activity
20172022
most citedAutomatic Detection of Fake News

379 citations · 514 across the 11 of their papers we have counts for

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Showing cs.CLShow all

15 papers · 1 filter

cs.CL202219 cited

Who is GPT-3? An Exploration of Personality, Values and Demographics

Marilù Miotto, Nicola Rossberg, Bennett Kleinberg

Language models such as GPT-3 have caused a furore in the research community. Some studies found that GPT-3 has some creative abilities and makes mistakes that are on par with huma…

cs.CL2022

Identifying Human Strategies for Generating Word-Level Adversarial Examples

Maximilian Mozes, Bennett Kleinberg, Lewis D. Griffin

Adversarial examples in NLP are receiving increasing research attention. One line of investigation is the generation of word-level adversarial examples against fine-tuned Transform…

cs.CL20221 cited

Explainable Verbal Deception Detection using Transformers

Loukas Ilias, Felix Soldner, Bennett Kleinberg

People are regularly confronted with potentially deceptive statements (e.g., fake news, misleading product reviews, or lies about activities). Only few works on automated text-base…

cs.CL2021

Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification

Maximilian Mozes, Max Bartolo, Pontus Stenetorp +2

Research shows that natural language processing models are generally considered to be vulnerable to adversarial attacks; but recent work has drawn attention to the issue of validat…

cs.CL20219 cited

No Intruder, no Validity: Evaluation Criteria for Privacy-Preserving Text Anonymization

Maximilian Mozes, Bennett Kleinberg

For sensitive text data to be shared among NLP researchers and practitioners, shared documents need to comply with data protection and privacy laws. There is hence a growing intere…

cs.CL2020

The Grievance Dictionary: Understanding Threatening Language Use

Isabelle van der Vegt, Maximilian Mozes, Bennett Kleinberg +1

This paper introduces the Grievance Dictionary, a psycholinguistic dictionary which can be used to automatically understand language use in the context of grievance-fuelled violenc…