2,529+ academic papers on AI security, attacks, and defenses
Showing 221–240 of 294 papers
Clear filtersYanzhen Lu, Muchen Jiang, Zhicheng Qian +1 more
Prompt-injected memory can improve reasoning without updating model weights, but it also creates a control problem: retrieved content helps only when...
Ziyang Liu
Hosted-LLM providers have a silent-substitution incentive: advertise a stronger model while serving cheaper replies. Probe-after-return schemes such...
Wentao Zhang, Yan Zhuang, ZhuHang Zheng +3 more
Existing jamming attacks on Retrieval-Augmented Generation (RAG) systems typically induce explicit refusals or denial-of-service behaviors, which are...
Sua Lee, Sanghee Park, Jinbae Im
Multimodal Large Language Models (MLLMs) have been increasingly used as automatic evaluators-a paradigm known as MLLM-as-a-Judge. However, their...
Jin Zhao, Marta Knežević, Tanja Käser
Large Language Models (LLMs) are increasingly used in education, yet their default helpfulness often conflicts with pedagogical principles. Prior...
Hu Wei
AI agent systems increasingly rely on reusable non-LLM engineering infrastructure that packages tool mediation, context handling, delegation, safety...
Dongcheng Zhang, Yiqing Jiang
Existing AI agent safety benchmarks focus on generic criminal harm (cybercrime, harassment, weapon synthesis), leaving a systematic blind spot for a...
Xingyu Liu, Zengqin Huang, Xiang Gao +1 more
Fuzz testing of software libraries relies on fuzz drivers to invoke library APIs. Traditionally, these drivers are written manually by developers - a...
Parteek Jamwal, Minghao Shao, Boyuan Chen +15 more
Large Language Models (LLMs) have demonstrated remarkable capabilities across various cybersecurity tasks, including vulnerability classification,...
Ziyao Tang, Pengkun Jiao, Bin Zhu +3 more
Video Large Language Models (Vid-LLMs) have demonstrated remarkable performance in video understanding tasks, yet their robustness under...
Ting Zhang, Yikun Li, Chengran Yang +15 more
Software vulnerabilities remain one of the most persistent threats to modern digital infrastructure. While static application security testing (SAST)...
Shozo Saeki, Minoru Kawahara, Hirohisa Aman
A nearest-neighbor framework is a fundamental tool for various applications involving Large Language Models (LLMs) and Visual Language Models (VLMs)....
Yuan Fang, Yiming Luo, Aimin Zhou +1 more
Ensuring the safety of large language models (LLMs) requires robust red teaming, yet the systematic synthesis of high-quality toxic data remains...
Yihao Zou, Tianming Zheng, Futai Zou +1 more
Fuzzing has become a widely adopted technique for vulnerability discovery, yet it remains ineffective for structured-input programs due to strict...
Khang Tran, Khoa Nguyen, Cristian Borcea +1 more
Recent advances in large language models for test case generation have improved branch coverage via prompt-engineered mutations. However, they still...
Ivan Bercovich, Ivgeni Segal, Kexun Zhang +3 more
We release Terminal Wrench, a subset of 331 terminal-agent benchmark environments, copied from the popular open benchmarks that are demonstrably...
Hailin Liu, Eugene Ilyushin, Jie Ni +1 more
Large language model (LLM) agents are vulnerable to prompt-injection attacks that propagate through multi-step workflows, tool interactions, and...
Jianming Tong, Hanshen Xiao, Krishna Kumar Nair +5 more
Multi-user virtual reality enables immersive interaction. However, rendering avatars for numerous participants on each headset incurs prohibitive...
Dongwook Lee, Eunwoo Song, Che Hyun Lee +2 more
While recent Spoken Language Models (SLMs) have been actively deployed in real-world scenarios, they lack the capability to discern Third-Party...
Rina Mishra, Gaurav Varshney, Doddipatla Sesha Sahithi
The rapid adoption of open-source Large Language Models (LLMs) in offline and enterprise environments has introduced a largely unexamined security...
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