Fix errors in latex compilation

paper/20_related_work.tex

@@ -32,7 +32,7 @@ linear combination of both states.
 \subsection{Word Embeddings} 
 Distributional semantic models (DSMs) have been researched for decades in NLP \cite{turney_frequency_2010}.
 Based on a huge amount of unlabeled texts, DSMs aim to represent words using a real-valued vector (also called embedding) which captures syntactic and semantic similarities between the words.
-Starting with the publication of the work from Collobert et al. \cite{collobert_natural_2011} in 2011, learning embeddings for linguistic units, such as words, sentences or paragraphs, is one of the hot topics in NLP and a plethora of approaches have been proposed \cite{bojanowski_enriching_2017,mikolov_distributed_2013,peters_deep_2018,pennington_glove_2014}.
+Starting with the publication of the work from Collobert et al. \cite{collobert_natural_2011} in 2011, learning embeddings for linguistic units, such as words, sentences or paragraphs, is one of the hot topics in NLP and a plethora of approaches have been proposed \cite{bojanowski_enriching_2017,mikolov_distributed_2013,pennington_glove_2014,peters_deep_2018}.
  
 The majority of todays embedding models are based on deep learning models trained to perform some kind of language modeling task \cite{peters_semi-supervised_2017,peters_deep_2018,pinter_mimicking_2017}. 
 The most popular embedding model is the Word2Vec model introduced by Mikolov et al. \cite{mikolov_efficient_2013,mikolov_distributed_2013}. 

paper/wbi-eclef18.tex

@@ -33,15 +33,15 @@
 % an abbreviated paper title here
 \titlerunning{ICD-10 coding using multi-lingual embeddings and RNNs}
 
-\author{Jurica \v{S}eva\inst{1} \and
-Mario Sänger\inst{1} \and
-Ulf Leser\inst{1}} 
+\author{Jurica \v{S}eva \and
+Mario Sänger \and
+Ulf Leser} 
 
 % First names are abbreviated in the running head.
 % If there are more than two authors, 'et al.' is used.
 \authorrunning{\v{S}eva et al.}
 
-\institute{\inst{1}Humboldt-Universität zu Berlin, Knowledge Management in
+\institute{Humboldt-Universität zu Berlin, Knowledge Management in
 Bioinformatics, \\ Berlin, Germany\\
 \email{\{seva,saengema,leser\}@informatik.hu-berlin.de}}
 %