arXiv:2607. 20730v1 Announce Type: cross Abstract: Large language models increasingly use search tools to retrieve up-to-date information, introducing a new attack surface in which retrieved documents can be manipulated.
By Zhaoqi Wang, Zijian Zhang, Xiaomei Yuan, Pengtao Kou, Jiamou Liu, Zhen Li, Liehuang Zhu
arXiv:2410. 01574v4 Announce Type: replace-cross Abstract: The rapid advancement of Generative Artificial Intelligence (GenAI) capabilities is accompanied by a concerning rise in its misuse.
By Sina Mavali, Jonas Ricker, David Pape, Asja Fischer, Lea Sch\"onherr
arXiv:2606. 27736v1 Announce Type: new Abstract: The rapid spread of fake news poses increasing threats to information ecosystems, especially as AI-generated misinformation under Generative Engine Optimization (GEO) poisoning allows adversarially crafted content to be systematically surfaced by retrieval systems, contaminating LLM reasoning.
By Zhaoqi Wang, Zijian Zhang, Kun Zheng, Zhen Li, Xin Li, Chunlei Li, Jiamou Liu
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:2608. 16259v1 Announce Type: cross Abstract: The rapid progress of image generation models calls for AI-generated image (AIGI) detectors that are not only accurate but also explainable and reliable.
By Bowen Deng, Jiahui Zhan, Yikun Ji, Haozhen Yan, Jianfu Zhang
arXiv:2508. 09105v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) and its Multimodal Retrieval-Augmented Generation (MRAG) significantly improve the knowledge coverage and contextual understanding of Large Language Models (LLMs) by introducing external knowledge sources.
By Shixuan Sun, Siyuan Liang, Jianjie Huang, Jingzhi Li, Xiaochun Cao