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08/07/2023
MedMine: Examining Pre-trained Language Models on Medication Mining
Automatic medication mining from clinical and biomedical text has become...
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07/31/2023
Predicting Perfect Quality Segments in MT Output with Fine-Tuned OpenAI LLM: Is it possible to capture editing distance patterns from historical data?
Translation Quality Estimation (TQE) is an important step before deployi...
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07/05/2023
PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records
This paper describes PULSAR, our system submission at the ImageClef 2023...
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06/05/2023
PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language Models
Medical progress notes play a crucial role in documenting a patient's ho...
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05/25/2023
Do You Hear The People Sing? Key Point Analysis via Iterative Clustering and Abstractive Summarisation
Argument summarisation is a promising but currently under-explored field...
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03/08/2023
Student's t-Distribution: On Measuring the Inter-Rater Reliability When the Observations are Scarce
In natural language processing (NLP) we always rely on human judgement a...
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01/08/2023
Topic Modelling of Swedish Newspaper Articles about Coronavirus: a Case Study using Latent Dirichlet Allocation Method
Topic Modelling (TM) is from the research branches of natural language u...
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10/23/2022
On Cross-Domain Pre-Trained Language Models for Clinical Text Mining: How Do They Perform on Data-Constrained Fine-Tuning?
Pre-trained language models (PLMs) have been deployed in many natural la...
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10/12/2022
Using Massive Multilingual Pre-Trained Language Models Towards Real Zero-Shot Neural Machine Translation in Clinical Domain
Massively multilingual pre-trained language models (MMPLMs) are develope...
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10/08/2022
EDU-level Extractive Summarization with Varying Summary Lengths
Extractive models usually formulate text summarization as extracting top...
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09/15/2022
Examining Large Pre-Trained Language Models for Machine Translation: What You Don't Know About It
Pre-trained language models (PLMs) often take advantage of the monolingu...
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12/07/2020
Semantics Altering Modifications for Evaluating Comprehension in Machine Reading
Advances in NLP have yielded impressive results for the task of machine ...
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10/16/2020
An efficient representation of chronological events in medical texts
In this work we addressed the problem of capturing sequential informatio...
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05/29/2020
Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models
Recent years have seen a growing number of publications that analyse Nat...
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05/24/2020
MASK: A flexible framework to facilitate de-identification of clinical texts
Medical health records and clinical summaries contain a vast amount of i...
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03/10/2020
A Framework for Evaluation of Machine Reading Comprehension Gold Standards
Machine Reading Comprehension (MRC) is the task of answering a question ...
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09/23/2019
GNTeam at 2018 n2c2: Feature-augmented BiLSTM-CRF for drug-related entity recognition in hospital discharge summaries
Monitoring the administration of drugs and adverse drug reactions are ke...
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05/28/2019
Extracting adverse drug reactions and their context using sequence labelling ensembles in TAC2017
Adverse drug reactions (ADRs) are unwanted or harmful effects experience...
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05/22/2019
From web crawled text to project descriptions: automatic summarizing of social innovation projects
In the past decade, social innovation projects have gained the attention...
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02/26/2019
A framework for information extraction from tables in biomedical literature
The scientific literature is growing exponentially, and professionals ar...
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11/22/2018
Creating a contemporary corpus of similes in Serbian by using natural language processing
Simile is a figure of speech that compares two things through the use of...
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05/20/2016
