2,077+ academic papers on AI security, attacks, and defenses
Showing 221–240 of 2,077 papers
Yuanbo Li, Tianyang Xu, Cong Hu +3 more
The rapid progress of Multi-Modal Large Language Models (MLLMs) has significantly advanced downstream applications. However, this progress also...
G. Madan Mohan, Veena Kiran Nambiar, Kiranmayee Janardhan
We introduce the Dynamic Behavioral Constraint (DBC) benchmark, the first empirical framework for evaluating the efficacy of a structured,...
Furkan Mumcu, Yasin Yilmaz
As Large Language Models (LLMs) transition into autonomous multi-agent ecosystems, robust minimax training becomes essential yet remains prone to...
Geraldin Nanfack, Eugene Belilovsky, Elvis Dohmatob
Safety-aligned language models refuse harmful requests through learned refusal behaviors encoded in their internal representations. Recent...
Kelly L Vomo-Donfack, Adryel Hoszu, Grégory Ginot +1 more
Federated learning (FL) faces two structural tensions: gradient sharing enables data-reconstruction attacks, while non-IID client distributions...
Evgenija Popchanovska, Ana Gjorgjevikj, Maryan Rizinski +3 more
Large language models (LLMs) are increasingly embedded in high-stakes workflows, where failures propagate beyond isolated model errors into systemic...
Jiaxun Guo, Ziyuan Yang, Mengyu Sun +3 more
The rapid adoption of Large Language Models (LLMs) has transformed modern software development by enabling automated code generation at scale. While...
Cameron Bell, Timothy Johnston, Antoine Luciano +1 more
Theoretical and applied research into privacy encompasses an incredibly broad swathe of differing approaches, emphasis and aims. This work introduces...
Max Landauer, Wolfgang Hotwagner, Thorina Boenke +2 more
Log data are essential for intrusion detection and forensic investigations. However, manual log analysis is tedious due to high data volumes,...
Arther Tian, Alex Ding, Frank Chen +2 more
Decentralized large language model (LLM) inference networks can pool heterogeneous compute to scale serving, but they require lightweight and...
Yizhe Xie, Congcong Zhu, Xinyue Zhang +5 more
Large Language Model-based Multi-Agent Systems (LLM-MAS) are increasingly applied to complex collaborative scenarios. However, their collaborative...
Junchen Li, Chao Qi, Rongzheng Wang +5 more
Retrieval-Augmented Generation (RAG) enhances the capabilities of large language models (LLMs) by incorporating external knowledge, but its reliance...
Wang Jian, Shen Hong, Ke Wei +1 more
While federated learning protects data privacy, it also makes the model update process vulnerable to long-term stealthy perturbations. Existing...
Maheep Chaudhary
Humans often become more self-aware under threat, yet can lose self-awareness when absorbed in a task; we hypothesize that language models exhibit...
Zeyu Zhang, Xiangxiang Dai, Ziyi Han +2 more
Large language models (LLMs) are typically governed by post-training alignment (e.g., RLHF or DPO), which yields a largely static policy during...
Yangyang Wei, Yijie Xu, Zhenyuan Li +2 more
Multi-Agent System is emerging as the \textit{de facto} standard for complex task orchestration. However, its reliance on autonomous execution and...
Neha Nagaraja, Lan Zhang, Zhilong Wang +2 more
Multimodal Large Language Models (MLLMs) integrate vision and text to power applications, but this integration introduces new vulnerabilities. We...
Neha Nagaraja, Hayretdin Bahsi
While incorporating LLMs into systems offers significant benefits in critical application areas such as healthcare, new security challenges emerge...
Brandon Yee, Krishna Sharma
MoltBook is a large-scale multi-agent coordination environment where over 770,000 autonomous LLM agents interact without human participation,...
Subramanyam Sahoo
Agentic AI systems - capable of goal interpretation, world modeling, planning, tool use, long-horizon operation, and autonomous coordination -...
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