2,589+ academic papers on AI security, attacks, and defenses
Showing 1601–1620 of 2,589 papers
Junjun Pan, Yixin Liu, Rui Miao +5 more
Large language model (LLM)-based multi-agent systems (MAS) have shown strong capabilities in solving complex tasks. As MAS become increasingly...
Haotian Deng, Chris Farber, Jiyoon Lee +1 more
Automated short-answer grading (ASAG) remains a challenging task due to the linguistic variability of student responses and the need for nuanced,...
Bin Wang, Wenjie Yu, Yilu Zhong +6 more
Large language models (LLMs) for code generation are becoming integral to modern software development, but their real-world prevalence and security...
Sumanth Bharadwaj Hachalli Karanam, Dhiwahar Adhithya Kennady
Manual software beta testing is costly and time-consuming, while single-agent large language model (LLM) approaches suffer from hallucinations and...
Scott Thornton
AI coding assistants produce vulnerable code in 45\% of security-relevant scenarios~\cite{veracode2025}, yet no public training dataset teaches both...
Ziqi Lin, Taiyu Hou
The use of large language model (LLM)-based AI chatbots among college students has increased rapidly, yet little is known about how individual...
Zehao Liu, Xi Lin
Large Language Models (LLMs) have gained considerable popularity and protected by increasingly sophisticated safety mechanisms. However, jailbreak...
Yueqiao Jin, Roberto Martinez-Maldonado, Dragan Gašević +1 more
Generative AI is increasingly embedded in collaborative learning, yet little is known about how AI personas shape learner agency when AI teammates...
Wei Qian, Chenxu Zhao, Yangyi Li +1 more
The rapid advancements in artificial intelligence (AI) have primarily focused on the process of learning from data to acquire knowledgeable learning...
Wang Bin, Ao Yang, Kedan Li +5 more
In the domain of software security testing, Directed Grey-Box Fuzzing (DGF) has garnered widespread attention for its efficient target localization...
Tung-Ling Li, Yuhao Wu, Hongliang Liu
Reward models and LLM-as-a-Judge systems are central to modern post-training pipelines such as RLHF, DPO, and RLAIF, where they provide scalar...
Yidong Chai, Yi Liu, Mohammadreza Ebrahimi +2 more
Social media platforms are plagued by harmful content such as hate speech, misinformation, and extremist rhetoric. Machine learning (ML) models are...
Abhivansh Gupta
As LLM-based agents grow more autonomous and multi-modal, ensuring they remain controllable, auditable, and faithful to deployer intent becomes...
Baolei Zhang, Minghong Fang, Zhuqing Liu +5 more
Federated Learning (FL) allows multiple clients to collaboratively train a model without sharing their private data. However, FL is vulnerable to...
Huixin Zhan
Genomic Foundation Models (GFMs), such as Evolutionary Scale Modeling (ESM), have demonstrated remarkable success in variant effect prediction....
Tomáš Souček, Pierre Fernandez, Hady Elsahar +5 more
Invisible watermarking is essential for tracing the provenance of digital content. However, training state-of-the-art models remains notoriously...
Nenad Tomašev, Matija Franklin, Julian Jacobs +2 more
AI safety and alignment research has predominantly been focused on methods for safeguarding individual AI systems, resting on the assumption of an...
Kai Hu, Abhinav Aggarwal, Mehran Khodabandeh +6 more
This paper introduces Jailbreak-Zero, a novel red teaming methodology that shifts the paradigm of Large Language Model (LLM) safety evaluation from a...
Xiao Li, Yue Li, Hao Wu +4 more
As large language models (LLMs) are increasingly adopted for code vulnerability detection, their reliability and robustness across diverse...
Himanshu Gharat, Himanshi Agrawal, Gourab K. Patro
Large Language Models (LLMs) have empowered AI agents with advanced capabilities for understanding, reasoning, and interacting across diverse tasks....
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