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].
One example is below.
Q: Este articulo no es un articulo de investigacion, ya que solo muestra como programar un robot mediante la herramienta de logica difusa. Este tema ya ha sido propuesto como solucion en navegacion de robots.
A: es
Rationale: This review is written in spanish. Hence, the label is 'es'.
Q: In this interesting paper the authors explore the idea of using an ensemble of multiple discriminators in generative adversarial network training. This comes with a number of benefits, mainly being able to use less powerful discriminators which may provide better training signal to the generator early on in training when strong discriminators might overpower the generator. My main comment is about the way the paper is presented. The caption of Figure 1. and Section 3.1 suggests using the best discriminator by taking the maximum over the performance of individual ensemble members. This does not appear to be the best thing to do because we are just bound to get a training signal that is stricter than any of the individual members of the ensemble. Then the rest of the paper explores relaxing the maximum and considers various averaging techniques to obtain a 'soft-discriminator'. To me, this idea is far more appealing, and the results seem to support this, too. Skimming the paper it seems as if the authors mainly advocated always using the strongest discriminator, evidenced by my premature pre-review question earlier. Overall, I think this paper is a valuable contribution, and I think the idea of multiple discriminators is an interesting direction to pursue.
A:
en