2,529+ academic papers on AI security, attacks, and defenses
Showing 121–140 of 142 papers
Clear filtersXinwei Wu, Heng Liu, Jiang Zhou +5 more
Large Language Models (LLMs) have advanced machine translation but remain vulnerable to hallucinations. Unfortunately, existing MT benchmarks are not...
Bin Wang, Zexin Liu, Hao Yu +6 more
The Model Context Protocol (MCP) has emerged as a standardized interface enabling seamless integration between Large Language Models (LLMs) and...
Ronghao Ni, Aidan Z. H. Yang, Min-Chien Hsu +5 more
Program analysis tools often produce large volumes of candidate vulnerability reports that require costly manual review, creating a practical...
Wu Yichao, Wang Yirui, Ding Panpan +3 more
With the wide application of deep reinforcement learning (DRL) techniques in complex fields such as autonomous driving, intelligent manufacturing,...
Wm. Matthew Kennedy, Cigdem Patlak, Jayraj Dave +10 more
AI systems have the potential to produce both benefits and harms, but without rigorous and ongoing adversarial evaluation, AI actors will struggle to...
Oleksandr Adamov, Anders Carlsson
This paper explores the challenges of cyberattack attribution, specifically APTs, applying the case study approach for the WhisperGate cyber...
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...
Francesco Giarrusso, Olga E. Sorokoletova, Vincenzo Suriani +1 more
Jailbreaking techniques pose a significant threat to the safety of Large Language Models (LLMs). Existing defenses typically focus on single-turn...
Zhenyu Mao, Jacky Keung, Fengji Zhang +3 more
The increasing demand for software development has driven interest in automating software engineering (SE) tasks using Large Language Models (LLMs)....
Vinay Bamil
Recent advances in large language models have enabled developers to generate software by conversing with artificial intelligence systems rather than...
Man Hu, Xinyi Wu, Zuofeng Suo +5 more
With the rise of advanced reasoning capabilities, large language models (LLMs) are receiving increasing attention. However, although reasoning...
Chongyu Fan, Changsheng Wang, Yancheng Huang +2 more
Machine unlearning for large language models (LLMs) aims to remove undesired data, knowledge, and behaviors (e.g., for safety, privacy, or copyright)...
Lorenzo Baraldi, Zifan Zeng, Chongzhe Zhang +9 more
The rapid progress in embodied artificial intelligence has highlighted the necessity for more advanced and integrated models that can perceive,...
Cade Houston Kennedy, Amr Hilal, Morteza Momeni
With the growth of digital financial systems, robust security and privacy have become a concern for financial institutions. Even though traditional...
Mizanur Rahman, Amran Bhuiyan, Mohammed Saidul Islam +5 more
Recent advances in large language models (LLMs) have enabled a new class of AI agents that automate multiple stages of the data science workflow by...
Niloofar Mireshghallah, Tianshi Li
The discourse on privacy risks in Large Language Models (LLMs) has disproportionately focused on verbatim memorization of training data, while a...
Guolei Huang, Qinzhi Peng, Gan Xu +3 more
As Vision-Language Models (VLMs) move into interactive, multi-turn use, safety concerns intensify for multimodal multi-turn dialogue, which is...
Kunlun Zhu, Zijia Liu, Bingxuan Li +15 more
Large Language Model (LLM) agents, which integrate planning, memory, reflection, and tool-use modules, have shown promise in solving complex,...
Dawei Li, Zhen Tan, Chengshuai Zhao +6 more
Large Language Model (LLM)-based judgments leverage powerful LLMs to efficiently evaluate candidate content and provide judgment scores. However, the...
Wenjie Fu, Huandong Wang, Junyao Gao +2 more
As Large Language Models (LLMs) achieve remarkable success across a wide range of applications, such as chatbots and code copilots, concerns...
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