Challenges and applications of large language models J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy arXiv preprint arXiv:2307.10169, 2023 | 232 | 2023 |
Measuring emotions in the covid-19 real world worry dataset B Kleinberg, I van der Vegt, M Mozes NLP COVID-19 Workshop, ACL 2020, 2020 | 217* | 2020 |
Frequency-guided word substitutions for detecting textual adversarial examples M Mozes, P Stenetorp, B Kleinberg, LD Griffin EACL 2021, 2020 | 94 | 2020 |
Using named entities for computer‐automated verbal deception detection B Kleinberg, M Mozes, A Arntz, B Verschuere Journal of forensic sciences 63 (3), 714-723, 2018 | 53 | 2018 |
Use of llms for illicit purposes: Threats, prevention measures, and vulnerabilities M Mozes, X He, B Kleinberg, LD Griffin arXiv preprint arXiv:2308.12833, 2023 | 40 | 2023 |
Online influence, offline violence: language use on YouTube surrounding the ‘Unite the Right’rally I Van der Vegt, M Mozes, P Gill, B Kleinberg Journal of Computational Social Science 4, 333-354, 2021 | 37 | 2021 |
The grievance dictionary: Understanding threatening language use I van der Vegt, M Mozes, B Kleinberg, P Gill Behavior research methods, 1-15, 2021 | 36 | 2021 |
Identifying the sentiment styles of YouTube's vloggers B Kleinberg, M Mozes, I van der Vegt EMNLP 2018, 2018 | 26 | 2018 |
No intruder, no validity: Evaluation criteria for privacy-preserving text anonymization M Mozes, B Kleinberg arXiv preprint arXiv:2103.09263, 2021 | 20 | 2021 |
Netanos-named entity-based text anonymization for open science B Kleinberg, M Mozes, Y van der Toolen OSF Preprints, 2017 | 16 | 2017 |
Susceptibility to influence of large language models LD Griffin, B Kleinberg, M Mozes, KT Mai, M Vau, M Caldwell, ... arXiv preprint arXiv:2303.06074, 2023 | 13 | 2023 |
Uphill from here: Sentiment patterns in videos from left-and right-wingYouTube news channels F Soldner, JCT Ho, M Makhortykh, I Van der Vegt, M Mozes, B Kleinberg Workshop on Natural Language Processing and Computational Social Science 3 …, 2019 | 12 | 2019 |
Web-based text anonymization with Node.js: Introducing NETANOS (Named entity-based Text Anonymization for Open Science) MM Bennett Kleinberg The Journal of Open Source Software 2 (14), 2017 | 12 | 2017 |
Contrasting human-and machine-generated word-level adversarial examples for text classification M Mozes, M Bartolo, P Stenetorp, B Kleinberg, LD Griffin EMNLP 2021, 2021 | 10 | 2021 |
A repeated-measures study on emotional responses after a year in the pandemic M Mozes, I van der Vegt, B Kleinberg Scientific reports 11 (1), 23114, 2021 | 9 | 2021 |
Challenges and applications of large language models. arXiv 2023 J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy arXiv preprint arXiv:2307.10169 10, 0 | 9 | |
Large language models respond to influence like humans L Griffin, B Kleinberg, M Mozes, K Mai, MDM Vau, M Caldwell, ... Proceedings of the First Workshop on Social Influence in Conversations …, 2023 | 8 | 2023 |
Challenges and applications of large language models. arXiv J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu, R McHardy Preprint posted online 19, 2023 | 7 | 2023 |
Textwash--automated open-source text anonymisation B Kleinberg, T Davies, M Mozes arXiv preprint arXiv:2208.13081, 2022 | 7 | 2022 |
Towards agile text classifiers for everyone M Mozes, J Hoffmann, K Tomanek, M Kouate, N Thain, A Yuan, ... arXiv preprint arXiv:2302.06541, 2023 | 6 | 2023 |