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20192024
most citedUsing Similarity Measures to Select Pretraining Data for NER

18 citations · 39 across the 10 of their papers we have counts for

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cs.CL2024

Can AI Extract Antecedent Factors of Human Trust in AI? An Application of Information Extraction for Scientific Literature in Behavioural and Computer Sciences

Melanie McGrath, Harrison Bailey, Necva Bölücü +3

Information extraction from the scientific literature is one of the main techniques to transform unstructured knowledge hidden in the text into structured data which can then be us…

cs.CL2024

A Critical Look at Meta-evaluating Summarisation Evaluation Metrics

Xiang Dai, Sarvnaz Karimi, Biaoyan Fang

Effective summarisation evaluation metrics enable researchers and practitioners to compare different summarisation systems efficiently. Estimating the effectiveness of an automatic…

cs.CL2024

MultiADE: A Multi-domain Benchmark for Adverse Drug Event Extraction

Xiang Dai, Sarvnaz Karimi, Abeed Sarker +2

Active adverse event surveillance monitors Adverse Drug Events (ADE) from different data sources, such as electronic health records, medical literature, social media and search eng…

cs.CL2024

Identifying Health Risks from Family History: A Survey of Natural Language Processing Techniques

Xiang Dai, Sarvnaz Karimi, Nathan O'Callaghan

Electronic health records include information on patients' status and medical history, which could cover the history of diseases and disorders that could be hereditary. One importa…

cs.CL20221 cited

Detecting Entities in the Astrophysics Literature: A Comparison of Word-based and Span-based Entity Recognition Methods

Xiang Dai, Sarvnaz Karimi

Information Extraction from scientific literature can be challenging due to the highly specialised nature of such text. We describe our entity recognition methods developed as part…

cs.CL202217 cited

An Exploration of Hierarchical Attention Transformers for Efficient Long Document Classification

Ilias Chalkidis, Xiang Dai, Manos Fergadiotis +2

Non-hierarchical sparse attention Transformer-based models, such as Longformer and Big Bird, are popular approaches to working with long documents. There are clear benefits to thes…