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The advent of generative Large Language Models (LLMs) such as ChatGPT has catalyzed transformative advancements across multiple domains. However, alongside these advancements, they have also introduced potential threats. One critical…

Computation and Language · Computer Science 2023-09-28 Bohan Jiang , Zhen Tan , Ayushi Nirmal , Huan Liu

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

Large Language Models (LLMs) have garnered significant attention for their powerful ability in natural language understanding and reasoning. In this paper, we present a comprehensive empirical study to explore the performance of LLMs on…

Computation and Language · Computer Science 2024-12-30 Mengyang Chen , Lingwei Wei , Han Cao , Wei Zhou , Songlin Hu

The advent of Large Language Models (LLMs) has made a transformative impact. However, the potential that LLMs such as ChatGPT can be exploited to generate misinformation has posed a serious concern to online safety and public trust. A…

Computation and Language · Computer Science 2024-04-25 Canyu Chen , Kai Shu

Automated disinformation generation is often listed as an important risk associated with large language models (LLMs). The theoretical ability to flood the information space with disinformation content might have dramatic consequences for…

Computation and Language · Computer Science 2025-06-13 Ivan Vykopal , Matúš Pikuliak , Ivan Srba , Robert Moro , Dominik Macko , Maria Bielikova

Large Language Models (LLMs) have shown remarkable capabilities in knowledge-intensive tasks, while they remain vulnerable when encountering misinformation. Existing studies have explored the role of LLMs in combating misinformation, but…

Computation and Language · Computer Science 2025-05-29 Miao Peng , Nuo Chen , Jianheng Tang , Jia Li

The proliferation of large language models (LLMs) has significantly transformed the digital information landscape, making it increasingly challenging to distinguish between human-written and LLM-generated content. Detecting LLM-generated…

Computation and Language · Computer Science 2025-06-30 Minjia Mao , Dongjun Wei , Xiao Fang , Michael Chau

The emergence of large language models (LLMs) has resulted in the production of LLM-generated texts that is highly sophisticated and almost indistinguishable from texts written by humans. However, this has also sparked concerns about the…

Computation and Language · Computer Science 2023-06-06 Ruixiang Tang , Yu-Neng Chuang , Xia Hu

Large Language Models (LLMs) have shown great potential in Natural Language Processing (NLP) tasks. However, recent literature reveals that LLMs generate nonfactual responses intermittently, which impedes the LLMs' reliability for further…

Computation and Language · Computer Science 2024-03-22 Yukun Zhao , Lingyong Yan , Weiwei Sun , Guoliang Xing , Chong Meng , Shuaiqiang Wang , Zhicong Cheng , Zhaochun Ren , Dawei Yin

Language Models (LMs) may acquire harmful knowledge, and yet feign ignorance of these topics when under audit. Inspired by the recent discovery of deception-related behaviour patterns in LMs, we aim to train classifiers that detect when a…

Computation and Language · Computer Science 2026-03-24 Dhananjay Ashok , Ruth-Ann Armstrong , Jonathan May

The spread of fake news has emerged as a critical challenge, undermining trust and posing threats to society. In the era of Large Language Models (LLMs), the capability to generate believable fake content has intensified these concerns. In…

Computation and Language · Computer Science 2023-09-19 Jinyan Su , Terry Yue Zhuo , Jonibek Mansurov , Di Wang , Preslav Nakov

The pervasiveness of the dissemination of fake news through social media platforms poses critical risks to the trust of the general public, societal stability, and democratic institutions. This challenge calls for novel methodologies in…

Computation and Language · Computer Science 2025-02-04 Jingyuan Yi , Zeqiu Xu , Tianyi Huang , Peiyang Yu

Fake news poses a significant threat to the integrity of information ecosystems and public trust. The advent of Large Language Models (LLMs) holds considerable promise for transforming the battle against fake news. Generally, LLMs represent…

Computation and Language · Computer Science 2024-09-27 Dorsaf Sallami , Yuan-Chen Chang , Esma Aïmeur

Large language models (LLMs) have transformed human writing by enhancing grammar correction, content expansion, and stylistic refinement. However, their widespread use raises concerns about authorship, originality, and ethics, even…

Computation and Language · Computer Science 2024-10-21 Zhen Tao , Zhiyu Li , Runyu Chen , Dinghao Xi , Wei Xu

Large Language Models (LLMs) have gained widespread adoption in various natural language processing tasks, including question answering and dialogue systems. However, a major drawback of LLMs is the issue of hallucination, where they…

Computation and Language · Computer Science 2024-07-08 Yuyan Chen , Qiang Fu , Yichen Yuan , Zhihao Wen , Ge Fan , Dayiheng Liu , Dongmei Zhang , Zhixu Li , Yanghua Xiao

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 (LLMs) have demonstrated remarkable capabilities, but their outputs can sometimes be unreliable or factually incorrect. To address this, we introduce Self Logits Evolution Decoding (SLED), a novel decoding framework…

Computation and Language · Computer Science 2025-08-21 Jianyi Zhang , Da-Cheng Juan , Cyrus Rashtchian , Chun-Sung Ferng , Heinrich Jiang , Yiran Chen

Increased sophistication of large language models (LLMs) and the consequent quality of generated multilingual text raises concerns about potential disinformation misuse. While humans struggle to distinguish LLM-generated content from…

Computation and Language · Computer Science 2026-02-05 Dominik Macko , Aashish Anantha Ramakrishnan , Jason Samuel Lucas , Robert Moro , Ivan Srba , Adaku Uchendu , Dongwon Lee

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) have made significant advances in natural language processing, but their underlying mechanisms are often misunderstood. Despite exhibiting coherent answers and apparent reasoning behaviors, LLMs rely on…

Computation and Language · Computer Science 2024-08-05 Bo Zhou , Daniel Geißler , Paul Lukowicz
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