2,077+ academic papers on AI security, attacks, and defenses
Showing 261–280 of 792 papers
Clear filtersMingqian Feng, Xiaodong Liu, Weiwei Yang +3 more
Large Language Models (LLMs) are typically evaluated for safety under single-shot or low-budget adversarial prompting, which underestimates...
Tanusree Debi, Wentian Zhu
Large language model (LLM) based agents are increasingly used to automate financial transactions, yet their reliance on contextual reasoning exposes...
Naen Xu, Jinghuai Zhang, Ping He +6 more
Large language models (LLMs) have been widely integrated into critical automated workflows, including contract review and job application processes....
Aarush Noheria, Yuguang Yao
Vision-language models (VLMs) have become central to tasks such as visual question answering, image captioning, and text-to-image generation....
Javier Carnerero-Cano, Luis Muñoz-González, Phillippa Spencer +1 more
Regression models are widely used in industrial processes, engineering, and in natural and physical sciences, yet their robustness to poisoning has...
Amirhossein Taherpour, Xiaodong Wang
Federated learning (FL) enables collaborative model training while preserving data privacy, yet both centralized and decentralized approaches face...
Xiaogeng Liu, Xinyan Wang, Yechao Zhang +5 more
Large reasoning models (LRMs) extend large language models with explicit multi-step reasoning traces, but this capability introduces a new class of...
Mingyang Liao, Yichen Wan, shuchen wu +6 more
LLM-based role-playing has rapidly improved in fidelity, yet stronger adherence to persona constraints commonly increases vulnerability to jailbreak...
Ningyuan He, Ronghong Huang, Qianqian Tang +3 more
In-context learning (ICL) has become a powerful, data-efficient paradigm for text classification using large language models. However, its robustness...
Wenhui Zhang, Huiyu Xu, Zhibo Wang +4 more
Recent advancements in multi-model AI systems have leveraged LLM routers to reduce computational cost while maintaining response quality by assigning...
Alvi Md Ishmam, Najibul Haque Sarker, Zaber Ibn Abdul Hakim +1 more
Multimodal Large Language Models (MLLMs) have achieved remarkable performance across vision-language tasks. Recent advancements allow these models to...
Arther Tian, Alex Ding, Frank Chen +2 more
Decentralized large language model inference networks require lightweight mechanisms to reward high quality outputs under heterogeneous latency and...
Jarrod Barnes
As large language models (LLMs) improve, so do their offensive applications: frontier agents now generate working exploits for under $50 in compute...
Onkar Shelar, Travis Desell
Evolutionary prompt search is a practical black-box approach for red teaming large language models (LLMs), but existing methods often collapse onto a...
Xingwei Lin, Wenhao Lin, Sicong Cao +4 more
Multi-turn jailbreak attacks have emerged as a critical threat to Large Language Models (LLMs), bypassing safety mechanisms by progressively...
Yizhong Ding
Webshells remain a primary foothold for attackers to compromise servers, particularly within PHP ecosystems. However, existing detection mechanisms...
Yuetian Chen, Kaiyuan Zhang, Yuntao Du +5 more
Diffusion Language Models (DLMs) represent a promising alternative to autoregressive language models, using bidirectional masked token prediction....
Md Tasnim Jawad, Mingyan Xiao, Yanzhao Wu
With the widespread adoption of Large Language Models (LLMs) and increasingly stringent privacy regulations, protecting data privacy in LLMs has...
Haonan Zhang, Dongxia Wang, Yi Liu +2 more
Safety-aligned LLMs suffer from two failure modes: jailbreak (answering harmful inputs) and over-refusal (declining benign queries). Existing vector...
Yangyang Guo, Ziwei Xu, Si Liu +2 more
This study reveals a previously unexplored vulnerability in the safety alignment of Large Language Models (LLMs). Existing aligned LLMs predominantly...
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