diff --git a/packages/CLPBN/pfl.tex b/packages/CLPBN/pfl.tex
index 27f051424..9793b0e9f 100644
--- a/packages/CLPBN/pfl.tex
+++ b/packages/CLPBN/pfl.tex
@@ -38,7 +38,7 @@ CRACS \& INESC TEC, Faculty of Sciences, University of Porto
 \thispagestyle{empty}
 \vspace{5cm}
 \begin{center}
-  \large Last revision: January 18, 2013
+  \large Last revision: April 12, 2013
 \end{center}
 \newpage
 
@@ -87,7 +87,7 @@ A first-order probabilistic graphical model is described using parametric factor
 
 $$Type~~F~~;~~Phi~~;~~C.$$
 
-, where
+Where,
 \begin{itemize}
 \item $Type$ refers the type of network over which the parfactor is defined. It can be \texttt{bayes} for directed networks, or \texttt{markov} for undirected ones.
 
@@ -489,9 +489,9 @@ The options that are available with the \texttt{set\_pfl\_flag/2} predicate can
 %------------------------------------------------------------------------------
 %------------------------------------------------------------------------------
 %------------------------------------------------------------------------------
-\section{Further Information}
-Please check the paper \textit{Evaluating Inference Algorithms for the Prolog Factor Language} for further information.
-
-Any question? Don't hesitate to contact us!
+\section{Papers}
+\begin{itemize}
+  \item \textit{Evaluating Inference Algorithms for the Prolog Factor Language}.
+\end{itemize}
 
 \end{document}