2,077+ academic papers on AI security, attacks, and defenses
Showing 181–200 of 603 papers
Clear filtersAbhilekh Borah, Shubhra Ghosh, Kedar Joshi +2 more
Tasks such as solving arithmetic equations, evaluating truth tables, and completing syllogisms are handled well by large language models (LLMs) in...
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...
Wei Chen, Zhiyuan Peng, Xin Yin +4 more
Smart contracts are the backbone of the decentralized web, yet ensuring their functional correctness and security remains a critical challenge. While...
Yunpeng Xiong, Ting Zhang
Static Application Security Testing (SAST) tools are essential for identifying software vulnerabilities, but they often produce a high volume of...
Evgeny Grigorenko, David Stanojević, David Ilić +2 more
Modern Integrated Development Environments (IDEs) increasingly leverage Large Language Models (LLMs) to provide advanced features like code...
Farnaz Soltaniani, Shoaib Razzaq, Mohammad Ghafari
Early detection of security bug reports (SBRs) is critical for timely vulnerability mitigation. We present an evaluation of prompt-based engineering...
Ivan K. Tung, Yu Xiang Shi, Alex Chien +2 more
Creating attack paths for cyber defence exercises requires substantial expert effort. Existing automation requires vulnerability graphs or exploit...
Jaehee Kim, Pilsung Kang
Modern LLMs are increasingly accessed via black-box APIs, requiring users to transmit sensitive prompts, outputs, and fine-tuning data to external...
Yanlin Wang, Ziyao Zhang, Chong Wang +5 more
Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, but their proficiency in producing secure code remains a...
Miao Lin, Feng Yu, Rui Ning +6 more
Deep neural networks are highly susceptible to backdoor attacks, yet most defense methods to date rely on balanced data, overlooking the pervasive...
Yavuz Bakman, Duygu Nur Yaldiz, Salman Avestimehr +1 more
Large Language Models (LLMs) are rarely static and are frequently updated in practice. A growing body of alignment research has shown that models...
Gloria Felicia, Michael Eniolade, Jinfeng He +4 more
Existing agent safety benchmarks report binary accuracy, conflating early intervention with post-mortem analysis. A detector that flags a violation...
Xiaoyu Xu, Minxin Du, Kun Fang +6 more
Large language models (LLMs) demonstrate impressive capabilities across diverse tasks but raise concerns about privacy, copyright, and harmful...
Devanshu Sahoo, Manish Prasad, Vasudev Majhi +5 more
The rapid integration of Large Language Models (LLMs) into educational assessment rests on the unverified assumption that instruction following...
Mingqiao Mo, Yunlong Tan, Hao Zhang +2 more
Large language models (LLMs) have achieved remarkable progress in code generation, yet their potential for software protection remains largely...
Faezeh Hosseini, Mohammadali Yousefzadeh, Yadollah Yaghoobzadeh
Figurative language, particularly fixed figurative expressions (FFEs) such as idioms and proverbs, poses persistent challenges for large language...
Bharath Krishnamurthy, Ajita Rattani
Morphing techniques generate artificial biometric samples that combine features from multiple individuals, allowing each contributor to be verified...
Nourin Shahin, Izzat Alsmadi
As large language models (LLMs) move from research prototypes to enterprise systems, their security vulnerabilities pose serious risks to data...
Xiangyang Zhu, Yuan Tian, Zicheng Zhang +6 more
Large vision-language models (LVLMs) exhibit remarkable capabilities in cross-modal tasks but face significant safety challenges, which undermine...
Quy-Anh Dang, Chris Ngo
Despite significant progress in alignment, large language models (LLMs) remain vulnerable to adversarial attacks that elicit harmful behaviors....
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