Adversarial Feature Map Pruning for Backdoor
Fuente:
arXiv
Saved in:
| Main Authors: | Huang, Dong, Bu, Qingwen |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Signature in Code Backdoor Detection, how far are we?
by: Le, Quoc Hung, et al.
Published: (2025)
by: Le, Quoc Hung, et al.
Published: (2025)
TopoMap: A Feature-based Semantic Discriminator of the Topographical Regions in the Test Input Space
by: De Vita, Gianmarco, et al.
Published: (2025)
by: De Vita, Gianmarco, et al.
Published: (2025)
PyTorch-based Geometric Learning with Non-CUDA Processing Units: Experiences from Intel Gaudi-v2 HPUs
by: Bu, Fanchen, et al.
Published: (2025)
by: Bu, Fanchen, et al.
Published: (2025)
Pruning the Unsurprising: Efficient LLM Reasoning via First-Token Surprisal
by: Zeng, Wenhao, et al.
Published: (2025)
by: Zeng, Wenhao, et al.
Published: (2025)
Engineering Resource-constrained Software Systems with DNN Components: a Concept-based Pruning Approach
by: Formica, Federico, et al.
Published: (2026)
by: Formica, Federico, et al.
Published: (2026)
Code Less, Align More: Efficient LLM Fine-tuning for Code Generation with Data Pruning
by: Tsai, Yun-Da, et al.
Published: (2024)
by: Tsai, Yun-Da, et al.
Published: (2024)
evomap: A Toolbox for Dynamic Mapping in Python
by: Matthe, Maximilian
Published: (2025)
by: Matthe, Maximilian
Published: (2025)
stable-pretraining-v1: Foundation Model Research Made Simple
by: Balestriero, Randall, et al.
Published: (2025)
by: Balestriero, Randall, et al.
Published: (2025)
Constrained Adversarial Learning for Automated Software Testing: a literature review
by: Vitorino, João, et al.
Published: (2023)
by: Vitorino, João, et al.
Published: (2023)
Machine Learning Operations: A Mapping Study
by: Chakraborty, Abhijit, et al.
Published: (2024)
by: Chakraborty, Abhijit, et al.
Published: (2024)
Learning-Based Testing for Deep Learning: Enhancing Model Robustness with Adversarial Input Prioritization
by: Rahman, Sheikh Md Mushfiqur, et al.
Published: (2025)
by: Rahman, Sheikh Md Mushfiqur, et al.
Published: (2025)
A Feature-Driven Framework for Software Fault Prediction
by: Ghazi, Ahmad Nauman, et al.
Published: (2026)
by: Ghazi, Ahmad Nauman, et al.
Published: (2026)
CodeCoT: Tackling Code Syntax Errors in CoT Reasoning for Code Generation
by: Huang, Dong, et al.
Published: (2023)
by: Huang, Dong, et al.
Published: (2023)
UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems
by: Zhang, Jingyu, et al.
Published: (2026)
by: Zhang, Jingyu, et al.
Published: (2026)
Enhancing Web Service Anomaly Detection via Fine-grained Multi-modal Association and Frequency Domain Analysis
by: Yang, Xixuan, et al.
Published: (2025)
by: Yang, Xixuan, et al.
Published: (2025)
Identifying Performance Issues in Cloud Service Systems Based on Relational-Temporal Features
by: Gu, Wenwei, et al.
Published: (2023)
by: Gu, Wenwei, et al.
Published: (2023)
Whitespaces Don't Lie: Feature-Driven and Embedding-Based Approaches for Detecting Machine-Generated Code
by: Nirob, Syed Mehedi Hasan, et al.
Published: (2026)
by: Nirob, Syed Mehedi Hasan, et al.
Published: (2026)
FAST: Boosting Uncertainty-based Test Prioritization Methods for Neural Networks via Feature Selection
by: Chen, Jialuo, et al.
Published: (2024)
by: Chen, Jialuo, et al.
Published: (2024)
Shapley-Guided Neural Repair Approach via Derivative-Free Optimization
by: Sun, Xinyu, et al.
Published: (2026)
by: Sun, Xinyu, et al.
Published: (2026)
Evaluating the Performance of a D-Wave Quantum Annealing System for Feature Subset Selection in Software Defect Prediction
by: Mandal, Ashis Kumar, et al.
Published: (2024)
by: Mandal, Ashis Kumar, et al.
Published: (2024)
Bridging Expert Knowledge with Deep Learning Techniques for Just-In-Time Defect Prediction
by: Zhou, Xin, et al.
