{tabularx}
\usepackage{xcolor}
\usepackage[utf8]{inputenc}
\usepackage{graphicx}
\usepackage{listings}
\usepackage{enumitem}
\usepackage[T1]{fontenc}
\usepackage[english]{babel}
\usepackage{lmodern}
\usepackage[square,numbers,nonamebreak]{natbib}
\bibliographystyle{plainnat}
\setlength\bibhang{0pt}
\renewcommand{\bibfont}{\raggedright}
\newcommand\tab[1][1.2cm]{\hspace*{#1}}\linespread{1.5}
\usepackage{geometry}
\usepackage{booktabs}
\usepackage{subfig}
\usepackage{placeins}
%\usepackage[font=12p,labelfont=bf]{caption}
\usepackage{tikz}
\usetikzlibrary{positioning}
\begin{document}
\begin{titlepage}
%\newcommand{\HRule}{\rule{\linewidth}{0.5mm}}
\center
\textsc{\LARGE University of Amsterdam}\\[1cm]
\includegraphics[scale=0.45]{Pic/UvA.jpg}\\[1cm]
\textsc{\Large MSc. Econometrics}\\[0.5cm]
{ \LARGE \bfseries Master Thesis}\\[0.4cm]
%\HRule \\[1cm]
\textsc{\LARGE The performance of the Netflix prize winning model on music data.} \\[1cm]
Supervisor: Kevin Pak\\
Student: Joshua Jones, 10757597\\
{\large \today \\ [2cm]}
\begin{abstract}
\input{Abstract.tex}
\end{abstract}
\large\textbf{}\\[2cm]
\end{titlepage}
\tableofcontents{}
\newpage
\section{Introduction}
\input{Indroduction.tex}
\section{Related Work}
\subsection{Basics of Collaborative Filtering}
\input{Relatedwork/CollaborativeFiltering.tex}
\section{Data}
\input{Data.tex}
\section{Methodology}
\subsection{Overview of estimated models}
\input{Methodology/Overview.tex}
\input{Methodology/Baseline.tex}
%\subsection{Netflix models}
\input{Methodology/Netflix.tex}
\subsection{Improved model}
\input{Methodology/Improved.tex}
\section{Results}
\input{Results.tex}
\section{Conclusion}
\input{Conclusion.tex}
\newpage
\bibliographystyle{plain}
\bibliography{References}
\clearpage
\appendix
\section*{Appendices}
\addcontentsline{toc}{section}{Appendices}
\renewcommand{\thesubsection}{\Alph{subsection}}
%\appendixpage
%\addappheadtotoc
\input{appendix.tex}
\end{document}
这是调用下面参考文件的主文件：
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author = {Ying Liu and Jiajun Yang},
doi = {https://doi.org/10.1016/j.procs.2015.07.164},
issn = {1877-0509},
journal = {Procedia Computer Science},
keywords = {Recommendation system, Ranking-based recommendation, Collaborative filtering},
note = {3rd International Conference on Information Technology and Quantitative Management, ITQM 2015},
pages = {732 - 740},
title = {Improving Ranking-based Recommendation by Social Information and Negative Similarity},
url = {http://www.sciencedirect.com/science/article/pii/S1877050915016397},
volume = {55},
year = {2015},
}
@inbook{AdvancesinCollaborativeFiltering,
author = {Koren, Yehuda and Bell, Robert},
doi = {10.1007/978-1-4899-7637-6_3},
isbn = {978-1-4899-7636-9},
month = {01},
pages = {77-118},
title = {Advances in Collaborative Filtering},
year = {2015},
}
@inproceedings{Boltzmann,
author = {Salakhutdinov, Ruslan and Mnih, Andriy and E. Hinton, Geoffrey},
doi = {10.1145/1273496.1273596},
journal = {ACM International Conference Proceeding Series},
month = {01},
pages = {791-798},
title = {Restricted Boltzmann machines for collaborative filtering},
volume = {227},
year = {2007},
}
@inproceedings{MSD1,
author = {Thierry Bertin-Mahieux and Daniel P.W. Ellis and Brian Whitman and Paul Lamere},
title = {The Million Song Dataset},
