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20242026
most citedSafety at Scale: A Comprehensive Survey of Large Model and Agent Safety

1 citations · 2 across the 13 of their papers we have counts for

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cs.CL2025

Self-Guided Adaptive Safety Alignment: Synthesizing and Internalizing Guidelines in Reasoning Models

Yuhang Wang, Yanxu Zhu, Jiaming Zhang +2

Explicit safety policies can improve reasoning-model safety, but their effective coverage may lag behind evolving jailbreak strategies. We study whether a reasoning model can synth…

cs.CV2025

NAP-Tuning: Neural Augmented Prompt Tuning for Adversarially Robust Vision-Language Models

Jiaming Zhang, Xin Wang, Xingjun Ma +3

Vision-Language Models (VLMs) such as CLIP have demonstrated remarkable capabilities in understanding relationships between visual and textual data through joint embedding spaces.…

cs.CR2025★ 1 cited

Can LLMs Handle WebShell Detection? Overcoming Detection Challenges with Behavioral Function-Aware Framework

Feijiang Han, Jiaming Zhang, Chuyi Deng +2

WebShell attacks - where adversaries implant malicious scripts on web servers - remain a persistent threat. Prior machine-learning and deep-learning detectors typically depend on t…

cs.LG2025

LagKV: Lag-Relative Information of the KV Cache Tells Which Tokens Are Important

Manlai Liang, JiaMing Zhang, Xiong Li +1

The increasing size of the Key-Value (KV) cache during the Large Language Models long-context inference is the main obstacle for its balance between the deployment cost and task ac…

cs.CR2025★ 1 cited

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety

Xingjun Ma, Yifeng Gao, Yixu Wang +45

The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape of Artifici…