2,560+ academic papers on AI security, attacks, and defenses
Showing 2201–2220 of 2,560 papers
Guangyu Lin, Li Lin, Christina P. Walker +2 more
The rapid proliferation of AI-generated content, driven by advances in generative adversarial networks, diffusion models, and multimodal large...
Dimitris Stefanopoulos, Andreas Voskou
This report presents the winning solution for Task 1 of Colliding with Adversaries: A Challenge on Robust Learning in High Energy Physics Discovery...
David Peer, Sebastian Stabinger
Large Language Models (LLMs) have demonstrated impressive capabilities, yet their deployment in high-stakes domains is hindered by inherent...
Shuai Li, Kejiang Chen, Jun Jiang +5 more
Large Language Models (LLMs) have demonstrated remarkable capabilities, but their training requires extensive data and computational resources,...
Mohammad Abdul Rehman, Syed Imad Ali Shah, Abbas Anwar +2 more
The remarkable capabilities of Large Language Models (LLMs) in natural language understanding and generation have sparked interest in their potential...
Sarah Egler, John Schulman, Nicholas Carlini
Large Language Model (LLM) providers expose fine-tuning APIs that let end users fine-tune their frontier LLMs. Unfortunately, it has been shown that...
Yang Feng, Xudong Pan
Malicious agents pose significant threats to the reliability and decision-making capabilities of Multi-Agent Systems (MAS) powered by Large Language...
Kate Glazko, Jennifer Mankoff
Generative AI risks such as bias and lack of representation impact people who do not interact directly with GAI systems, but whose content does:...
Owais Makroo, Siva Rajesh Kasa, Sumegh Roychowdhury +4 more
Membership Inference Attacks (MIAs) pose a critical privacy threat by enabling adversaries to determine whether a specific sample was included in a...
Shiwen Ou, Yuwei Li, Lu Yu +6 more
Deep learning (DL) frameworks serve as the backbone for a wide range of artificial intelligence applications. However, bugs within DL frameworks can...
Eduard Andrei Cristea, Petter Molnes, Jingyue Li
Malicious software attacks are having an increasingly significant economic impact. Commercial malware detection software can be costly, and tools...
Yao Huang, Yitong Sun, Yichi Zhang +3 more
Despite the remarkable advances of Large Language Models (LLMs) across diverse cognitive tasks, the rapid enhancement of these capabilities also...
Yuexiao Liu, Lijun Li, Xingjun Wang +1 more
Recent advancements in Reinforcement Learning with Verifiable Rewards (RLVR) have gained significant attention due to their objective and verifiable...
Muslim Chochlov, Gul Aftab Ahmed, James Vincent Patten +4 more
Source code clones pose risks ranging from intellectual property violations to unintended vulnerabilities. Effective and efficient scalable clone...
Hanbin Hong, Shuya Feng, Nima Naderloui +6 more
Large Language Models (LLMs) have rapidly become integral to real-world applications, powering services across diverse sectors. However, their...
Shuang Liang, Zhihao Xu, Jialing Tao +2 more
Despite extensive alignment efforts, Large Vision-Language Models (LVLMs) remain vulnerable to jailbreak attacks, posing serious safety risks. To...
Luca Belli, Kate Bentley, Will Alexander +5 more
We introduce VERA-MH (Validation of Ethical and Responsible AI in Mental Health), an automated evaluation of the safety of AI chatbots used in mental...
Ahmed Aly, Essam Mansour, Amr Youssef
Advanced Persistent Threats (APTs) are stealthy cyberattacks that often evade detection in system-level audit logs. Provenance graphs model these...
Issam Seddik, Sami Souihi, Mohamed Tamaazousti +1 more
As Large Language Models (LLMs) gain traction across critical domains, ensuring secure and trustworthy training processes has become a major concern....
Deyue Zhang, Dongdong Yang, Junjie Mu +6 more
Multimodal large language models (MLLMs) exhibit remarkable capabilities but remain susceptible to jailbreak attacks exploiting cross-modal...
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