Neural Machine Translation (NMT) has seen tremendous growth in the last ten years since
the early 2000s and has already entered a mature phase. While considered the most widely …

Abstract Knowledge distillation (KD) is the preliminary step for training non-autoregressive
translation (NAT) models, which eases the training of NAT models at the cost of losing …

Recent work in Neural Machine Translation (NMT) has shown significant quality gains from
noised-beam decoding during back-translation, a method to generate synthetic parallel …

With the invention of deep learning concepts, Machine Translation (MT) migrated towards
Neural Machine Translation (NMT) architectures, eventually from Statistical Machine …

Lexically-constrained sequence decoding allows for explicit positive or negative phrase-
based constraints to be placed on target output strings in generation tasks such as machine …

Knowledge distillation (KD) is commonly used to construct synthetic data for training non-
autoregressive translation (NAT) models. However, there exists a discrepancy on low …

While back-translation is simple and effective in exploiting abundant monolingual corpora to
improve low-resource neural machine translation (NMT), the synthetic bilingual corpora …

It is generally believed that a translation memory (TM) should be beneficial for machine
translation tasks. Unfortunately, existing wisdom demonstrates the superiority of TM-based …

This thesis presents Bharathi Raja Asoka Chakravarthi's work on machine translation for
underresourced languages. As the internet becomes increasingly available to the whole …

Social media platforms have become an essential means of communication, but they also
serve as a breeding ground for hateful content. Detecting hate speech accurately is …