2,560+ academic papers on AI security, attacks, and defenses
Showing 301–320 of 558 papers
Clear filtersBibhabasu Mandal, Sagnik Nandy
In sensitive applications involving relational datasets, protecting information about individual links from adversarial queries is of paramount...
Omar Abdelnasser, Fatemah Alharbi, Khaled Khasawneh +2 more
Safety alignment in Language Models (LMs) is fundamental for trustworthy AI. However, while different stakeholders are trying to leverage Arabic...
Hao Li, Ruoyao Wen, Shanghao Shi +2 more
AI agents that autonomously interact with external tools and environments show great promise across real-world applications. However, the external...
Tomer Kordonsky, Maayan Yamin, Noam Benzimra +2 more
LLMs are increasingly used for code generation, but their outputs often follow recurring templates that can induce predictable vulnerabilities. We...
Najmul Hasan, Prashanth BusiReddyGari
The Uniform Resource Locator (URL), introduced in a connectivity-first era to define access and locate resources, remains historically limited,...
Rodrigo Tertulino, Ricardo Almeida, Laercio Alencar
The digitization of healthcare has generated massive volumes of Electronic Health Records (EHRs), offering unprecedented opportunities for training...
Hoang M. Ngo, Tre' R. Jeter, Incheol Shin +3 more
Quantum Machine Learning (QML) is becoming increasingly prevalent due to its potential to enhance classical machine learning (ML) tasks, such as...
Wenjin Hou, Wei Liu, Han Hu +3 more
Multimodal Large Language Models (MLLMs) have shown remarkable proficiency on general-purpose vision-language benchmarks, reaching or even exceeding...
Yen-Shan Chen, Zhi Rui Tam, Cheng-Kuang Wu +1 more
Current evaluations of LLM safety predominantly rely on severity-based taxonomies to assess the harmfulness of malicious queries. We argue that this...
Yangfan Deng, Anirudh Nakra, Min Wu
3D content acquisition and creation are expanding rapidly in the new era of machine learning and AI. 3D Gaussian Splatting (3DGS) has become a...
Max Manolov, Tony Gao, Siddharth Shukla +2 more
Large language models (LLMs) are increasingly used to assist developers with code, yet their implementations of cryptographic functionality often...
Shaowei Shen, Xiaohong Yang, Jie Yang +4 more
Electronic medical records (EMRs), particularly in neurology, are inherently heterogeneous, sparse, and noisy, which poses significant challenges for...
Shaowei Shen, Xiaohong Yang, Jie Yang +4 more
Electronic medical records (EMRs), particularly in neurology, are inherently heterogeneous, sparse, and noisy, which poses significant challenges for...
Abhilekh 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...
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