1 citations · 1 across the 3 of their papers we have counts for
3 papers
A Case Study on Context-Aware Neural Machine Translation with Multi-Task Learning
Ramakrishna Appicharla, Baban Gain, Santanu Pal +2
In document-level neural machine translation (DocNMT), multi-encoder approaches are common in encoding context and source sentences. Recent studies \cite{li-etal-2020-multi-encoder…
Reference Free Domain Adaptation for Translation of Noisy Questions with Question Specific Rewards
Baban Gain, Ramakrishna Appicharla, Soumya Chennabasavaraj +3
Community Question-Answering (CQA) portals serve as a valuable tool for helping users within an organization. However, making them accessible to non-English-speaking users continue…
A Case Study on Context Encoding in Multi-Encoder based Document-Level Neural Machine Translation
Ramakrishna Appicharla, Baban Gain, Santanu Pal +1
Recent studies have shown that the multi-encoder models are agnostic to the choice of context, and the context encoder generates noise which helps improve the models in terms of BL…