booktitle = {{Proceedings of the 12th International Conference on Music Information
Retrieval ({ISMIR} 2011)}},
year = {2011},
owner = {thierry},
timestamp = {2010.03.07}
}
@misc{echo,
title = {The Echo Nest Taste profile subset, the official user data collection for the Million Song Dataset},
author = {{The Echo Nest}},
howpublished={\url{http://labrosa.ee.columbia.edu/millionsong/tasteprofile}},
note = {Retrieved on: 10.04.2019}
}
@MISC{TheBellkorSolution,
author = {Robert M. Bell and Yehuda Koren and Chris Volinsky},
title = {The BellKor solution to the Netflix Prize},
year = {2007}
}
@misc{Echo2,
title = {The Echo Nest company website, available at:},
author = {{The Echo Nest}},
howpublished={\url{http://the.echonest.com/company/}},
note = {Retrieved on: 10.04.2019}
}
@misc{Kaggle,
title={Million Song Dataset Challenge, the Kaggle challenge, available at:},
author = {Kaggle},
howpublished={\url{https://www.kaggle.com/c/msdchallenge}},
note = {Retrieved on: 10.04.2019}
}
@misc{MSD2,
title={The Echo Nest company website, available at:},
author = {Thierry Bertin-Mahieux},
howpublished={\url{http://labrosa.ee.columbia.edu/millionsong}},
note = {Retrieved on: 10.04.2019}
}
@misc{NetflixPrize,
title={The Netflix Prize Official Website, available at:},
author = {Netflix},
howpublished={\url{https://www.netflixprize.com/index.html}},
note = {Retrieved on: 10.04.2019}
}
@misc{Johnson,
title = {Algorithmic music recommendations at spotify, available at:},
author = {Chris Johnson},
howpublished={\url{http://www.slideshare.net/MrChrisJohnson/algorithmic-music-recommendations-at-spotify/}},
note = {Retrieved on: 10.04.2019}
}
@article{Sanchez,
author = {S\'{a}nchez-Moreno, Diego and Gil Gonz\'{a}lez, Ana B. and Mu\~{n}oz Vicente, M. Dolores and L\'{o}pez Batista, Vivian F. and Moreno Garc\'{\i}a, Mar\'{\i}a N.},
title = {A Collaborative Filtering Method for Music Recommendation Using Playing Coefficients for Artists and Users},
journal = {Expert Syst. Appl.},
issue_date = {December 2016},
volume = {66},
number = {C},
month = dec,
year = {2016},
issn = {0957-4174},
pages = {234--244},
numpages = {11},
url = {https://doi.org/10.1016/j.eswa.2016.09.019},
doi = {10.1016/j.eswa.2016.09.019},
acmid = {3006098},
publisher = {Pergamon Press, Inc.},
address = {Tarrytown, NY, USA},
keywords = {Collaborative filtering, Data mining, Gray-sheep, Music recommendation, Sparsity},
}
@inproceedings{Sarwar,
author = {Sarwar, Badrul and Karypis, George and Konstan, Joseph and Riedl, John},
title = {Item-based Collaborative Filtering Recommendation Algorithms},
booktitle = {Proceedings of the 10th International Conference on World Wide Web},
series = {WWW '01},
year = {2001},
isbn = {1-58113-348-0},
location = {Hong Kong, Hong Kong},
pages = {285--295},
numpages = {11},
url = {http://doi.acm.org/10.1145/371920.372071},
doi = {10.1145/371920.372071},
acmid = {372071},
publisher = {ACM},
address = {New York, NY, USA},
}
@inproceedings{Grouplens,
author = {Resnick, Paul and Iacovou, Neophytos and Suchak, Mitesh and Bergstrom, Peter and Riedl, John},
title = {GroupLens: An Open Architecture for Collaborative Filtering of Netnews},
booktitle = {Proceedings of the 1994 ACM Conference on Computer Supported Cooperative Work},
series = {CSCW '94},
year = {1994},
isbn = {0-89791-689-1},
