From Credit Assignment to Entropy Regularization: Two New Algorithms for Neural Sequence Prediction
Greedy Search with Probabilistic N-gram Matching for Neural Machine Translation
Differentiable Scheduled Sampling for Credit Assignment
A Continuous Relaxation of Beam Search for End-to-End Training of Neural Sequence Models
Token-level and sequence-level loss smoothing for RNN language models
Policy Optimization as Wasserstein Gradient Flows