6 citations · 22 across the 25 of their papers we have counts for
27 papers
Computational Lesions in Multilingual Language Models Separate Shared and Language-specific Brain Alignment
Yang Cui, Jingyuan Sun, Yizheng Sun +8
How the brain supports language across different languages is a basic question in neuroscience and a useful test for multilingual artificial intelligence. Neuroimaging has identifi…
HealthcareNLP: where are we and what is next?
Lifeng Han, Paul Rayson, Suzan Verberne +2
This tutorial focused on Healthcare Domain Applications of NLP, what we have achieved around HealthcareNLP, and the challenges that lie ahead for the future. Existing reviews in th…
Arg-LLaDA: Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement
Hao Li, Yizheng Sun, Viktor Schlegel +3
Argument summarization aims to generate concise, structured representations of complex, multi-perspective debates. While recent work has advanced the identification and clustering…
Large Language Models in Argument Mining: A Survey
Hao Li, Viktor Schlegel, Yizheng Sun +2
Large Language Models (LLMs) have fundamentally reshaped Argument Mining (AM), shifting it from a pipeline of supervised, task-specific classifiers to a spectrum of prompt-driven,…
BRIDGE: Bootstrapping Text to Control Time-Series Generation via Multi-Agent Iterative Optimization and Diffusion Modeling
Hao Li, Yu-Hao Huang, Chang Xu +5
Time-series Generation (TSG) is a prominent research area with broad applications in simulations, data augmentation, and counterfactual analysis. While existing methods have shown…
MaLei at the PLABA Track of TREC 2024: RoBERTa for Term Replacement -- LLaMA3.1 and GPT-4o for Complete Abstract Adaptation
Zhidong Ling, Zihao Li, Pablo Romero +2
This report is the system description of the MaLei team (Manchester and Leiden) for the shared task Plain Language Adaptation of Biomedical Abstracts (PLABA) 2024 (we had an earlie…
TriG-NER: Triplet-Grid Framework for Discontinuous Named Entity Recognition
Rina Carines Cabral, Soyeon Caren Han, Areej Alhassan +3
Discontinuous Named Entity Recognition (DNER) presents a challenging problem where entities may be scattered across multiple non-adjacent tokens, making traditional sequence labell…
CAST: Corpus-Aware Self-similarity Enhanced Topic modelling
Yanan Ma, Chenghao Xiao, Chenhan Yuan +4
Topic modelling is a pivotal unsupervised machine learning technique for extracting valuable insights from large document collections. Existing neural topic modelling methods often…
DeIDClinic: A Risk-Aware Pseudonymization Framework for Clinical Text De-identification and Re-identification Risk Assessment
Angel Paul, Dhivin Shaji, Lifeng Han +3
The increasing availability of sensitive textual data has created an urgent need for robust de-identification methods that enable compliant data sharing while preserving downstream…
Large Language Models for Biomedical Text Simplification: Promising But Not There Yet
Zihao Li, Samuel Belkadi, Nicolo Micheletti +3
In this system report, we describe the models and methods we used for our participation in the PLABA2023 task on biomedical abstract simplification, part of the TAC 2023 tracks. Th…
Synthetic4Health: Generating Annotated Synthetic Clinical Letters
Libo Ren, Samuel Belkadi, Lifeng Han +2
Since clinical letters contain sensitive information, clinical-related datasets can not be widely applied in model training, medical research, and teaching. This work aims to gener…
INSIGHTBUDDY-AI: Medication Extraction and Entity Linking using Large Language Models and Ensemble Learning
Pablo Romero, Lifeng Han, Goran Nenadic
Medication Extraction and Mining play an important role in healthcare NLP research due to its practical applications in hospital settings, such as their mapping into standard clini…
AutoLLM-CARD: Towards a Description and Landscape of Large Language Models
Shengwei Tian, Lifeng Han, Goran Nenadic
With the rapid growth of the Natural Language Processing (NLP) field, a vast variety of Large Language Models (LLMs) continue to emerge for diverse NLP tasks. As more papers are pu…
Extract-and-Abstract: Unifying Extractive and Abstractive Summarization within Single Encoder-Decoder Framework
Yuping Wu, Hao Li, Goran Nenadic +1
Extract-then-Abstract is a naturally coherent paradigm to conduct abstractive summarization with the help of salient information identified by the extractive model. Previous works…
Generating Synthetic Free-text Medical Records with Low Re-identification Risk using Masked Language Modeling
Samuel Belkadi, Libo Ren, Nicolo Micheletti +2
The vast amount of available medical records has the potential to improve healthcare and biomedical research. However, privacy restrictions make these data accessible for internal…
Investigating a Benchmark for Training-set free Evaluation of Linguistic Capabilities in Machine Reading Comprehension
Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro
Performance of NLP systems is typically evaluated by collecting a large-scale dataset by means of crowd-sourcing to train a data-driven model and evaluate it on a held-out portion…
A Comparative Study on Automatic Coding of Medical Letters with Explainability
Jamie Glen, Lifeng Han, Paul Rayson +1
This study aims to explore the implementation of Natural Language Processing (NLP) and machine learning (ML) techniques to automate the coding of medical letters with visualised ex…
Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluation
Hao Li, Yuping Wu, Viktor Schlegel +8
With the recent advances of large language models (LLMs), it is no longer infeasible to build an automated debate system that helps people to synthesise persuasive arguments. Previ…
CANTONMT: Investigating Back-Translation and Model-Switch Mechanisms for Cantonese-English Neural Machine Translation
Kung Yin Hong, Lifeng Han, Riza Batista-Navarro +1
This paper investigates the development and evaluation of machine translation models from Cantonese to English, where we propose a novel approach to tackle low-resource language tr…
The Multi-Range Theory of Translation Quality Measurement: MQM scoring models and Statistical Quality Control
Arle Lommel, Serge Gladkoff, Alan Melby +10
The year 2024 marks the 10th anniversary of the Multidimensional Quality Metrics (MQM) framework for analytic translation quality evaluation. The MQM error typology has been widely…
Exploration of Masked and Causal Language Modelling for Text Generation
Nicolo Micheletti, Samuel Belkadi, Lifeng Han +1
Large Language Models (LLMs) have revolutionised the field of Natural Language Processing (NLP) and have achieved state-of-the-art performance in practically every task in this fie…
CantonMT: Cantonese to English NMT Platform with Fine-Tuned Models Using Synthetic Back-Translation Data
Kung Yin Hong, Lifeng Han, Riza Batista-Navarro +1
Neural Machine Translation (NMT) for low-resource languages is still a challenging task in front of NLP researchers. In this work, we deploy a standard data augmentation methodolog…
Neural Machine Translation of Clinical Text: An Empirical Investigation into Multilingual Pre-Trained Language Models and Transfer-Learning
Lifeng Han, Serge Gladkoff, Gleb Erofeev +3
We conduct investigations on clinical text machine translation by examining multilingual neural network models using deep learning such as Transformer based structures. Furthermore…
Generating Medical Prescriptions with Conditional Transformer
Samuel Belkadi, Nicolo Micheletti, Lifeng Han +2
Access to real-world medication prescriptions is essential for medical research and healthcare quality improvement. However, access to real medication prescriptions is often limite…