2 citations · 2 across the 3 of their papers we have counts for
8 papers
Data Selection Curriculum for Neural Machine Translation
Tasnim Mohiuddin, Philipp Koehn, Vishrav Chaudhary +3
Neural Machine Translation (NMT) models are typically trained on heterogeneous data that are concatenated and randomly shuffled. However, not all of the training data are equally u…
AUGVIC: Exploiting BiText Vicinity for Low-Resource NMT
Tasnim Mohiuddin, M Saiful Bari, Shafiq Joty
The success of Neural Machine Translation (NMT) largely depends on the availability of large bitext training corpora. Due to the lack of such large corpora in low-resource language…
Rethinking Coherence Modeling: Synthetic vs. Downstream Tasks
Tasnim Mohiuddin, Prathyusha Jwalapuram, Xiang Lin +1
Although coherence modeling has come a long way in developing novel models, their evaluation on downstream applications for which they are purportedly developed has largely been ne…
LNMap: Departures from Isomorphic Assumption in Bilingual Lexicon Induction Through Non-Linear Mapping in Latent Space
Tasnim Mohiuddin, M Saiful Bari, Shafiq Joty
Most of the successful and predominant methods for bilingual lexicon induction (BLI) are mapping-based, where a linear mapping function is learned with the assumption that the word…
A Unified Neural Coherence Model
Han Cheol Moon, Tasnim Mohiuddin, Shafiq Joty +1
Recently, neural approaches to coherence modeling have achieved state-of-the-art results in several evaluation tasks. However, we show that most of these models often fail on harde…
Revisiting Adversarial Autoencoder for Unsupervised Word Translation with Cycle Consistency and Improved Training
Tasnim Mohiuddin, Shafiq Joty
Adversarial training has shown impressive success in learning bilingual dictionary without any parallel data by mapping monolingual embeddings to a shared space. However, recent wo…