activity
20242026
most citedAdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting

1 citations · 3 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CR2026

Reverse-Engineering Model Editing on Language Models

Zhiyu Sun, Minrui Luo, Yu Wang +2

Large language models (LLMs) are pretrained on corpora containing trillions of tokens and, therefore, inevitably memorize sensitive information. Locate-then-edit methods, as a main…

cs.CR2025

Fine-Tuning Jailbreaks under Highly Constrained Black-Box Settings: A Three-Pronged Approach

Xiangfang Li, Yu Wang, Bo Li

With the rapid advancement of large language models (LLMs), ensuring their safe use becomes increasingly critical. Fine-tuning is a widely used method for adapting models to downst…

cs.CL2025

Positional Encoding via Token-Aware Phase Attention

Yu Wang, Sheng Shen, Rémi Munos +2

We prove under practical assumptions that Rotary Positional Embedding (RoPE) introduces an intrinsic distance-dependent bias in attention scores that limits RoPE's ability to model…

cs.CL2025★ 1 cited

ZPD-SCA: Unveiling the Blind Spots of LLMs in Assessing Students' Cognitive Abilities

Wenhan Dong, Zhen Sun, Yuemeng Zhao +9

Large language models (LLMs) have demonstrated potential in educational applications, yet their capacity to accurately assess the cognitive alignment of reading materials with stud…

cs.LG2025

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

Kejia Chen, Jiawen Zhang, Jiacong Hu +4

Quantized large language models (LLMs) have gained increasing attention and significance for enabling deployment in resource-constrained environments. However, emerging studies on…

cs.CR2025★ 1 cited

LLM Access Shield: Domain-Specific LLM Framework for Privacy Policy Compliance

Yu Wang, Cailing Cai, Zhihua Xiao +1

Large language models (LLMs) are increasingly applied in fields such as finance, education, and governance due to their ability to generate human-like text and adapt to specialized…

cs.CL2025

EfficientLLM: Efficiency in Large Language Models

Zhengqing Yuan, Weixiang Sun, Yixin Liu +13

Large Language Models (LLMs) have driven significant progress, yet their growing parameter counts and context windows incur prohibitive compute, energy, and monetary costs. We intr…

cs.CR2024

Visual-RolePlay: Universal Jailbreak Attack on MultiModal Large Language Models via Role-playing Image Character

Siyuan Ma, Weidi Luo, Yu Wang +1

With the advent and widespread deployment of Multimodal Large Language Models (MLLMs), ensuring their safety has become increasingly critical. To achieve this objective, it require…

cs.CR2024★ 1 cited

AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting

Yu Wang, Xiaogeng Liu, Yu Li +2

With the advent and widespread deployment of Multimodal Large Language Models (MLLMs), the imperative to ensure their safety has become increasingly pronounced. However, with the i…