Positive good job, good paper, future work, theoretical analysis, adversarial examples, optimization problem, variational inference, interesting paper, significant improvement, active learning	Reject, Positive significant improvement, more parameters, interesting approach, deep learning architectures, learning architectures, sequence prediction, good performance, node classification, weight decay, empirical risk	Review that was Contrary to Acceptance Decision aspect of the paper, inception distance, scale datasets, convolutional features, formulation of the problem, shannon divergence, single object, graph generation, value functions, random walks

Accept, Positive training time, future work, experimental results, theoretical analysis, deep learning, adversarial examples, neural network, optimization problem, good paper, network architecture		Accept, Negative certain conditions, number of model, natural language, convolutional features, image translation, serious issues, scale data, optimization method, mean discrepancy, maximum mean discrepancy
Review that in Line With Acceptance Decision previous work, network architecture, loss function, neural network, reinforcement learning, experimental section, main text, latent space, training data, main idea		Negative current form, other methods, contribution of the paper, main contribution, experimental evaluation, baseline methods, other words, nearest neighbor, time series, shot learning
	Reject, Negative contribution of the paper, current state, current form, experimental evaluation, other methods, prior work, international conference, experimental setup, technical contribution, ground truth