All your fake detector are belong to us: evaluating adversarial robustness of fake-news detectors under black-box settings
With the hyperconnectivity and ubiquity of the Internet, the fake news problem now presents
a greater threat than ever before. One promising solution for countering this threat is to …
a greater threat than ever before. One promising solution for countering this threat is to …
[PDF][PDF] Are we safe yet? the limitations of distributional features for fake news detection
Automatic detection of fake news—texts that are deceitful and misleading—is a long
outstanding and largely unsolved problem. Worse yet, recent developments in language …
outstanding and largely unsolved problem. Worse yet, recent developments in language …
Malcom: Generating malicious comments to attack neural fake news detection models
In recent years, the proliferation of so-called “fake news” has caused much disruptions in
society and weakened the news ecosystem. Therefore, to mitigate such problems …
society and weakened the news ecosystem. Therefore, to mitigate such problems …
Explainable tsetlin machine framework for fake news detection with credibility score assessment
The proliferation of fake news, ie, news intentionally spread for misinformation, poses a
threat to individuals and society. Despite various fact-checking websites such as PolitiFact …
threat to individuals and society. Despite various fact-checking websites such as PolitiFact …
Adversarial training for fake news classification
News is a source of information to know about progress in the various areas of life all across
the globe. However, the volume of this information is high, and getting benefits from the …
the globe. However, the volume of this information is high, and getting benefits from the …
A transformer-based approach to multilingual fake news detection in low-resource languages
Fake news classification is one of the most interesting problems that has attracted huge
attention to the researchers of artificial intelligence, natural language processing, and …
attention to the researchers of artificial intelligence, natural language processing, and …
Context-aware misinformation detection: A benchmark of deep learning architectures using word embeddings
New mass media paradigms for information distribution have emerged with the digital age.
With new digital-enabled mass media, the communication process is centered around the …
With new digital-enabled mass media, the communication process is centered around the …
Dafd: Domain adaptation framework for fake news detection
Nowadays, social media has become the leading platform for news dissemination and
consumption. Due to the convenience of social media platforms, fake news spread at an …
consumption. Due to the convenience of social media platforms, fake news spread at an …
Fake news detectors are biased against texts generated by large language models
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 …
threats to society. In the era of Large Language Models (LLMs), the capability to generate …
Fake news detection via NLP is vulnerable to adversarial attacks
News plays a significant role in shaping people's beliefs and opinions. Fake news has
always been a problem, which wasn't exposed to the mass public until the past election …
always been a problem, which wasn't exposed to the mass public until the past election …