4 citations · 4 across the 4 of their papers we have counts for
4 papers
A LayoutLMv3-Based Model for Enhanced Relation Extraction in Visually-Rich Documents
Wiam Adnan, Joel Tang, Yassine Bel Khayat Zouggari +3
Document Understanding is an evolving field in Natural Language Processing (NLP). In particular, visual and spatial features are essential in addition to the raw text itself and he…
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…
Reducing Hallucinations in Neural Machine Translation with Feature Attribution
Joël Tang, Marina Fomicheva, Lucia Specia
Neural conditional language generation models achieve the state-of-the-art in Neural Machine Translation (NMT) but are highly dependent on the quality of parallel training dataset.…