2,077+ academic papers on AI security, attacks, and defenses
Showing 121–140 of 355 papers
Clear filtersAkriti Vij, Benjamin Chua, Darshini Ramiah +43 more
As frontier AI models are deployed globally, it is essential that their behaviour remains safe and reliable across diverse linguistic and cultural...
Kristen Moore, Diksha Goel, Cody James Christopher +5 more
Realistic network traffic simulation is critical for evaluating intrusion detection systems, stress-testing network protocols, and constructing...
Xiaonan Jing, Gongqing Wu, Xingrui Zhuo +2 more
Open-domain Relational Triplet Extraction (ORTE) is the foundation for mining structured knowledge without predefined schemas. Despite the impressive...
Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim +6 more
Large language models (LLMs) are increasingly used as judges to evaluate agent performance, particularly in non-verifiable settings where judgments...
Linbo Cao, Lihao Sun, Yang Yue
Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of actions with real-world impacts beyond text generation. While...
Yiyang Lu, Jinwen He, Yue Zhao +2 more
Large Language Models (LLMs) are widely integrated into interactive systems such as dialogue agents and task-oriented assistants. This growing...
Johannes Kaiser, Alexander Ziller, Eleni Triantafillou +2 more
Individual Differential Privacy (iDP) promises users control over their privacy, but this promise can be broken in practice. We reveal a previously...
Wenqi Zhang, Yulin Shen, Changyue Jiang +3 more
Large foundation models are integrated into Computer Use Agents (CUAs), enabling autonomous interaction with operating systems through graphical user...
Arunkumar V, Gangadharan G. R., Rajkumar Buyya
Artificial Intelligence is moving from models that only generate text to Agentic AI, where systems behave as autonomous entities that can perceive,...
Huanyi Ye, Jiale Guo, Ziyao Liu +1 more
RAG has emerged as a key technique for enhancing response quality of LLMs without high computational cost. In traditional architectures, RAG services...
Yixuan Du, Chenxiao Yu, Haoyan Xu +3 more
Vision-Language Models (VLMs) are rapidly replacing unimodal encoders in modern retrieval and recommendation systems. While their capabilities are...
Xiaomei Zhang, Zhaoxi Zhang, Leo Yu Zhang +3 more
Visual token compression is widely adopted to improve the inference efficiency of Large Vision-Language Models (LVLMs), enabling their deployment in...
Jun 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...
Jun 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...
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