Cover Image

Can Distillation Mitigate Backdoor Attacks in Pre-trained Encoders?

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Han, TIngxu, Song, Wei, Sun, Weisong, Ding, Ziqi, Feng, Yebo, Fang, Chunrong, Li, Jun, Qian, Hanwei, Chen, Zhenyu, Liu, Yang
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Eliminating Backdoors in Neural Code Models for Secure Code Understanding
by: Sun, Weisong, et al.
Published: (2024)

APPT: Boosting Automated Patch Correctness Prediction via Fine-tuning Pre-trained Models
by: Zhang, Quanjun, et al.
Published: (2023)

A Prompt Learning Framework for Source Code Summarization
by: Xu, Tingting, et al.
Published: (2023)

Log-based, Business-aware REST API Testing
by: Yang, Ding, et al.
Published: (2026)

Enhancing and Reporting Robustness Boundary of Neural Code Models for Intelligent Code Understanding
by: Han, Tingxu, et al.
Published: (2026)

UOR: Universal Backdoor Attacks on Pre-trained Language Models
by: Du, Wei, et al.
Published: (2023)

Demonstration Attack against In-Context Learning for Code Intelligence
by: Ge, Yifei, et al.
Published: (2024)

Patronus: Identifying and Mitigating Transferable Backdoors in Pre-trained Language Models
by: Zhao, Tianhang, et al.
Published: (2025)

A Vision-Language Pre-training Model-Guided Approach for Mitigating Backdoor Attacks in Federated Learning
by: Gai, Keke, et al.
Published: (2025)

Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor
by: Wei, Shaokui, et al.
Published: (2024)

A Systematic Literature Review on Large Language Models for Automated Program Repair
by: Zhang, Quanjun, et al.
Published: (2024)

Commenting Higher-level Code Unit: Full Code, Reduced Code, or Hierarchical Code Summarization
by: Sun, Weisong, et al.
Published: (2025)

A Critical Review of Large Language Model on Software Engineering: An Example from ChatGPT and Automated Program Repair
by: Zhang, Quanjun, et al.
Published: (2023)

A Survey on Large Language Models for Software Engineering
by: Zhang, Quanjun, et al.
Published: (2023)

Securely Fine-tuning Pre-trained Encoders Against Adversarial Examples
by: Zhou, Ziqi, et al.
Published: (2024)

Debiasing LLMs by Masking Unfairness-Driving Attention Heads
by: Han, Tingxu, et al.
Published: (2025)

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

Secure Transfer Learning: Training Clean Models Against Backdoor in (Both) Pre-trained Encoders and Downstream Datasets
by: Zhang, Yechao, et al.
Published: (2025)

Unleashing the Power of Pre-trained Encoders for Universal Adversarial Attack Detection
by: Zhang, Yinghe, et al.
Published: (2025)

CooTest: An Automated Testing Approach for V2X Communication Systems
by: Guo, An, et al.
Published: (2024)

Not All Prompts Are Secure: A Switchable Backdoor Attack Against Pre-trained Vision Transformers
by: Yang, Sheng, et al.
Published: (2024)

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

Continuous Concepts Removal in Text-to-image Diffusion Models
by: Han, Tingxu, et al.
Published: (2024)

Pre-trained Model-based Actionable Warning Identification: A Feasibility Study
by: Ge, Xiuting, et al.
Published: (2024)

Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
by: Yang, Wenhan, et al.
Published: (2023)

INK: Inheritable Natural Backdoor Attack Against Model Distillation
by: Liu, Xiaolei, et al.
Published: (2023)

MBTSAD: Mitigating Backdoors in Language Models Based on Token Splitting and Attention Distillation
by: Ding, Yidong, et al.
Published: (2025)

SecureSplit: Mitigating Backdoor Attacks in Split Learning
by: Dou, Zhihao, et al.
Published: (2026)

Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing
by: Ding, Ruyi, et al.
Published: (2024)

Teaching Code LLMs to Use Autocompletion Tools in Repository-Level Code Generation
by: Wang, Chong, et al.
Published: (2024)

Probing Privacy Leaks in LLM-based Code Generation via Test Generation
by: Ge, Yifei, et al.
Published: (2026)

Security of Language Models for Code: A Systematic Literature Review
by: Chen, Yuchen, et al.
Published: (2024)

ToxicTextCLIP: Text-Based Poisoning and Backdoor Attacks on CLIP Pre-training
by: Yao, Xin, et al.
Published: (2025)

Protocol-agnostic and Data-free Backdoor Attacks on Pre-trained Models in RF Fingerprinting
by: Zhao, Tianya, et al.
Published: (2025)

SWE-Skills-Bench: Do Agent Skills Actually Help in Real-World Software Engineering?
by: Han, Tingxu, et al.
Published: (2026)

Show Me Your Code! Kill Code Poisoning: A Lightweight Method Based on Code Naturalness
by: Sun, Weisong, et al.
Published: (2025)

Source Code Summarization in the Era of Large Language Models
by: Sun, Weisong, et al.
Published: (2024)

Improving Deep Assertion Generation via Fine-Tuning Retrieval-Augmented Pre-trained Language Models
by: Zhang, Quanjun, et al.
Published: (2025)

Memory Reviving, Continuing Learning and Beyond: Evaluation of Pre-trained Encoders and Decoders for Multimodal Machine Translation
by: Yu, Zhuang, et al.
Published: (2025)