location = {Chapel Hill, North Carolina, USA},
pages = {175--186},
numpages = {12},
url = {http://doi.acm.org/10.1145/192844.192905},
doi = {10.1145/192844.192905},
acmid = {192905},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {Usenet, collaborative filtering, electronic bulletin boards, information filtering, netnews, selective dissemination of information, social filtering, user model},
}
@article{Herlocker,
author = {Herlocker, Jonathan L. and Konstan, Joseph A. and Terveen, Loren G. and Riedl, John T.},
title = {Evaluating Collaborative Filtering Recommender Systems},
journal = {ACM Trans. Inf. Syst.},
issue_date = {January 2004},
volume = {22},
number = {1},
month = jan,
year = {2004},
issn = {1046-8188},
pages = {5--53},
numpages = {49},
url = {http://doi.acm.org/10.1145/963770.963772},
doi = {10.1145/963770.963772},
acmid = {963772},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {Collaborative filtering, evaluation, metrics, recommender systems},
}
@inproceedings{Paterek,
title={Improving regularized singular value decomposition for collaborative filtering},
author={Arkadiusz Paterek},
year={2007}
}
@article{leedaniel,
author = {Lee, Daniel and Seung, Hyunjune},
journal = {Adv. Neural Inform. Process. Syst.},
month = {02},
title = {Algorithms for Non-negative Matrix Factorization},
volume = {13},
year = {2001},
}
@article{xinzhou,
author = {Xin Luo and
MengChu Zhou and
Shuai Li and
Mingsheng Shang},
title = {An Inherently Nonnegative Latent Factor Model for High-Dimensional
and Sparse Matrices from Industrial Applications},
journal = {{IEEE} Trans. Industrial Informatics},
volume = {14},
number = {5},
pages = {2011--2022},
year = {2018},
url = {https://doi.org/10.1109/TII.2017.2766528},
doi = {10.1109/TII.2017.2766528},
timestamp = {Sat, 24 Nov 2018 00:00:00 +0100},
biburl = {https://dblp.org/rec/bib/journals/tii/LuoZ0S18},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@INPROCEEDINGS{KDD,
author = {Robert M. Bell and Yehuda Koren and Chris Volinsky},
title = {Modeling relationships at multiple scales to improve accuracy of large recommender systems},
booktitle = {Proc. KDD’07},
year = {2007}
}
@article{HALS,
author = {Kim, Jinguand He, Yunlongand Park, Haesun},
issn = {1573-2916},
journal = {Journal of Global Optimization},
month = {Feb},
number = {2},
pages = {285--319},
title = {Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework},
url = {https://doi.org/10.1007/s10898-013-0035-4},
volume = {58},
year = {2014},
}
@article{NALS,
author = {Kim, H. and Park, H.},
doi = {10.1137/07069239X},
eprint = {https://doi.org/10.1137/07069239X},
journal = {SIAM Journal on Matrix Analysis and Applications},
number = {2},
pages = {713-730},
title = {Nonnegative Matrix Factorization Based on Alternating Nonnegativity Constrained Least Squares and Active Set Method},
url = {https://doi.org/10.1137/07069239X},
volume = {30},
year = {2008},
}
@inproceedings{NSVDalgorithm,
author = {Takács, Gábor and Pilászy, István and Németh, Bottyán and Tikk, Domonkos},
doi = {10.1109/ICADIWT.2008.4664342},
journal = {1st International Conference on the Applications of Digital Information and Web Technologies, ICADIWT 2008},
month = {09},
pages = {186 - 191},
title = {A Unified Approach of Factor Models and Neighbor Based Methods for Large Recommender Systems},
year = {2008},
}