2,529+ academic papers on AI security, attacks, and defenses
Showing 241–260 of 294 papers
Clear filtersMadhav Agarwal, Sotirios A. Tsaftaris, Laura Sevilla-Lara +1 more
Understanding emotions is a fundamental ability for intelligent systems to be able to interact with humans. Vision-language models (VLMs) have made...
XiangRui Zhang, Qiang Li, Haining Wang
Binary analysis increasingly relies on large language models (LLMs) to perform semantic reasoning over complex program behaviors. However, existing...
Haochun Tang, Yuliang Yan, Jiahua Lu +2 more
Cost-aware routing dynamically dispatches user queries to models of varying capability to balance performance and inference cost. However, the...
Xuanli He, Bilgehan Sel, Faizan Ali +3 more
Large Language Models (LLMs) are increasingly exposed to adaptive jailbreaking, particularly in high-stakes Chemical, Biological, Radiological, and...
Peifeng Zhang, Zice Qiu, Donghua Yu +4 more
In continual visual question answering (VQA), existing Continual Learning (CL) methods are mostly built for symmetric, unimodal architectures....
Meng Chen, Kun Wang, Li Lu +2 more
Modern Large audio-language models (LALMs) power intelligent voice interactions by tightly integrating audio and text. This integration, however,...
Firas Ben Hmida, Philemon Hailemariam, Kashif Ali Khan +1 more
Deep neural networks (DNNs) remain largely opaque at inference time, limiting our ability to detect and diagnose malicious input manipulations such...
Fortunatus Aabangbio Wulnye, Justice Owusu Agyemang, Kwame Opuni-Boachie Obour Agyekum +3 more
Ensuring the reliability of machine learning-based intrusion detection systems remains a critical challenge in Internet of Things (IoT) environments,...
Pavel Chizhov, Egor Bogomolov, Ivan P. Yamshchikov
Efficiency and safety of Large Language Models (LLMs), among other factors, rely on the quality of tokenization. A good tokenizer not only improves...
Djiré Albérick Euraste, Kaboré Abdoul Kader, Jordan Samhi +3 more
The lack of transparency about code datasets used to train large language models (LLMs) makes it difficult to detect, evaluate, and mitigate data...
Yi Ting Shen, Kentaroh Toyoda, Alex Leung
The rapid proliferation of Model Context Protocol (MCP)-based agentic systems has introduced a new category of security threats that existing...
Xixun Lin, Yang Liu, Yancheng Chen +9 more
The performance of large language model (LLM) agents depends critically on the execution harness, the system layer that orchestrates tool use,...
Aram Ebtekar, Michael K. Cohen
Reinforcement learners can attain high reward through novel unintended strategies. We study a Bayesian mitigation for general environments: we expand...
Xiaohua Wang, Muzhao Tian, Yuqi Zeng +20 more
Reinforcement Learning from Human Feedback (RLHF) and related alignment paradigms have become central to steering large language models (LLMs) and...
Shawn, Zhong, Junxuan Liao +4 more
AI coding agents operate directly on users' filesystems, where they regularly corrupt data, delete files, and leak secrets. Current approaches force...
Eun Woo Im, Dhruv Madhwal, Vivek Gupta
Vision-Language Models demonstrate remarkable capabilities but often struggle with compositional reasoning, exhibiting vulnerabilities regarding word...
Andrii Vakhnovskyi
The United States designates Food and Agriculture as one of sixteen critical infrastructure sectors, yet no mandatory cybersecurity requirements...
Sujan Ghimire, Parsa Mirfasihi, Muhtasim Alam Chowdhury +6 more
The globalization of integrated circuit (IC) design and manufacturing has increased the exposure of hardware intellectual property (IP) to untrusted...
Prajas Wadekar, Venkata Sai Pranav Bachina, Kunal Bhosikar +2 more
3D Gaussian Splatting (3DGS) has recently enabled highly photorealistic 3D reconstruction from casually captured multi-view images. However, this...
Syed Md Mukit Rashid, Abdullah Al Ishtiaq, Kai Tu +7 more
Logical vulnerabilities in software stem from flaws in program logic rather than memory safety, which can lead to critical security failures....
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