1 citations · 1 across the 4 of their papers we have counts for
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Information Redundancy and Biases in Public Document Information Extraction Benchmarks
Seif Laatiri, Pirashanth Ratnamogan, Joel Tang +3
Advances in the Visually-rich Document Understanding (VrDU) field and particularly the Key-Information Extraction (KIE) task are marked with the emergence of efficient Transformer-…
Information Extraction from Documents: Question Answering vs Token Classification in real-world setups
Laurent Lam, Pirashanth Ratnamogan, Joël Tang +2
Research in Document Intelligence and especially in Document Key Information Extraction (DocKIE) has been mainly solved as Token Classification problem. Recent breakthroughs in bot…
Robust Domain Adaptation for Pre-trained Multilingual Neural Machine Translation Models
Mathieu Grosso, Pirashanth Ratnamogan, Alexis Mathey +2
Recent literature has demonstrated the potential of multilingual Neural Machine Translation (mNMT) models. However, the most efficient models are not well suited to specialized ind…
Building a Multi-domain Neural Machine Translation Model using Knowledge Distillation
Idriss Mghabbar, Pirashanth Ratnamogan
Lack of specialized data makes building a multi-domain neural machine translation tool challenging. Although emerging literature dealing with low resource languages starts to show…