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].

Example Input: this proposes a multi-view learning approach for learning representations for acoustic sequences. they investigate the use of bidirectional LSTM with contrastive losses. experiments show improvement over the previous work.  although I have no expertise in speech processing, I am in favor of accepting this paper because of following contributions: - investigating the use of fairly known architecture on a new domain. - providing novel objectives specific to the domain - setting up new benchmarks designed for evaluating multi-view models  I hope authors open-source their implementation so that people can replicate results, compare their work, and improve on this work.
Example Output: en

Example Input: El  trabajo "Liderazgo en adopción de TI en PYMEs ¿Sólo el involucramiento del propietario importa?" explora a través de la metodología IA la relación entre involucramiento del propietario y el éxito de la TI en PYME. Si bien es un buen trabajo, el texto puede ser mejorado en algunos aspectos de forma y fondo: 1.	Los autores deben declarar el objetivo del estudio para facilitar la lectura del trabajo. 2.	Lamentablemente los autores cometen un error importante al colocar a  D&M como modelo de aceptación a nivel individual ("Otros modelos de aceptación a nivel individual incluyen: el modelo de DeLone y McLean (D&M) [5]"). De hecho, a partir de ese error la redacción del texto confunde dimensiones del éxito del uso de sistemas de información (el modelo D&M) con modelos de adopción de tecnologías de información (TAM y sucesores). Los autores deben revisar D&M y ver las implicaciones para su trabajo de la correcta interpretación de este modelo. 3.	Asociado a lo anterior, ¿que entienden los autores por éxito del uso de sistemas de información? deben explicarlo, ¿los beneficios individuales y los beneficios organizaciones son parte de ellos?,  ¿es posible que otras dimensiones del éxito del uso de sistemas de información, como la calidad de la información y la calidad de servicio de la función informática, sean variables importantes para explorar en los dos proyectos estudiados?
Example Output: es

Example Input: The paper provides a first study of customized precision hardware for large convolutional networks, namely alexnet, vgg and googlenet. It shows that it is possible to achieve larger speed-ups using floating-point precision (up to 7x) when using fewer bits, and better than using fixed-point representations.   The paper also explores predicting custom floating-point precision parameters directly from the neural network activations, avoiding exhaustive search, but i could not follow this part. Only the activations of the last layer are evaluated, but on what data ? On all the validation set ? Why would this be faster than computing the classification accuracy ?  The results should be useful for hardware manufacturers, but with a catch. All popular convolutional networks now use batch normalization, while none of the evaluated ones do. It may well be that the conclusions of this study will be completely different on batch normalization networks, and fixed-point representations are best there, but that remains to be seen. It seems like something worth exploring.  Overall there is not a great deal of novelty other than being a useful study on numerical precision trade-offs at neural network test time. Training time is also something of interest. There are a lot more researchers trying to train new networks fast than trying to evaluate old ones fast.   I am also no expert in digital logic design, but my educated guess is that this paper is marginally below the acceptance threshold.
Example Output:
en