2,560+ academic papers on AI security, attacks, and defenses
Showing 221–240 of 442 papers
Clear filtersJun Liu, Leo Yu Zhang, Fengpeng Li +2 more
Hard-label black-box settings, where only top-1 predicted labels are observable, pose a fundamentally constrained yet practically important feedback...
Greta Dolcetti, Giulio Zizzo, Sergio Maffeis
We present an experimental evaluation that assesses the robustness of four open source LLMs claiming function-calling capabilities against three...
Ziqi Ding, Yunfeng Wan, Wei Song +7 more
CAPTCHAs are widely used by websites to block bots and spam by presenting challenges that are easy for humans but difficult for automated programs to...
Seong-Gyu Park, Sohee Park, Jisu Lee +2 more
Recent LLMs increasingly integrate reasoning mechanisms like Chain-of-Thought (CoT). However, this explicit reasoning exposes a new attack surface...
Erin Feiglin, Nir Hutnik, Raz Lapid
We investigate a failure mode of large language models (LLMs) in which plain-text prompts elicit excessive outputs, a phenomenon we term Overflow....
Dongryeol Lee, Yerin Hwang, Taegwan Kang +3 more
While large language models (LLMs) are increasingly used as automatic judges for question answering (QA) and other reference-conditioned evaluation...
Weipeng Jiang, Xiaoyu Zhang, Juan Zhai +3 more
Emoticons are widely used in digital communication to convey affective intent, yet their safety implications for Large Language Models (LLMs) remain...
Ying Zhou, Jiacheng Wei, Yu Qi +2 more
Large language models (LLMs) demonstrate remarkable capabilities in natural language understanding and generation. Despite being trained on...
Vasanth Iyer, Leonardo Bobadilla, S. S. Iyengar
Large Language Models (LLMs) such as Gemma-2B have shown strong performance in various natural language processing tasks. However, general-purpose...
Qiang Zhang, Elena Emma Wang, Jiaming Li +1 more
This study presents a Secure Multi-Tenant Architecture (SMTA) combined with a novel concept Burn-After-Use (BAU) mechanism for enterprise LLM...
Minfeng Qi, Dongyang He, Qin Wang +1 more
Visual Reasoning CAPTCHAs (VRCs) combine visual scenes with natural-language queries that demand compositional inference over objects, attributes,...
Keyang Zhang, Zeyu Chen, Xuan Feng +4 more
The security of scripting languages such as PowerShell is critical given their powerful automation and administration capabilities, often exercised...
Hoang-Chau Luong, Lingwei Chen
Low-Rank Adaptation (LoRA) is widely used for parameter-efficient fine-tuning of large language models, but it is notably ineffective at removing...
Tianshi Li
On December 4, 2025, Anthropic released Anthropic Interviewer, an AI tool for running qualitative interviews at scale, along with a public dataset of...
Zhi Yang, Runguo Li, Qiqi Qiang +15 more
Financial agents powered by large language models (LLMs) are increasingly deployed for investment analysis, risk assessment, and automated...
Suyash Mishra, Qiang Li, Srikanth Patil +1 more
Vision Language Models (VLMs) are poised to revolutionize the digital transformation of pharmacyceutical industry by enabling intelligent, scalable,...
Konstantinos E. Kampourakis, Vyron Kampourakis, Efstratios Chatzoglou +2 more
Realistic, large-scale, and well-labeled cybersecurity datasets are essential for training and evaluating Intrusion Detection Systems (IDS). However,...
Huawei Zheng, Xinqi Jiang, Sen Yang +3 more
Large language models (LLMs) are increasingly applied in specialized domains such as finance and healthcare, where they introduce unique safety...
Xiaoyu Xu, Minxin Du, Zitong Li +6 more
Although machine unlearning is essential for removing private, harmful, or copyrighted content from LLMs, current benchmarks often fail to faithfully...
Dinesh Srivasthav P, Ashok Urlana, Rahul Mishra +2 more
Machine unlearning aims to selectively remove the influence of specific training samples to satisfy privacy regulations such as the GDPR's 'Right to...
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