4 accepted papers
From generating headlines to fabricating news, the Large Language Models (LLMs) are typically assessed by their final outputs, under the safety assumption that a refusal response signifies safe reasoning throughout the entire process. Challenging this assumption, our study reveals that during fake n…
The spread of fake news on online platforms has long been a pressing concern. Considering this, extensive efforts have been made to develop fake news detectors. However, a major drawback of these models is their relatively low performance—lagging by more than 20%—in identifying *fake* news compared…
Image forgeries can entirely change the semantic information of an image, and can be used for unscrupulous purposes. In this paper, we propose a novel image forgery localization network named as MUN, which consists of an M^3 encoder and a UN decoder. Firstly, the M^3 encoder is constructed based on…
Sentence-level extractive summarization is a fundamental yet challenging task, and recent powerful approaches prefer to pick sentences sorted by the predicted probabilities until the length limit is reached, a.k.a. ``Top-K Strategy''. This length limit is fixed based on the validation set, resulting…