:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Gai, Keke, Wang, Dongjue, Yu, Jing, Zhu, Liehuang, Wu, Qi
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2508.10315
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Adaptive Prototype Knowledge Transfer for Federated Learning with Mixed Modalities and Heterogeneous Tasks
by: Gai, Keke, et al.
Published: (2025)

Binary Linear Tree Commitment-based Ownership Protection for Distributed Machine Learning
by: Xie, Tianxiu, et al.
Published: (2024)

EASTER: Embedding Aggregation-based Heterogeneous Models Training in Vertical Federated Learning
by: Wang, Shuo, et al.
Published: (2023)

Vertical Federated Continual Learning via Evolving Prototype Knowledge
by: Wang, Shuo, et al.
Published: (2025)

Effective Backdoor Mitigation in Vision-Language Models Depends on the Pre-training Objective
by: Verma, Sahil, et al.
Published: (2023)

Mutual Information Guided Backdoor Mitigation for Pre-trained Encoders
by: Han, Tingxu, et al.
Published: (2024)

Secure and Efficient Watermarking for Latent Diffusion Models in Model Distribution Scenarios
by: Lei, Liangqi, et al.
Published: (2025)

AGATE: Stealthy Black-box Watermarking for Multimodal Model Copyright Protection
by: Gao, Jianbo, et al.
Published: (2025)

PCDiff: Proactive Control for Ownership Protection in Diffusion Models with Watermark Compatibility
by: Gai, Keke, et al.
Published: (2025)

Watermarking Visual Concepts for Diffusion Models
by: Lei, Liangqi, et al.
Published: (2024)

DiffuseTrace: A Transparent and Flexible Watermarking Scheme for Latent Diffusion Model
by: Lei, Liangqi, et al.
Published: (2024)

A2-DIDM: Privacy-preserving Accumulator-enabled Auditing for Distributed Identity of DNN Model
by: Xie, Tianxiu, et al.
Published: (2024)

Backdoor for Debias: Mitigating Model Bias with Backdoor Attack-based Artificial Bias
by: Wu, Shangxi, et al.
Published: (2023)

DeTrigger: A Gradient-Centric Approach to Backdoor Attack Mitigation in Federated Learning
by: Lee, Kichang, et al.
Published: (2024)

FLAIN: Mitigating Backdoor Attacks in Federated Learning via Flipping Weight Updates of Low-Activation Input Neurons
by: Ding, Binbin, et al.
Published: (2024)

Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning
by: Kim, Taejin, et al.
Published: (2023)

ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
by: Ren, Zhiyao, et al.
Published: (2025)

Structure-Aware Distributed Backdoor Attacks in Federated Learning
by: Jian, Wang, et al.
Published: (2026)

A Post-Training Enhanced Optimization Approach for Small Language Models
by: Zhai, Keke
Published: (2024)

Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking
by: Kong, Cong, et al.
Published: (2024)

Feedback-based Modal Mutual Search for Attacking Vision-Language Pre-training Models
by: Ding, Renhua, et al.
Published: (2024)

Exploiting Layer-Specific Vulnerabilities to Backdoor Attack in Federated Learning
by: Foroughi, Mohammad Hadi, et al.
Published: (2026)

Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)

Client-Side Patching against Backdoor Attacks in Federated Learning
by: Molina-Coronado, Borja
Published: (2024)

Heterogeneity-Aware Coordination for Federated Learning via Stitching Pre-trained blocks
by: Zhan, Shichen, et al.
Published: (2024)

Beyond Traditional Threats: A Persistent Backdoor Attack on Federated Learning
by: Liu, Tao, et al.
Published: (2024)

S$^2$ALM: Sequence-Structure Pre-trained Large Language Model for Comprehensive Antibody Representation Learning
by: Yin, Mingze, et al.
Published: (2024)

The Future of Large Language Model Pre-training is Federated
by: Sani, Lorenzo, et al.
Published: (2024)

Revisiting Pre-trained Language Models for Vulnerability Detection
by: Li, Youpeng, et al.
Published: (2025)

Practical Continual Forgetting for Pre-trained Vision Models
by: Zhao, Hongbo, et al.
Published: (2025)

Cooperative Backdoor Attack in Decentralized Reinforcement Learning with Theoretical Guarantee
by: Gao, Mengtong, et al.
Published: (2024)

Hypergraph Attacks via Injecting Homogeneous Nodes into Elite Hyperedges
by: He, Meixia, et al.
Published: (2024)

Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning
by: Shan, Junjie, et al.
Published: (2024)

Defending the Edge: Representative-Attention Defense against Backdoor Attacks in Federated Learning
by: Obioma, Chibueze Peace, et al.
Published: (2025)

Unlearn to Relearn Backdoors: Deferred Backdoor Functionality Attacks on Deep Learning Models
by: Shin, Jeongjin, et al.
Published: (2024)

Pre-trained Large Language Models Learn Hidden Markov Models In-context
by: Dai, Yijia, et al.
Published: (2025)

Symphony-MoE: Harmonizing Disparate Pre-trained Models into a Coherent Mixture-of-Experts
by: Wang, Qi, et al.
Published: (2025)

FedDefender: Backdoor Attack Defense in Federated Learning
by: Gill, Waris, et al.
Published: (2023)

Pre-trained Vision-Language Models Learn Discoverable Visual Concepts
by: Zang, Yuan, et al.
Published: (2024)

PNAct: Crafting Backdoor Attacks in Safe Reinforcement Learning
by: Guo, Weiran, et al.
Published: (2025)