In our lab meeting tomorrow, Anahita will present another paper from ICLR 2018 about Neural Phrase-based Machine Translation. Here is the title and abstract of the paper:
Title: Towards Neural Phrase-based Machine Translation
Abstract: In this paper, we present Neural Phrase-based Machine Translation (NPMT). Our method explicitly models the phrase structures in output sequences using Sleep- WAke Networks (SWAN), a recently proposed segmentation-based sequence modeling method. To mitigate the monotonic alignment requirement of SWAN, we introduce a new layer to perform (soft) local reordering of input sequences. Different from existing neural machine translation (NMT) approaches, NPMT does not use attention-based decoding mechanisms. Instead, it directly outputs phrases in a sequential order and can decode in linear time. Our experiments show that NPMT achieves superior performances on IWSLT 2014 German-English/English- German and IWSLT 2015 English-Vietnamese machine translation tasks compared with strong NMT baselines. We also observe that our method produces meaningful phrases in output languages.
The paper can be found here: https://openreview.net/forum?id=HktJec1RZ
Wednesday, June 13th, 10-11 AM, Location: TASC1 9408.