23 citations · 58 across the 11 of their papers we have counts for
9 papers · 1 filter
Build it, Break it, Repeat: Benchmarking and improving LLM-manipulated disinformation detection in social media posts
Kevin Thomas, Milosz Kasprzyk, Reuel C Igbokwe Onuigbo +5
Detecting machine-generated disinformation on social media is increasingly difficult as large language models (LLMs) make it easier to generate and rewrite misleading content at sc…
A Browser-based Open Source Assistant for Multimodal Content Verification
Rosanna Milner, Michael Foster, Twin Karmakharm +5
Disinformation and false content produced by generative AI pose a significant challenge for journalists and fact-checkers who must rapidly verify digital media information. While t…
Truth with a Twist: The Rhetoric of Persuasion in Professional vs. Community-Authored Fact-Checks
Olesya Razuvayevskaya, Kalina Bontcheva
This study presents the first large-scale comparison of persuasion techniques present in crowd- versus professionally-written debunks. Using extensive datasets from Community Notes…
LLM-Based Adversarial Persuasion Attacks on Fact-Checking Systems
João A. Leite, Olesya Razuvayevskaya, Kalina Bontcheva +1
Automated fact-checking (AFC) systems are susceptible to adversarial attacks, enabling false claims to evade detection. Existing adversarial frameworks typically rely on injecting…
A Survey on Automatic Credibility Assessment Using Textual Credibility Signals in the Era of Large Language Models
Ivan Srba, Olesya Razuvayevskaya, João A. Leite +10
In the age of social media and generative AI, the ability to automatically assess the credibility of online content has become increasingly critical, complementing traditional appr…
EUvsDisinfo: A Dataset for Multilingual Detection of Pro-Kremlin Disinformation in News Articles
João A. Leite, Olesya Razuvayevskaya, Kalina Bontcheva +1
This work introduces EUvsDisinfo, a multilingual dataset of disinformation articles originating from pro-Kremlin outlets, along with trustworthy articles from credible / less biase…
Weakly Supervised Veracity Classification with LLM-Predicted Credibility Signals
João A. Leite, Olesya Razuvayevskaya, Kalina Bontcheva +1
Credibility signals represent a wide range of heuristics typically used by journalists and fact-checkers to assess the veracity of online content. Automating the extraction of cred…
Comparison between parameter-efficient techniques and full fine-tuning: A case study on multilingual news article classification
Olesya Razuvayevskaya, Ben Wu, Joao A. Leite +5
Adapters and Low-Rank Adaptation (LoRA) are parameter-efficient fine-tuning techniques designed to make the training of language models more efficient. Previous results demonstrate…
SheffieldVeraAI at SemEval-2023 Task 3: Mono and multilingual approaches for news genre, topic and persuasion technique classification
Ben Wu, Olesya Razuvayevskaya, Freddy Heppell +4
This paper describes our approach for SemEval-2023 Task 3: Detecting the category, the framing, and the persuasion techniques in online news in a multi-lingual setup. For Subtask 1…