Maximilian Mozes

Maximilian Mozes

University College London

H-index: 11

Europe-United Kingdom

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

Susceptibility to influence of large language models

Towards agile text classifiers for everyone

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

Gradient-based automated iterative recovery for parameter-efficient tuning

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)

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

University College London

Google Scholar

View Google Scholar Profile

Maximilian Mozes Skills & Research Interests

Natural Language Processing

Machine Learning

Top articles of Maximilian Mozes

Title

Journal

Author(s)

Publication Date

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

arXiv preprint arXiv:2402.19334

Ansh Arora

Xuanli He

Maximilian Mozes

Srinibas Swain

Mark Dras

...

2024/2/29

Susceptibility to influence of large language models

arXiv preprint arXiv:2303.06074

Lewis D Griffin

Bennett Kleinberg

Maximilian Mozes

Kimberly T Mai

Maria Vau

...

2023/3/10

Towards agile text classifiers for everyone

arXiv preprint arXiv:2302.06541

Maximilian Mozes

Jessica Hoffmann

Katrin Tomanek

Muhamed Kouate

Nithum Thain

...

2023/2/13

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

arXiv preprint arXiv:2308.12833

Maximilian Mozes

Xuanli He

Bennett Kleinberg

Lewis D Griffin

2023/8/24

Gradient-based automated iterative recovery for parameter-efficient tuning

arXiv preprint arXiv:2302.06598

Maximilian Mozes

Tolga Bolukbasi

Ann Yuan

Frederick Liu

Nithum Thain

...

2023/2/13

Challenges and applications of large language models

Jean Kaddour

Joshua Harris

Maximilian Mozes

Herbie Bradley

Roberta Raileanu

...

2023/7/19

Large language models respond to influence like humans

Lewis Griffin

Bennett Kleinberg

Maximilian Mozes

Kimberly Mai

Maria Do Mar Vau

...

2023/7

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

Burcu Can

Maximilian Mozes

Samuel Cahyawijaya

Naomi Saphra

Nora Kassner

...

2023/7

Identifying Human Strategies for Generating Word-Level Adversarial Examples

arXiv preprint arXiv:2210.11598

Maximilian Mozes

Bennett Kleinberg

Lewis D Griffin

2022/10/20

Textwash--automated open-source text anonymisation

arXiv preprint arXiv:2208.13081

Bennett Kleinberg

Toby Davies

Maximilian Mozes

2022/8/27

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

Scientific reports

Maximilian Mozes

Isabelle van der Vegt

Bennett Kleinberg

2021/11/30

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

arXiv preprint arXiv:2103.09263

Maximilian Mozes

Bennett Kleinberg

2021/3/16

The grievance dictionary: Understanding threatening language use

Behavior Research Methods

Isabelle van der Vegt

Maximilian Mozes

Bennett Kleinberg

Paul Gill

2021/3/23

Scene graph generation for better image captioning?

arXiv preprint arXiv:2109.11398

Maximilian Mozes

Martin Schmitt

Vladimir Golkov

Hinrich Schütze

Daniel Cremers

2021/9/23

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

EMNLP 2021

Maximilian Mozes

Max Bartolo

Pontus Stenetorp

Bennett Kleinberg

Lewis D Griffin

2021/9/9

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

Maximilian Mozes

Vegt Ivd

Bennett Kleinberg

2021/7/7

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

Journal of Computational Social Science

Isabelle van der Vegt

Maximilian Mozes

Paul Gill

Bennett Kleinberg

2021/5

Frequency-guided word substitutions for detecting textual adversarial examples

EACL 2021

Maximilian Mozes

Pontus Stenetorp

Bennett Kleinberg

Lewis D Griffin

2020/4/13

Measuring emotions in the covid-19 real world worry dataset

NLP COVID-19 Workshop, ACL 2020

Bennett Kleinberg

Isabelle van der Vegt

Maximilian Mozes

2020/4/8

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

Co-Authors

H-index: 117
Daniel Cremers

Daniel Cremers

Technische Universität München

H-index: 79
Hinrich Schütze

Hinrich Schütze

Ludwig-Maximilians-Universität München

H-index: 56
Bruno Verschuere

Bruno Verschuere

Universiteit van Amsterdam

H-index: 42
Paul Gill

Paul Gill

University College London

H-index: 40
Lewis D Griffin

Lewis D Griffin

University College London

H-index: 14
Vladimir Golkov

Vladimir Golkov

Technische Universität München

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