1 citations · 2 across the 3 of their papers we have counts for
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Learning Section Weights for Multi-Label Document Classification
Maziar Moradi Fard, Paula Sorrolla Bayod, Kiomars Motarjem +3
Multi-label document classification is a traditional task in NLP. Compared to single-label classification, each document can be assigned multiple classes. This problem is crucially…
Stress Testing BERT Anaphora Resolution Models for Reaction Extraction in Chemical Patents
Chieling Yueh, Evangelos Kanoulas, Bruno Martins +2
The high volume of published chemical patents and the importance of a timely acquisition of their information gives rise to automating information extraction from chemical patents.…
Word Embeddings for Chemical Patent Natural Language Processing
Camilo Thorne, Saber Akhondi
We evaluate chemical patent word embeddings against known biomedical embeddings and show that they outperform the latter extrinsically and intrinsically. We also show that using co…
Improving Chemical Named Entity Recognition in Patents with Contextualized Word Embeddings
Zenan Zhai, Dat Quoc Nguyen, Saber A. Akhondi +5
Chemical patents are an important resource for chemical information. However, few chemical Named Entity Recognition (NER) systems have been evaluated on patent documents, due in pa…