Julia Ive

Julia Ive

Imperial College London

H-index: 11

Europe-United Kingdom

About Julia Ive

Julia Ive, With an exceptional h-index of 11 and a recent h-index of 10 (since 2020), a distinguished researcher at Imperial College London,

His recent articles reflect a diverse array of research interests and contributions to the field:

Safe Training with Sensitive In-domain Data: Leveraging Data Fragmentation To Mitigate Linkage Attacks

Using Large Language Models (LLMs) to Extract Evidence from Pre-Annotated Social Media Data

Clinically meaningful timeline summarisation in social media for mental health monitoring

Systems and methods for generating a text report and simulating health care journey

Source Code is a Graph, Not a Sequence: A Cross-Lingual Perspective on Code Clone Detection

Embracing the uncertainty in human–machine collaboration to support clinical decision-making for mental health conditions

Revisiting contextual toxicity detection in conversations

Controlled text generation using T5 based encoder-decoder soft prompt tuning and analysis of the utility of generated text in AI

Julia Ive Information

University

Position

___

Citations(all)

501

Citations(since 2020)

480

Cited By

132

hIndex(all)

11

hIndex(since 2020)

10

i10Index(all)

13

i10Index(since 2020)

11

Email

University Profile Page

Google Scholar

Top articles of Julia Ive

Safe Training with Sensitive In-domain Data: Leveraging Data Fragmentation To Mitigate Linkage Attacks

arXiv preprint arXiv:2404.19486

2024/4/30

Julia Ive
Julia Ive

H-Index: 5

Using Large Language Models (LLMs) to Extract Evidence from Pre-Annotated Social Media Data

2024/3

Julia Ive
Julia Ive

H-Index: 5

Clinically meaningful timeline summarisation in social media for mental health monitoring

arXiv preprint arXiv:2401.16240

2024/1/29

Julia Ive
Julia Ive

H-Index: 5

Maria Liakata
Maria Liakata

H-Index: 30

Systems and methods for generating a text report and simulating health care journey

2024/1/25

Source Code is a Graph, Not a Sequence: A Cross-Lingual Perspective on Code Clone Detection

arXiv preprint arXiv:2312.16488

2023/12/27

Julia Ive
Julia Ive

H-Index: 5

Embracing the uncertainty in human–machine collaboration to support clinical decision-making for mental health conditions

Frontiers in Digital Health

2023/9/5

Julia Ive
Julia Ive

H-Index: 5

Revisiting contextual toxicity detection in conversations

ACM Journal of Data and Information Quality

2022/12/28

Julia Ive
Julia Ive

H-Index: 5

Controlled text generation using T5 based encoder-decoder soft prompt tuning and analysis of the utility of generated text in AI

arXiv preprint arXiv:2212.02924

2022/12/6

Julia Ive
Julia Ive

H-Index: 5

Unsupervised numerical reasoning to extract phenotypes from clinical text by leveraging external knowledge

2022/11/29

Phenotyping in clinical text with unsupervised numerical reasoning for patient stratification

Experimental Biology and Medicine

2022/11

Medical Scientific Table-to-Text Generation with Synthetic Data under Data Sparsity Constraint

2022/10/20

Leveraging the potential of synthetic text for AI in mental healthcare

Frontiers in Digital Health

2022/10

Julia Ive
Julia Ive

H-Index: 5

SURF: Semantic-level Unsupervised Reward Function for Machine Translation

2022/7

Julia Ive
Julia Ive

H-Index: 5

Predicting moments of mood changes overtime from imbalanced social media data

2022/7

Julia Ive
Julia Ive

H-Index: 5

Findings of the Third Workshop on Automatic Simultaneous Translation

2022/7

Modeling Disagreement in Automatic Data Labelling for Semi-Supervised Learning in Clinical Natural Language Processing

arXiv preprint arXiv:2205.14761

2022/5/29

Nabeel Seedat
Nabeel Seedat

H-Index: 3

Julia Ive
Julia Ive

H-Index: 5

Natural Language Processing: A Machine Learning Perspective by Yue Zhang and Zhiyang Teng

2022/4/4

Julia Ive
Julia Ive

H-Index: 5

Clinical utility of automatic phenotype annotation in unstructured clinical notes: intensive care unit use

BMJ Health & Care Informatics

2022

Self-supervised detection of contextual synonyms in a multi-class setting: Phenotype annotation use case

2021/11

Clinical utility of the automatic phenotype annotation in unstructured clinical notes: ICU use cases

arXiv preprint arXiv:2107.11665

2021/7/24

See List of Professors in Julia Ive University(Imperial College London)

Co-Authors

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