Define bycite

This commit is contained in:
Filip Gralinski 2021-02-22 22:13:28 +01:00
parent 1715969672
commit ca933acc48
12 changed files with 21 additions and 3 deletions

View File

@ -16,6 +16,8 @@
\input{preamble} \input{preamble}
\input{extras} \input{extras}
\newcommand\bycite[1]{przez~\citet{#1}}
%% %%

View File

@ -29,6 +29,7 @@
\newcommand\citep[1]{\cite{#1}} \newcommand\citep[1]{\cite{#1}}
\newcommand\citet[1]{\newcite{#1}} \newcommand\citet[1]{\newcite{#1}}
\newcommand\bycite[1]{by~\citet{#1}}
\documentclass[11pt]{article} \documentclass[11pt]{article}
\usepackage{coling2020} \usepackage{coling2020}

View File

@ -43,6 +43,7 @@
% in the camera-ready version and ask you to change it back. % in the camera-ready version and ask you to change it back.
\newcommand\BibTeX{B\textsc{ib}\TeX} \newcommand\BibTeX{B\textsc{ib}\TeX}
\newcommand\bycite[1]{by~\citet{#1}}
\input{config} \input{config}
\input{extras} \input{extras}

View File

@ -21,6 +21,8 @@
% to display URLs in blue roman font according to Springer's eBook style: % to display URLs in blue roman font according to Springer's eBook style:
% \renewcommand\UrlFont{\color{blue}\rmfamily} % \renewcommand\UrlFont{\color{blue}\rmfamily}
\newcommand\bycite[1]{in~\citet{#1}}
\input{config} \input{config}
\input{extras} \input{extras}
\input{preamble} \input{preamble}

View File

@ -22,6 +22,8 @@
\else% \else%
\fi \fi
\newcommand\bycite[1]{by~\citet{#1}}
\input{config} \input{config}
\input{preamble} \input{preamble}
\input{extras} \input{extras}

View File

@ -9,6 +9,8 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\documentclass{poleval} \documentclass{poleval}
\newcommand\bycite[1]{by~\citet{#1}}
\input{config} \input{config}
\input{extras} \input{extras}
\input{preamble} \input{preamble}

View File

@ -13,6 +13,8 @@
% ---------------------- PREAMBLE PART ------------------------------ % ---------------------- PREAMBLE PART ------------------------------
\newcommand\bycite[1]{by~\citet{#1}}
\input{config} \input{config}
\input{preamble} \input{preamble}
\input{extras} \input{extras}

View File

@ -78,6 +78,8 @@
%% the next command will enable that style. %% the next command will enable that style.
%%\citestyle{acmauthoryear} %%\citestyle{acmauthoryear}
\newcommand\bycite[1]{in~\citet{#1}}
\input{config} \input{config}
\input{extras} \input{extras}
\input{preamble} \input{preamble}

View File

@ -77,6 +77,8 @@ TACL-submission anonymization requirements)}
\input{metadata} \input{metadata}
\date{} \date{}
\newcommand\bycite[1]{by~\citet{#1}}
\input{config} \input{config}
\input{preamble} \input{preamble}
\input{extras} \input{extras}

View File

@ -19,6 +19,8 @@
\usepackage{placeins} \usepackage{placeins}
\newcommand\bycite[1]{by~\citet{#1}}
\input{config} \input{config}
\input{extras} \input{extras}
\input{preamble} \input{preamble}

View File

@ -17,7 +17,7 @@
abstract = "This paper presents a simple but general and effective method to debug the output of machine learning (ML) supervised models, including neural networks. The algorithm looks for features that lower the evaluation metric in such a way that it cannot be ascribed to chance (as measured by their p-values). Using this method {--} implemented as MLEval tool {--} you can find: (1) anomalies in test sets, (2) issues in preprocessing, (3) problems in the ML model itself. It can give you an insight into what can be improved in the datasets and/or the model. The same method can be used to compare ML models or different versions of the same model. We present the tool, the theory behind it and use cases for text-based models of various types.", abstract = "This paper presents a simple but general and effective method to debug the output of machine learning (ML) supervised models, including neural networks. The algorithm looks for features that lower the evaluation metric in such a way that it cannot be ascribed to chance (as measured by their p-values). Using this method {--} implemented as MLEval tool {--} you can find: (1) anomalies in test sets, (2) issues in preprocessing, (3) problems in the ML model itself. It can give you an insight into what can be improved in the datasets and/or the model. The same method can be used to compare ML models or different versions of the same model. We present the tool, the theory behind it and use cases for text-based models of various types.",
} }
@incollection { gonito2016, @incollection {gonito2016,
title = {Gonito.net -- Open Platform for Research Competition, Cooperation and Reproducibility}, title = {Gonito.net -- Open Platform for Research Competition, Cooperation and Reproducibility},
author = "Grali{\'n}ski, Filip and Jaworski, Rafa{\l} and Borchmann, {\L}ukasz and Wierzcho{\'n}, Piotr", author = "Grali{\'n}ski, Filip and Jaworski, Rafa{\l} and Borchmann, {\L}ukasz and Wierzcho{\'n}, Piotr",
editor = "Branco, António and Calzolari , Nicoletta and Choukri, Khalid", editor = "Branco, António and Calzolari , Nicoletta and Choukri, Khalid",

View File

@ -1,8 +1,8 @@
\section{Main} \section{Main}
This is a~sample paper~\cite{DBLP:journals/corr/cs-CL-0108005}. This is a~sample paper~\cite{gonito2016}.
See the experiments described \bycite{DBLP:journals/corr/cs-CL-0108005}. See the experiments described \bycite{gonito2016}.
Please put your content here. Please put your content here.