\documentclass[ xcolor={svgnames}, hyperref={colorlinks,citecolor=DeepPink4,linkcolor=DarkRed,urlcolor=DarkBlue} ]{beamer} % define using customized theme. \usetheme{pas} % define using packages \usepackage[utf8]{inputenc} \usepackage[T1]{fontenc} \usepackage {minted} % the general information. \title[] % (optional, only for long titles) {Citation Intent Classification} \subtitle{Identifying the Intent of a Citation in scientific papers} \author[tmip, hieutt] % (optional, for multiple authors) {Isaac Riley and Pavan Mandava} \institute[Universities Here and There] % (optional) { \inst{1}% Computational Linguistics, M.Sc.\\ \and \inst{2}% Computational Linguistics, M.Sc.\\ } \date[] % (optional) {May 20, 2020} \subject{Computational Linguistics} % begin presentation content \begin{document} %%%% Slide : 1 -- INTRO \begin{frame} \titlepage \end{frame} %%%% TASK DESCRIPTION ----- Slide 2 \begin{frame} \frametitle{Task Description} \begin{itemize} \item Identifying intent of a citation in scientific papers \item Three Intent categories/classes from the data set \begin{enumerate} \item background (background information) \item method (use of methods/tools) \item result (comparing results) \end{enumerate} \item Classification Task \begin{itemize} \item Assign a discrete class (intent) for each data point \end{itemize} \end{itemize} \end{frame} %%%% DATA SET ---- Slide 3 \begin{frame} \frametitle{Data set} \begin{itemize} \item Training Data: 8.2K+ data points \begin{enumerate} \item background - 4.8K \item method - 2.3K \item result - 1.1K \end{enumerate} \item Testing Data: 1.8K data points \begin{enumerate} \item background - 1K \item method - 0.6K \item result - 0.2K \end{enumerate} \end{itemize} \end{frame} %%%% Approach/Architectures ---- Slide 4 \begin{frame}[fragile] \frametitle{Approach \& Architecture} \framesubtitle{Classifier Implementation} Base Classifier: {\bf {\color{red} Perceptron}} \begin{itemize} \item Linear Classifier \item Binary Classifier \end{itemize} \bigskip \begin{minted}[autogobble, breaklines,breakanywhere, fontfamily=helvetica, fontsize=\small]{python} class Perceptron: def __init__(self, label: str, weights: dict, theta_bias: float) def score(self, features: list) def update_weights(self, features: list, learning_rate: float, penalize: bool, reward: bool) class MultiClassPerceptron: def __init__(self, epochs: int,learning_rate: float,random_state: int) def fit(self, X_train: list, labels: list) def predict(self, X_test: list) \end{minted} \end{frame} %%%% Approach/Architectures ---- Slide 5 \begin{frame}[fragile] \frametitle{Approach \& Architecture} \framesubtitle{Feature Representation} Lexicons and Regular Expressions \begin{itemize} \item LEXICONS \item REGEX \end{itemize} \end{frame} \begin{frame} \frametitle{There Is No Largest Prime Number} \framesubtitle{The proof uses \textit{reductio ad absurdum}.} \begin{theorem} There is no largest prime number. \end{theorem} \begin{enumerate} \item<1-| alert@1> Suppose $p$ were the largest prime number. \item<2-> Let $q$ be the product of the first $p$ numbers. \item<3-> Then $q+1$ is not divisible by any of them. \item<1-> But $q + 1$ is greater than $1$, thus divisible by some prime number not in the first $p$ numbers. \end{enumerate} \end{frame} \begin{frame}{A longer title} \begin{itemize} \item one \item two \end{itemize} \end{frame} \begin{frame}[allowframebreaks] \frametitle{References} \bibliographystyle{plain} \bibliography{lib} \end{frame} \end{document}