2,583+ academic papers on AI security, attacks, and defenses
Showing 101–120 of 740 papers
Clear filtersYuchen Chen, Yuan Xiao, Chunrong Fang +2 more
The proliferation of large language models for code (CodeLMs) and open-source contributions has heightened concerns over unauthorized use of source...
Wenbo Hu, Xin Chen, Yan Gao-Tian +3 more
Group Relative Policy Optimization (GRPO) has emerged as the de facto Reinforcement Learning (RL) objective driving recent advancements in Multimodal...
Runpeng Geng, Chenlong Yin, Yanting Wang +2 more
Prompt injection attacks pose serious security risks across a wide range of real-world applications. While receiving increasing attention, the...
Wenhao Yuan, Chenchen Lin, Jian Chen +3 more
In large language model (LLM) agents, reasoning trajectories are treated as reliable internal beliefs for guiding actions and updating memory....
Aryaman Arora, Zhengxuan Wu, Jacob Steinhardt +1 more
In language model interpretability research, \textbf{circuit tracing} aims to identify which internal features causally contributed to a particular...
Yu Liang, Liangxin Liu, Longzheng Wang +5 more
Generative reward models (GRMs) have emerged as a promising approach for aligning Large Language Models (LLMs) with human preferences by offering...
Hanyi Liu, Zhonghao Jiu, Minghao Wang +2 more
Implicit artistic influence, although visually plausible, is often undocumented and thus poses a historically constrained attribution problem:...
Yuanhang Li
Operating LEO mega-constellations requires translating high-level operator intents ("reroute financial traffic away from polar links under 80 ms")...
Phan The Duy, Nguyen Viet Duy, Khoa Ngo-Khanh +2 more
While recent approaches leverage large language models (LLMs) and multi-agent pipelines to automatically generate proof-of-concept (PoC) exploits...
Baoshun Tong, Haoran He, Ling Pan +2 more
Vision-Language-Action (VLA) models have achieved remarkable success in robotic manipulation. However, their robustness to linguistic nuances remains...
Geert Trooskens, Aaron Karlsberg, Anmol Sharma +6 more
We study compiled AI, a paradigm in which large language models generate executable code artifacts during a compilation phase, after which workflows...
Cheng Xu, Changhong Jin, Yingjie Niu +5 more
The rapid development of Large Language Models (LLMs) has transformed fake news detection and fact-checking tasks from simple classification to...
Houzhe Wang, Xiaojie Zhu, Chi Chen
With the increasing importance of data privacy and security, federated unlearning has emerged as a novel research field dedicated to ensuring that...
Kanishk Jain, Qian Yang, Shravan Nayak +3 more
Vision-language Models (VLMs), despite achieving strong performance on multimodal benchmarks, often misinterpret straightforward visual concepts that...
Zhuohao Yu, Zhiwei Steven Wu, Adam Block
Inference-time compute scaling has emerged as a powerful paradigm for improving language model performance on a wide range of tasks, but the question...
Jia Chengyu, AprilPyone MaungMaung, Huy H. Nguyen +2 more
Recent advances in vision-language models (VLMs) trained on web-scale image-text pairs have enabled impressive zero-shot transfer across a diverse...
Shuyao Gao, Minghao Huang
The deployment of Large Language Models (LLMs) has ignited concerns about technological unemployment. Existing task-based evaluations predominantly...
Abinitha Gourabathina, Inkit Padhi, Manish Nagireddy +2 more
For Large Language Models (LLMs) to be reliably deployed, models must effectively know when not to answer: abstain. Reasoning models, in particular,...
Jaemin Kim, Jae O Lee, Sumyeong Ahn +1 more
Retrieval-Augmented Language Models (RALMs) have demonstrated significant potential in knowledge-intensive tasks; however, they remain vulnerable to...
Matteo Migliarini, Joaquin Pereira Pizzini, Luca Moresca +3 more
Instrumental convergence predicts that sufficiently advanced AI agents will resist shutdown, yet current safety training (RLHF) may obscure this risk...
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