Maximilian Mozes

About Maximilian Mozes

Maximilian Mozes, With an exceptional h-index of 11 and a recent h-index of 10 (since 2020), a distinguished researcher at University College London, specializes in the field of Natural Language Processing, Machine Learning.

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

Here's a Free Lunch: Sanitizing Backdoored Models with Model Merge

Use of llms for illicit purposes: Threats, prevention measures, and vulnerabilities

Challenges and applications of large language models

Large language models respond to influence like humans

Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP 2023)

Susceptibility to influence of large language models

Towards agile text classifiers for everyone

Gradient-based automated iterative recovery for parameter-efficient tuning

Maximilian Mozes Information

University

Position

___

Citations(all)

615

Citations(since 2020)

602

Cited By

133

hIndex(all)

11

hIndex(since 2020)

10

i10Index(all)

12

i10Index(since 2020)

12

Email

University Profile Page

Google Scholar

Maximilian Mozes Skills & Research Interests

Natural Language Processing

Machine Learning

Top articles of Maximilian Mozes

Here's a Free Lunch: Sanitizing Backdoored Models with Model Merge

arXiv preprint arXiv:2402.19334

2024/2/29

Use of llms for illicit purposes: Threats, prevention measures, and vulnerabilities

arXiv preprint arXiv:2308.12833

2023/8/24

Challenges and applications of large language models

2023/7/19

Large language models respond to influence like humans

2023/7

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Augustine Mavor-Parker
Augustine Mavor-Parker

H-Index: 1

Proceedings of the 8th Workshop on Representation Learning for NLP (RepL4NLP 2023)

2023/7

Susceptibility to influence of large language models

arXiv preprint arXiv:2303.06074

2023/3/10

Towards agile text classifiers for everyone

arXiv preprint arXiv:2302.06541

2023/2/13

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Gradient-based automated iterative recovery for parameter-efficient tuning

arXiv preprint arXiv:2302.06598

2023/2/13

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Textwash--automated open-source text anonymisation

arXiv preprint arXiv:2208.13081

2022/8/27

Toby Davies
Toby Davies

H-Index: 11

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Identifying Human Strategies for Generating Word-Level Adversarial Examples

arXiv preprint arXiv:2210.11598

2022/10/20

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Lewis D Griffin
Lewis D Griffin

H-Index: 23

A repeated-measures study on emotional responses after a year in the pandemic

Scientific reports

2021/11/30

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Isabelle Van Der Vegt
Isabelle Van Der Vegt

H-Index: 6

The grievance dictionary: Understanding threatening language use

Behavior Research Methods

2021/3/23

Scene graph generation for better image captioning?

arXiv preprint arXiv:2109.11398

2021/9/23

Contrasting human-and machine-generated word-level adversarial examples for text classification

EMNLP 2021

2021/9/9

Worry, coping and resignation--A repeated-measures study on emotional responses after a year in the pandemic

2021/7/7

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Online influence, offline violence: language use on YouTube surrounding the ‘Unite the Right’rally

Journal of Computational Social Science

2021/5

No intruder, no validity: Evaluation criteria for privacy-preserving text anonymization

arXiv preprint arXiv:2103.09263

2021/3/16

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Frequency-guided word substitutions for detecting textual adversarial examples

EACL 2021

2020/4/13

Maximilian Mozes
Maximilian Mozes

H-Index: 5

Lewis D Griffin
Lewis D Griffin

H-Index: 23

Measuring emotions in the covid-19 real world worry dataset

NLP COVID-19 Workshop, ACL 2020

2020/4/8

Isabelle Van Der Vegt
Isabelle Van Der Vegt

H-Index: 6

Maximilian Mozes
Maximilian Mozes

H-Index: 5

See List of Professors in Maximilian Mozes University(University College London)

Co-Authors

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