In this task, you are given a paper review. Based on the review, your job is to identify language and generate "en" if the review is in English or generate "es" if the review is in Spanish. Note that URLs in the text have been replaced with [Link].

In this paper, the authors propose a Bayesian variant of the skipgram model to learn word embeddings. There are two important variant compared to the original model. First, aligned sentences from multiple languages are used to train the model. Therefore, the context words of a given target word can be either from the same sentence, or from an aligned sentence in a different language. This allows to learn multilingual embedding. The second difference is that each word is represented by multiple vectors, one for each of its different senses. A latent variable z models which sense should be used, given the context.  Overall, I believe that the idea of using a probabilistic model to capture polysemy is an interesting idea. The model introduced in this paper is a nice generalization of the skipgram model in that direction. However, I found the paper a bit hard to follow. The formulation might probably be simplified (e.g. why not consider a target word w and a context c, where c is either in the source or target language. Since all factors are independent, this should not change the model much, and would make the presentation easier). The performance of all models reported in Table 2 & 3 seem pretty low.  Overall, I like the main idea of the paper, which is to represent word senses by latent variables in a probabilistic model. I feel that the method could be presented more clearly, which would make the paper much stronger. I also have some concerns regarding the experimental results.  Pros: Interesting extension of skipgram to capture polysemy. Cons: The paper is not clearly written. Results reported in the paper seems pretty low.
en

Me ha gustado mucho  Lo dejaría tal cual.
es

Este trabajo hace una presentación de trabajos relacionados con el control de acceso de personas a determinadas instalaciones. Describe algunas tecnologías que se pueden emplear para implementar este control. Sin embargo, se queda en una propuesta que trata de adaptar soluciones a un problema local. Falta más desarrollo de modelos y sustento teórico para presentar una solución original, que aporte al avance en esta área. OBSERVACIONES DE FORMA: 1) Indicar las referencias usadas en el texto con corchetes []. 2) Mejorar la redacción del texto, uso de conectivos, prenombres, acentos ortográficos, puntos, comas, etc. Por ejemplo: "El alumno, simplemente al acercar el móvil al libro, recibirá en su terminal la información Correspondiente al texto sin ninguna intervención."  3) El título: "1. Otras Secciones."

es