Search Results for author:
Found 5 papers, 3 papers with code
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models
In this work, we adopt the intuition that the LVLM tends to respond logically consistently for existent objects but inconsistently for hallucinated objects.
Can Large Language Models Detect Rumors on Social Media?
In this work, we investigate to use Large Language Models (LLMs) for rumor detection on social media.
Out-of-distribution Evidence-aware Fake News Detection via Dual Adversarial Debiasing
Then, DAL reversely optimizes news-aspect and evidence-aspect debiasing discriminators to mitigate the impact of news and evidence content biases.
Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks
Comprehensive experiments have demonstrated the superiority of GETRAL over the state-of-the-arts and validated the efficacy of semantic mining with graph structure and contrastive learning.
Evidence-aware Fake News Detection with Graph Neural Networks
In this paper, we focus on the evidence-based fake news detection, where several evidences are utilized to probe the veracity of news (i. e., a claim).
