Curriculum Learning And Minibatch Bucketing In Neural Machine Translation | Awesome LLM Papers Add your paper to Awesome LLM Papers

Awesome LLM Papers

A continuously updated collection of research papers on LLMs.

Stay Updated

Contact Sean Moran about this survey or website. Made with Jekyll and Hyde.

Curriculum Learning And Minibatch Bucketing In Neural Machine Translation

Tom Kocmi, Ondrej Bojar . RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning 2017 – 97 citations

[Paper]   Search on Google Scholar   Search on Semantic Scholar
Compositional Generalization Interdisciplinary Approaches Neural Machine Translation Training Techniques Variational Autoencoders

We examine the effects of particular orderings of sentence pairs on the on-line training of neural machine translation (NMT). We focus on two types of such orderings: (1) ensuring that each minibatch contains sentences similar in some aspect and (2) gradual inclusion of some sentence types as the training progresses (so called “curriculum learning”). In our English-to-Czech experiments, the internal homogeneity of minibatches has no effect on the training but some of our “curricula” achieve a small improvement over the baseline.

Similar Work