2,583+ academic papers on AI security, attacks, and defenses
Showing 741–760 of 927 papers
Clear filtersNaseem Machlovi, Maryam Saleki, Ruhul Amin +5 more
As large language models (LLMs) become deeply embedded in daily life, the urgent need for safer moderation systems that distinguish between naive and...
Naseem Machlovi, Maryam Saleki, Ruhul Amin +5 more
As large language models (LLMs) become deeply embedded in daily life, the urgent need for safer moderation systems, distinguishing between naive from...
A. A. Gde Yogi Pramana, Jason Ray, Anthony Jaya +1 more
Vision--Language Models (VLMs) show significant promise for Medical Visual Question Answering (VQA), yet their deployment in clinical settings is...
Md Minhazul Islam Munna, Md Mahbubur Rahman, Jaroslav Frnda +2 more
The proliferation of IoT devices and their reliance on Wi-Fi networks have introduced significant security vulnerabilities, particularly the KRACK...
Kun Zhao, Siyuan Dai, Yingying Zhang +9 more
Early detection of Alzheimer's disease (AD) requires models capable of integrating macro-scale neuroanatomical alterations with micro-scale genetic...
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...
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...
Hao Li, Yubing Ren, Yanan Cao +3 more
Benefiting from the superior capabilities of large language models in natural language understanding and generation, Embeddings-as-a-Service (EaaS)...
Saksham Sahai Srivastava, Haoyu He
Large Language Model (LLM) agents increasingly rely on long-term memory and Retrieval-Augmented Generation (RAG) to persist experiences and refine...
Zhexi Lu, Hongliang Chi, Nathalie Baracaldo +3 more
Membership inference attacks (MIAs) pose a critical privacy threat to fine-tuned large language models (LLMs), especially when models are adapted to...
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