2,077+ academic papers on AI security, attacks, and defenses
Showing 641–660 of 2,025 papers
Clear filtersWeizhe Tang, Junwei You, Jiaxi Liu +5 more
End-to-end autonomous driving models increasingly benefit from large vision--language models for semantic understanding, yet ensuring safe and...
Xueyi Li, Zhuoneng Zhou, Zitao Liu +2 more
Large language models (LLMs) have demonstrated remarkable potential for automatic short answer grading (ASAG), significantly boosting student...
Srinivas Rao Marri
The proliferation of AI-assisted "vibe coding" enables rapid software development but introduces significant security risks, as Large Language Models...
Manveer Singh Tamber, Hosna Oyarhoseini, Jimmy Lin
Research on adversarial robustness in language models is currently fragmented across applications and attacks, obscuring shared vulnerabilities. In...
Licheng Pan, Yunsheng Lu, Jiexi Liu +5 more
Uncovering the mechanisms behind "jailbreaks" in large language models (LLMs) is crucial for enhancing their safety and reliability, yet these...
Cláudio Lúcio do Val Lopes, João Marcus Pitta, Fabiano Belém +2 more
The integration of Artificial Intelligence (AI) into clinical settings presents a software engineering challenge, demanding a shift from isolated...
Md Jahedur Rahman, Ihsen Alouani
Large language models (LLMs) are increasingly used in interactive and retrieval-augmented systems, but they remain vulnerable to task drift;...
Hao Gu, Mao-Lin Luo, Zi-Hao Zhou +3 more
Parameter-efficient continual learning aims to adapt pre-trained models to sequential tasks without forgetting previously acquired knowledge. Most...
Ranjith Krishnamurthy, Oshando Johnson, Goran Piskachev +1 more
Security vulnerabilities often arise unintentionally during development due to a lack of security expertise and code complexity. Traditional tools,...
Yuxuan Lu, Yongkang Guo, Yuqing Kong
Safety alignment in Large Language Models (LLMs) often creates a systematic discrepancy between a model's aligned output and the underlying...
Haoran Ou, Kangjie Chen, Gelei Deng +4 more
Fact-checking systems with search-enabled large language models (LLMs) have shown strong potential for verifying claims by dynamically retrieving...
Naen Xu, Hengyu An, Shuo Shi +7 more
Recent advancements in large language models (LLMs) have significantly enhanced the capabilities of collaborative multi-agent systems, enabling them...
Yihang Chen, Zhao Xu, Youyuan Jiang +2 more
Large Vision-Language Models (LVLMs) are increasingly equipped with robust safety safeguards to prevent responses to harmful or disallowed prompts....
Zeyuan He, Yupeng Chen, Lang Lin +7 more
Diffusion large language models (D-LLMs) offer an alternative to autoregressive LLMs (AR-LLMs) and have demonstrated advantages in generation...
Jiate Li, Defu Cao, Li Li +8 more
Large language models (LLMs) have been serving as effective backbones for retrieval systems, including Retrieval-Augmentation-Generation (RAG), Dense...
Kunal Mukherjee, Zulfikar Alom, Tran Gia Bao Ngo +2 more
The rise of bot accounts on social media poses significant risks to public discourse. To address this threat, modern bot detectors increasingly rely...
Luze Sun, Alina Oprea, Eric Wong
LLM-based vulnerability detectors are increasingly deployed in security-critical code review, yet their resilience to evasion under...
Abhishek Mishra, Mugilan Arulvanan, Reshma Ashok +3 more
Emergent misalignment poses risks to AI safety as language models are increasingly used for autonomous tasks. In this paper, we present a population...
Rory Driscoll, Alexandros Christoforos, Chadbourne Davis
While sequential reasoning enhances the capability of Vision-Language Models (VLMs) to execute complex multimodal tasks, their reliability in...
Ye Yu, Haibo Jin, Yaoning Yu +2 more
Large audio-language models increasingly operate on raw speech inputs, enabling more seamless integration across domains such as voice assistants,...
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