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Related papers: Explore the Potential of LLMs in Misinformation De…

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The emergence of Large Language Models (LLMs) presents a dual challenge in the fight against disinformation. These powerful tools, capable of generating human-like text at scale, can be weaponised to produce sophisticated and persuasive…

Large Language Models (LLMs) demonstrate impressive capabilities across various fields, yet their increasing use raises critical security concerns. This article reviews recent literature addressing key issues in LLM security, with a focus…

Cryptography and Security · Computer Science 2025-11-26 Benji Peng , Keyu Chen , Ming Li , Pohsun Feng , Ziqian Bi , Junyu Liu , Xinyuan Song , Qian Niu

The proliferation of fake news has had far-reaching implications on politics, the economy, and society at large. While Fake news detection methods have been employed to mitigate this issue, they primarily depend on two essential elements:…

Computation and Language · Computer Science 2024-03-18 Guanghua Li , Wensheng Lu , Wei Zhang , Defu Lian , Kezhong Lu , Rui Mao , Kai Shu , Hao Liao

Large language models are limited by challenges in factuality and hallucinations to be directly employed off-the-shelf for judging the veracity of news articles, where factual accuracy is paramount. In this work, we propose DELL that…

Computation and Language · Computer Science 2024-07-08 Herun Wan , Shangbin Feng , Zhaoxuan Tan , Heng Wang , Yulia Tsvetkov , Minnan Luo

The proliferation of disinformation, particularly in multimodal contexts combining text and images, presents a significant challenge across digital platforms. This study investigates the potential of large multimodal models (LMMs) in…

Computer Vision and Pattern Recognition · Computer Science 2025-09-29 Yasmina Kheddache , Marc Lalonde

Large Language Models (LLMs) have garnered significant attention due to their remarkable ability to process information across various languages. Despite their capabilities, they exhibit inconsistencies in handling identical queries in…

Computation and Language · Computer Science 2024-06-24 Yue Huang , Chenrui Fan , Yuan Li , Siyuan Wu , Tianyi Zhou , Xiangliang Zhang , Lichao Sun

The rapid growth of social media has resulted in an explosion of online news content, leading to a significant increase in the spread of misleading or false information. While machine learning techniques have been widely applied to detect…

Computation and Language · Computer Science 2024-12-10 Hao Chen , Hui Guo , Baochen Hu , Shu Hu , Jinrong Hu , Siwei Lyu , Xi Wu , Xin Wang

Large Language Models (LLMs) store an extensive amount of factual knowledge obtained from vast collections of text. To effectively utilize these models for downstream tasks, it is crucial to have reliable methods for measuring their…

Computation and Language · Computer Science 2023-06-13 Pouya Pezeshkpour

Large language models (LLMs) are the result of a massive experiment in bottom-up, data-driven reverse engineering of language at scale. Despite their utility in a number of downstream NLP tasks, ample research has shown that LLMs are…

Artificial Intelligence · Computer Science 2024-08-05 Walid S. Saba

The paper considers the possibility of fine-tuning Llama 2 large language model (LLM) for the disinformation analysis and fake news detection. For fine-tuning, the PEFT/LoRA based approach was used. In the study, the model was fine-tuned…

Computation and Language · Computer Science 2023-09-12 Bohdan M. Pavlyshenko

As Large Language Models (LLMs) are widely deployed in diverse scenarios, the extent to which they could tacitly spread misinformation emerges as a critical safety concern. Current research primarily evaluates LLMs on explicit false…

Computation and Language · Computer Science 2025-09-30 Ruohao Guo , Wei Xu , Alan Ritter

It is challenging to control the quality of online information due to the lack of supervision over all the information posted online. Manual checking is almost impossible given the vast number of posts made on online media and how quickly…

Computation and Language · Computer Science 2022-03-16 Rini Anggrainingsih , Ghulam Mubashar Hassan , Amitava Datta

Large Language Models (LLMs) have revolutionised natural language processing, exhibiting impressive human-like capabilities. In particular, LLMs are capable of "lying", knowingly outputting false statements. Hence, it is of interest and…

Computation and Language · Computer Science 2024-10-22 Lennart Bürger , Fred A. Hamprecht , Boaz Nadler

Large language models (LLMs) offer unprecedented opportunities for analyzing social phenomena at scale. This paper demonstrates the value of LLMs in psychological measurement by (1) compiling the first large-scale dataset of election rumors…

Artificial Intelligence · Computer Science 2026-01-09 Etienne Casanova , R. Michael Alvarez

Preventing the spread of misinformation is challenging. The detection of misleading content presents a significant hurdle due to its extreme linguistic and domain variability. Content-based models have managed to identify deceptive language…

Computation and Language · Computer Science 2024-01-30 Flavio Merenda , José Manuel Gómez-Pérez

The widespread deployment of large language models (LLMs) across critical domains has amplified the societal risks posed by algorithmically generated misinformation. Unlike traditional false content, LLM-generated misinformation can be…

Information Retrieval · Computer Science 2025-07-09 Shuliang Liu , Hongyi Liu , Aiwei Liu , Bingchen Duan , Qi Zheng , Yibo Yan , He Geng , Peijie Jiang , Jia Liu , Xuming Hu

Mechanistic approaches to deception in large language models (LLMs) often rely on "lie detectors", that is, truth probes trained to identify internal representations of model outputs as false. The lie detector approach to LLM deception…

Computation and Language · Computer Science 2026-03-12 Tom-Felix Berger

Explainable fake news detection predicts the authenticity of news items with annotated explanations. Today, Large Language Models (LLMs) are known for their powerful natural language understanding and explanation generation abilities.…

Computation and Language · Computer Science 2024-12-25 Yifeng Wang , Zhouhong Gu , Siwei Zhang , Suhang Zheng , Tao Wang , Tianyu Li , Hongwei Feng , Yanghua Xiao

Automatic detection of multimodal misinformation has gained a widespread attention recently. However, the potential of powerful Large Language Models (LLMs) for multimodal misinformation detection remains underexplored. Besides, how to…

Computation and Language · Computer Science 2024-04-09 Longzheng Wang , Xiaohan Xu , Lei Zhang , Jiarui Lu , Yongxiu Xu , Hongbo Xu , Minghao Tang , Chuang Zhang

Real-world information, often multimodal, can be misinformed or potentially misleading due to factual errors, outdated claims, missing context, misinterpretation, and more. Such "misinformation" is understudied, challenging to address, and…

Computation and Language · Computer Science 2026-01-13 Xinyi Zhou , Ashish Sharma , Amy X. Zhang , Tim Althoff