2,077+ academic papers on AI security, attacks, and defenses
Showing 361–380 of 809 papers
Clear filtersBinh Nguyen, Thai Le
Audio Language Models (ALMs) offer a promising shift towards explainable audio deepfake detections (ADDs), moving beyond \textit{black-box}...
Xiao Lin, Philip Li, Zhichen Zeng +6 more
Despite rich safety alignment strategies, large language models (LLMs) remain highly susceptible to jailbreak attacks, which compromise safety...
Zhakshylyk Nurlanov, Frank R. Schmidt, Florian Bernard
As Large Language Models (LLMs) are increasingly deployed in safety-critical domains, rigorously evaluating their robustness against adversarial...
Bocheng Chen, Xi Chen, Han Zi +5 more
Identifying specific moral errors in an input and generating appropriate corrections require moral sensitivity in large language models (LLMs), which...
Xi Wang, Songlei Jian, Shasha Li +5 more
Despite extensive safety alignment, Large Language Models (LLMs) often fail against jailbreak attacks. While machine unlearning has emerged as a...
Yuetian Chen, Yuntao Du, Kaiyuan Zhang +4 more
Most membership inference attacks (MIAs) against Large Language Models (LLMs) rely on global signals, like average loss, to identify training data....
Dinghong Song, Zhiwei Xu, Hai Wan +3 more
Model quantization is critical for deploying large language models (LLMs) on resource-constrained hardware, yet recent work has revealed severe...
Scott Thornton
Large language models remain vulnerable to jailbreak attacks, and single-layer defenses often trade security for usability. We present TRYLOCK, the...
Ahmed Ahmed, A. Feder Cooper, Sanmi Koyejo +1 more
Many unresolved legal questions over LLMs and copyright center on memorization: whether specific training data have been encoded in the model's...
Devang Kulshreshtha, Hang Su, Chinmay Hegde +1 more
Most jailbreak methods achieve high attack success rates (ASR) but require attacker LLMs to craft adversarial queries and/or demand high query...
Neusha Javidnia, Ruisi Zhang, Ashish Kundu +1 more
We present SWaRL, a robust and fidelity-preserving watermarking framework designed to protect the intellectual property of code LLM owners by...
Alexandre Le Mercier, Chris Develder, Thomas Demeester
State space models (SSMs) like Mamba offer efficient alternatives to Transformer-based language models, with linear time complexity. Yet, their...
Alexandre Le Mercier, Chris Develder, Thomas Demeester
State space models (SSMs) like Mamba offer efficient alternatives to Transformer-based language models, with linear time complexity. Yet, their...
Jiwei Guan, Haibo Jin, Haohan Wang
Recent advancements in Large Vision-Language Models (LVLMs) have shown groundbreaking capabilities across diverse multimodal tasks. However, these...
Davis Brown, Juan-Pablo Rivera, Dan Hendrycks +1 more
As frontier AIs become more powerful and costly to develop, adversaries have increasing incentives to steal model weights by mounting exfiltration...
Jiajie Zhu, Xia Du, Xiaoyuan Liu +4 more
The rapid advancements in artificial intelligence have significantly accelerated the adoption of speech recognition technology, leading to its...
M P V S Gopinadh, S Mahaboob Hussain
Large Language Models (LLMs) are integral to modern AI applications, but their safety alignment mechanisms can be bypassed through adversarial prompt...
Zhenhong Zhou, Shilinlu Yan, Chuanpu Liu +3 more
Large language models (LLMs) are increasingly deployed in cost-sensitive and on-device scenarios, and safety guardrails have advanced mainly in...
Md Mahbub Hasan, Marcus Sternhagen, Krishna Chandra Roy
Additive manufacturing (AM) is rapidly integrating into critical sectors such as aerospace, automotive, and healthcare. However, this cyber-physical...
Nandish Chattopadhyay, Abdul Basit, Amira Guesmi +3 more
Adversarial attacks pose a significant challenge to the reliable deployment of machine learning models in EdgeAI applications, such as autonomous...
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