most citedMind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia

3 citations · 9 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CR2025

REDEditing: Relationship-Driven Precise Backdoor Poisoning on Text-to-Image Diffusion Models

Chongye Guo, Jinhu Fu, Junfeng Fang +2

The rapid advancement of generative AI highlights the importance of text-to-image (T2I) security, particularly with the threat of backdoor poisoning. Timely disclosure and mitigati…

cs.LG2025

SafeMLRM: Demystifying Safety in Multi-modal Large Reasoning Models

Junfeng Fang, Yukai Wang, Ruipeng Wang +5

The rapid advancement of multi-modal large reasoning models (MLRMs) -- enhanced versions of multimodal language models (MLLMs) equipped with reasoning capabilities -- has revolutio…

cs.CV2025

ACE: Concept Editing in Diffusion Models without Performance Degradation

Ruipeng Wang, Junfeng Fang, Jiaqi Li +4

Diffusion-based text-to-image models have demonstrated remarkable capabilities in generating realistic images, but they raise societal and ethical concerns, such as the creation of…

cs.AI2025

AgentSafe: Safeguarding Large Language Model-based Multi-agent Systems via Hierarchical Data Management

Junyuan Mao, Fanci Meng, Yifan Duan +6

Large Language Model based multi-agent systems are revolutionizing autonomous communication and collaboration, yet they remain vulnerable to security threats like unauthorized acce…

cs.AI2024★ 3 cited

Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia

Miao Yu, Junyuan Mao, Guibin Zhang +7

Research into the external behaviors and internal mechanisms of large language models (LLMs) has shown promise in addressing complex tasks in the physical world. Studies suggest th…

cs.CL2024★ 2 cited

AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models

Junfeng Fang, Houcheng Jiang, Kun Wang +5

Large language models (LLMs) often exhibit hallucinations due to incorrect or outdated knowledge. Hence, model editing methods have emerged to enable targeted knowledge updates. To…

cs.LG2024★ 1 cited

EXGC: Bridging Efficiency and Explainability in Graph Condensation

Junfeng Fang, Xinglin Li, Yongduo Sui +5

Graph representation learning on vast datasets, like web data, has made significant strides. However, the associated computational and storage overheads raise concerns. In sight of…

q-bio.QM2024★ 3 cited

MolTC: Towards Molecular Relational Modeling In Language Models

Junfeng Fang, Shuai Zhang, Chang Wu +6

Molecular Relational Learning (MRL), aiming to understand interactions between molecular pairs, plays a pivotal role in advancing biochemical research. Recently, the adoption of la…