Published: (2024)
by: Zhou, Xin, et al.
Published: (2024)
LLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs
by: Liu, Kaibo, et al.
Published: (2024)
by: Liu, Kaibo, et al.
Published: (2024)
Pre-Training Representations of Binary Code Using Contrastive Learning
by: Zhang, Yifan, et al.
Published: (2022)
by: Zhang, Yifan, et al.
Published: (2022)
A Comprehensive Study of Deep Learning Model Fixing Approaches
by: You, Hanmo, et al.
Published: (2025)
by: You, Hanmo, et al.
Published: (2025)
VeriScale: Adversarial Test-Suite Scaling for Verifiable Code Generation
by: Bai, Yifan, et al.
Published: (2026)
by: Bai, Yifan, et al.
Published: (2026)
Concolic Testing on Individual Fairness of Neural Network Models
by: Huang, Ming-I, et al.
Published: (2025)
by: Huang, Ming-I, et al.
Published: (2025)
Defect Prediction with Content-based Features
by: Pham, Hung Viet, et al.
Published: (2024)
by: Pham, Hung Viet, et al.
Published: (2024)
Protecting Deep Learning Model Copyrights with Adversarial Example-Free Reuse Detection
by: Luan, Xiaokun, et al.
Published: (2024)
by: Luan, Xiaokun, et al.
Published: (2024)
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations
by: Bostani, Hamid, et al.
Published: (2024)
by: Bostani, Hamid, et al.
Published: (2024)
AKD : Adversarial Knowledge Distillation For Large Language Models Alignment on Coding tasks
by: Oulkadda, Ilyas, et al.
Published: (2025)
by: Oulkadda, Ilyas, et al.
Published: (2025)
K-ASTRO: Structure-Aware Adaptation of LLMs for Code Vulnerability Detection
by: Zhang, Yifan, et al.
Published: (2022)
by: Zhang, Yifan, et al.
Published: (2022)
SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair
by: Zhang, Yifan, et al.
Published: (2026)
by: Zhang, Yifan, et al.
Published: (2026)
Evaluating Reinforcement Learning Safety and Trustworthiness in Cyber-Physical Systems
by: Dearstyne, Katherine, et al.
Published: (2025)
by: Dearstyne, Katherine, et al.
Published: (2025)
Renaissance of Literate Programming in the Era of LLMs: Enhancing LLM-Based Code Generation in Large-Scale Projects
by: Zhang, Wuyang, et al.
Published: (2024)
by: Zhang, Wuyang, et al.
Published: (2024)
Deep Smart Contract Intent Detection
by: Huang, Youwei, et al.
Published: (2022)
by: Huang, Youwei, et al.
Published: (2022)
NeuSemSlice: Towards Effective DNN Model Maintenance via Neuron-level Semantic Slicing
by: Zhou, Shide, et al.
Published: (2024)
by: Zhou, Shide, et al.
Published: (2024)
FAME: Failure-Aware Mixture-of-Experts for Message-Level Log Anomaly Detection
by: Wang, Huanchi, et al.
Published: (2026)
by: Wang, Huanchi, et al.
Published: (2026)
Think Anywhere in Code Generation
by: Jiang, Xue, et al.
Published: (2026)
by: Jiang, Xue, et al.
Published: (2026)
It's LIT! Reliability-Optimized LLMs with Inspectable Tools
by: Zhang, Ruixin, et al.
Published: (2025)
by: Zhang, Ruixin, et al.
Published: (2025)
Beyond Window-Based Detection: A Graph-Centric Framework for Discrete Log Anomaly Detection
by: Qi, Jiaxing, et al.
Published: (2025)
by: Qi, Jiaxing, et al.
Published: (2025)
Similar Items
-
Signature in Code Backdoor Detection, how far are we?
by: Le, Quoc Hung, et al.
Published: (2025) -
TopoMap: A Feature-based Semantic Discriminator of the Topographical Regions in the Test Input Space
by: De Vita, Gianmarco, et al.
Published: (2025) -
PyTorch-based Geometric Learning with Non-CUDA Processing Units: Experiences from Intel Gaudi-v2 HPUs
by: Bu, Fanchen, et al.
Published: (2025) -
Pruning the Unsurprising: Efficient LLM Reasoning via First-Token Surprisal
by: Zeng, Wenhao, et al.
Published: (2025) -
Engineering Resource-constrained Software Systems with DNN Components: a Concept-based Pruning Approach
by: Formica, Federico, et al.
Published: (2026)