activity
20232026
most citedKnowledge Distillation in Federated Learning: a Survey on Long Lasting Challenges and New Solutions

18 citations · 61 across the 51 of their papers we have counts for

collaborators

55 papers

cs.CR2026

BASIS: Breach-Aware Selective Prompt Injection Shielding with Prefill Attention Probes

Laiqiao Qin, Tianqing Zhu, Longxiang Gao +1

Prompt injection is a critical security threat in large language model (LLM) applications, where attackers hijack model behavior by embedding malicious instructions in user or exte…

cs.CV2026

Dual Inversion for Text-to-Image Diffusion Models: From Both Prompt and Noise Perspectives

Xiaolong Liu, Junjian Li, Yuan Xiao +4

Prompt inversion, as a typical reverse engineering technique, enables text-to-image (T2I) diffusion models to generate the desired target images without extensive prompt engineerin…

cs.CV2026

Fundus Image-based Glaucoma Screening via Retinal Knowledge-Oriented Dynamic Multi-Level Feature Integration

Chi Liu, Yuzhuo Zhou, Sheng Shen +9

While deep learning has advanced automated glaucoma screening via color fundus photography, existing purely data-driven models often overfit to confounding imaging artifacts and st…

cs.CR2026

Osmosis Distillation: Model Hijacking with the Fewest Samples

Yuchen Shi, Huajie Chen, Heng Xu +6

Transfer learning is devised to leverage knowledge from pre-trained models to solve new tasks with limited data and computational resources. Meanwhile, dataset distillation has eme…

cs.MA2026

From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration

Yizhe Xie, Congcong Zhu, Xinyue Zhang +5

Large Language Model-based Multi-Agent Systems (LLM-MAS) are increasingly applied to complex collaborative scenarios. However, their collaborative mechanisms may cause minor inaccu…

cs.CR2026

Hide&Seek: Remove Image Watermarks with Negligible Cost via Pixel-wise Reconstruction

Huajie Chen, Tianqing Zhu, Hailin Yang +7

Watermarking has emerged as a key defense against the misuse of machine-generated images (MGIs). Yet the robustness of these protections remains underexplored. To reveal the limits…