AI labels, typically implemented via underlying tracing mechanisms such as watermarks and metadata, are crucial for protecting Artificial Intelligence-Generated Content (AIGC) against security threats like disinformation and evasion. However, the perceived devaluation of AI-assisted work discourages creators from discl...
Shu-Ning Zhang, Hui Wang, Rongjun Ma et al.· 0 citations
Human dishonesty in group settings is highly susceptible to peer influence, particularly when incentivized. Although artificial intelligence (AI) evolves from passive tools into active collaborators, its impact on human moral behavior within groups remains underexplored. We addressed this gap through a two-phase random...
Shu-Ning Zhang, Xin-Yuan Zhou, Yuan-Yang Qiu et al.· 0 citations
Social media fact-checking has long been challenged by evidence-level and aggregation-level conflicts, where erroneous evidence mimics authoritative news sources. To capture this challenge and support conflict verification tasks, we present ContraNote, a large-scale real-world dataset curated from X's Community Notes s...
Shu-Ning Zhang, D. Shi, Bo-Hao Chu et al.· 0 citations
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