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A comparative study of pre|trained language models for named ...


A comparative study of pre-trained language models for named ...

In this study we fine-tuned pre-trained language models to support the NER task on clinical trial eligibility criteria.

(PDF) A comparative study of pre-trained language models for ...

Named entity recognition (NER) is a fundamental and necessary step to process and standardize the unstructured text in clinical trials using Natural Language ...

A Comparative Study of Pretrained Language Models for Long ...

Discussion: Our pre-trained language models provide the bedrock for clinical NLP using long texts. We have made our source code available at ...

A comparative study of pre-trained language models for named ...

A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora · Jianfu Li, Qiang ...

comparative study of pretrained language models for long clinical text

These domain-enriched models, for example, BioBERT15 pretrained on biomedical publications and ClinicalBERT16 pretrained on clinical narratives, ...

[2204.04980] A Comparative Study of Pre-trained Encoders for Low ...

Pre-trained language models (PLM) are effective components of few-shot named entity recognition (NER) approaches when augmented with continued ...

(PDF) A Comparative Study of Pretrained Language Models for ...

Clinical-Longformer and Clinical-BigBird, which are pre-trained on a large-scale clinical corpus. We evaluate both language models using 10 ...

A Comparative Study of Using Pre-trained Language Models for ...

As recent popular methods for text classification tasks, pre-trained language model-based methods are at the forefront of natural language ...

A comparative study of pretrained language models for long clinical ...

DISCUSSION: Our pretrained language models provide the bedrock for clinical NLP using long texts. We have made our source code available at ...

[PDF] A Comparative Study of Using Pre-trained Language Models ...

It is proved that using a basic linear downstream structure outperforms complex ones such as CNN and BiLSTM and further fine-tuning a pre-trained language ...

A comparative study of using pre-trained language models for toxic ...

In this work, we study how to best make use of pre-trained language model-based methods for toxic comment classification and the performances of different pre-.

Table 4 The strict and relaxed overall performance on the test sets of ...

From: A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora. Models.

Pre-Trained Language Models and Their Applications - ScienceDirect

The NLP community has witnessed a surge of research interest in improving pre-trained models. This article presents a comprehensive review of representative ...

A Comparative Study on Bias Metrics for Pre-trained Language ...

We survey the literature on fairness metrics for pre-trained language models and experimentally evaluate compatibility, including both biases in language ...

A comparative study of pretrained language models for long clinical ...

Clinical knowledge-enriched transformer models (eg, ClinicalBERT) have state-of-the-art results on clinical natural language processing (NLP) tasks.

A comparative study of pre-trained language models for named ...

RESEARCH. A comparative study of pre-trained language models for named entity recognition in clinical trial eligibility criteria from multiple corpora. Jianfu ...

Comparison of pre-trained language models in terms of carbon ...

The ConvBERTurk mC4 (uncased) model is also the best-performing second language model. As a result of this study, we have provided a deeper understanding of the ...

Comparative Analysis of Large Language Models in Chinese ... - MDPI

The emergence of large language models (LLMs) has provided robust support for application tasks across various domains, such as name entity recognition ...

Pretrained Language Model in Continual Learning: A Comparative ...

Comment: This paper presents a comparison and analysis of continual learning methods for pretrained language models. The authors categorise ...

A comparative study of pretrained language models for long clinical ...

Abstract ObjectiveClinical knowledge-enriched transformer models (eg, ClinicalBERT) have state-of-the-art results on clinical natural language processing ...