2,104+ academic papers on AI security, attacks, and defenses
Showing 761–780 of 2,049 papers
Clear filtersMengyuan Jin, Zehui Liao, Yong Xia
Multimodal Large Language Models (MLLMs) have shown remarkable capability in assisting disease diagnosis in medical visual question answering (VQA)....
Krittin Pachtrachai, Petmongkon Pornpichitsuwan, Wachiravit Modecrua +1 more
Building reliable conversational AI assistants for customer-facing industries remains challenging due to noisy conversational data, fragmented...
Dezhang Kong, Zhuxi Wu, Shiqi Liu +8 more
LLM-based web agents have become increasingly popular for their utility in daily life and work. However, they exhibit critical vulnerabilities when...
Mohammad Fasha, Faisal Abul Rub, Nasim Matar +2 more
Large Language Models (LLMs) have emerged as a transformative and disruptive technology, enabling a wide range of applications in natural language...
Alexandra Chouldechova, A. Feder Cooper, Solon Barocas +3 more
We argue that conclusions drawn about relative system safety or attack method efficacy via AI red teaming are often not supported by evidence...
Thomas Heverin
Prompt injection evaluations typically treat refusal as a stable, binary indicator of safety. This study challenges that paradigm by modeling refusal...
Jiahe Guo, Xiangran Guo, Yulin Hu +8 more
Long-term memory enables large language model (LLM) agents to support personalized and sustained interactions. However, most work on personalized...
Xiaohui Hu, Wun Yu Chan, Yuejie Shi +5 more
Smart contract security is paramount, but identifying intricate business logic vulnerabilities remains a persistent challenge because existing...
Zelong Zheng, Jiayuan Zhou, Xing Hu +2 more
Software vulnerability management has become increasingly critical as modern systems scale in size and complexity. However, existing automated...
Alireza Salemi, Hamed Zamani
Personalization is crucial for aligning Large Language Model (LLM) outputs with individual user preferences and background knowledge....
Qi Li, Xinchao Wang
Enabling large language models (LLMs) to solve complex reasoning tasks is a key step toward artificial general intelligence. Recent work augments...
Narek Maloyan, Dmitry Namiot
The Model Context Protocol (MCP) has emerged as a de facto standard for integrating Large Language Models with external tools, yet no formal security...
Narek Maloyan, Dmitry Namiot
The proliferation of agentic AI coding assistants, including Claude Code, GitHub Copilot, Cursor, and emerging skill-based architectures, has...
Marton Szep, Jorge Marin Ruiz, Georgios Kaissis +4 more
Fine-tuning Large Language Models (LLMs) on sensitive datasets carries a substantial risk of unintended memorization and leakage of Personally...
Chen Ling, Kai Hu, Hangcheng Liu +3 more
Large Vision-Language Models (LVLMs) are increasingly deployed in real-world intelligent systems for perception and reasoning in open physical...
Mohammad Zare, Pirooz Shamsinejadbabaki
Membership inference attacks (MIAs) pose a serious threat to the privacy of machine learning models by allowing adversaries to determine whether a...
Jiankai Jin, Xiangzheng Zhang, Zhao Liu +2 more
Machine learning systems can produce personalized outputs that allow an adversary to infer sensitive input attributes at inference time. We introduce...
Hugo Silva, Mateus Mendes, Hugo Gonçalo Oliveira
Large language models (LLMs) are evolving fast and are now frequently used as evaluators, in a process typically referred to as LLM-as-a-Judge, which...
David Condrey
Recent proposals advocate using keystroke timing signals, specifically the coefficient of variation ($δ$) of inter-keystroke intervals, to...
Massimiliano Pronesti, Anya Belz, Yufang Hou
Recent work on reinforcement learning with verifiable rewards (RLVR) has shown that large language models (LLMs) can be substantially improved using...
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