arXiv:2512. 03553v3 Announce Type: replace-cross Abstract: Content moderation remains a critical yet challenging task for large-scale user-generated video platforms, especially in livestreaming environments where moderation must be timely, multimodal, and robust to evolving forms of unwanted content.
By Wei Chee Yew, Hailun Xu, Sanjay Saha, Xiaotian Fan, Hiok Hian Ong, David Yuchen Wang, Kanchan Sarkar, Zhenheng Yang, Danhui Guan
arXiv:2607. 10312v1 Announce Type: cross Abstract: The rapid proliferation of online polarization threatens social cohesion, necessitating robust automated detection systems that operate effectively across diverse linguistic contexts.
By Muhammad Abdullahi Said
arXiv:2607. 20463v1 Announce Type: new Abstract: This paper presents an AI-driven browser extension that identifies clickbait to help users avoid misleading Internet articles.
By Wojciech Michaluk, Tymoteusz Urban, Mateusz Kubita, Soveatin Kuntur, Anna Wr\'oblewska
arXiv:2608. 02399v1 Announce Type: cross Abstract: Content-based detection of unreliable news is increasingly difficult, as low-reliability sources mimic credible journalism and generative AI makes fabricated content harder to flag.
By Raphaela Ke{\ss}ler, Roman David Ventzke, Viola Priesemann, Giordano De Marzo
arXiv:2607. 15267v1 Announce Type: new Abstract: Poisoning pretraining data can introduce harmful behaviors to LMs that are difficult to detect and mitigate.
By Victoria Graf, Hannaneh Hajishirzi, Noah A. Smith, David Kohlbrenner, Kyle Lo
arXiv:2606. 04199v1 Announce Type: cross Abstract: The increasing use of large language models has raised concerns about the spread of AI-generated fake news, particularly under varying prompting strategies.
By Aya Vera-Jimenez, Samuel Jaeger, Calvin Ibenye, Dhrubajyoti Ghosh