2,529+ academic papers on AI security, attacks, and defenses
Showing 181–200 of 2,529 papers
Zhaohui Geoffrey Wang
Automated code vulnerability detection is critical for software security, yet existing approaches face a fundamental trade-off between detection...
Guilin Deng, Silong Chen, Yuchuan Luo +6 more
Federated Large Language Models (FedLLMs) enable multiple parties to collaboratively fine-tune LLMs without sharing raw data, addressing challenges...
Jesse Zymet, Andy Luo, Swapnil Shinde +2 more
Many approaches to LLM red-teaming leverage an attacker LLM to discover jailbreaks against a target. Several of them task the attacker with...
Irti Haq, Belén Saldías
As state-of-the-art Large Language Models (LLMs) have become ubiquitous, ensuring equitable performance across diverse demographics is critical....
Ari Azarafrooz
AI-agent guardrails are memoryless: each message is judged in isolation, so an adversary who spreads a single attack across dozens of sessions slips...
Mohammad Farhad, Shuvalaxmi Dass
Software security relies on effective vulnerability detection and patching, yet determining whether a patch fully eliminates risk remains an...
Yannis Belkhiter, Giulio Zizzo, Sergio Maffeis +2 more
The growth of agentic AI has drawn significant attention to function calling Large Language Models (LLMs), which are designed to extend the...
Mikko Lempinen, Joni Kemppainen, Niklas Raesalmi
As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of...
Hanzhi Liu, Chaofan Shou, Xiaonan Liu +4 more
LLM agents have begun to find real security vulnerabilities that human auditors and automated fuzzers missed for decades, in source-available targets...
Krishiv Agarwal, Ramneet Kaur, Colin Samplawski +6 more
Effective safety auditing of large language models (LLMs) demands tools that go beyond black-box probing and systematically uncover vulnerabilities...
Hoang Nguyen, Lu Wang, Marta Gaia Bras
Freight brokerages negotiate thousands of carrier rates daily under dynamic pricing conditions where models frequently revise targets...
Abhijit Talluri
Adversarial robustness evaluation underpins every claim of trustworthy ML deployment, yet the field suffers from fragmented protocols and undetected...
Yuhang Wu, Qinyuan Liu, Qiuyang Zhao +1 more
Currently, Large Language Models (LLMs) feature a diversified architectural landscape, including traditional Transformer, GateDeltaNet, and Mamba....
Nandakrishna Giri, Asmitha K. A., Serena Nicolazzo +2 more
Machine learning-based static malware detectors remain vulnerable to adversarial evasion techniques, such as metamorphic engine mutations. To address...
Pranav Pallerla, Wilson Naik Bhukya, Bharath Vemula +1 more
Retrieval-augmented generation (RAG) systems are increasingly deployed in sensitive domains such as healthcare and law, where they rely on private,...
Yingyong Hou, Xinyuan Lao, Huimei Wang +10 more
Background: Agent skills are increasingly deployed as modular, reusable capability units in AI agent systems. Medical research agent skills require...
Chao Pan, Yu Wu, Xin Yao
Internal Safety Collapse (ISC) is a failure mode in which frontier LLMs, when executing legitimate professional tasks whose correct completion...
He Yang Yuan, Xin Wang, Kundi Yao +3 more
Logging code plays an important role in software systems by recording key events and behaviors, which are essential for debugging and monitoring....
Ronghao Ni, Mihai Christodorescu, Limin Jia
The rapidly evolving Node$.$js ecosystem currently includes millions of packages and is a critical part of modern software supply chains, making...
Patrick Vossler, Jean Feng, Venkat Sivaraman +9 more
Hospital Quality Improvement (QI) plays a critical role in optimizing healthcare delivery by translating high-level hospital goals into actionable...
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