{"total":55,"rows":[{"id":"2405.09786","title":"IBD-PSC: Input-level Backdoor Detection via Parameter-oriented Scaling Consistency","created":"2024-05-16","cited_by_count":39,"area":null},{"id":"2408.07362","title":"BadMerging: Backdoor Attacks Against Model Merging","created":"2024-08-14","cited_by_count":34,"area":null},{"id":"2405.16134","title":"Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack","created":"2024-05-25","cited_by_count":28,"area":null},{"id":"2405.11227","title":"BadActs: A Universal Backdoor Defense in the Activation Space","created":"2024-05-18","cited_by_count":21,"area":null},{"id":"2401.15295","title":"Shortcuts Everywhere and Nowhere: Exploring Multi-Trigger Backdoor Attacks","created":"2024-01-27","cited_by_count":19,"area":null},{"id":"2209.05244","title":"Universal Backdoor Attacks Detection via Adaptive Adversarial Probe","created":"2022-09-12","cited_by_count":16,"area":null},{"id":"2310.17498","title":"CBD: A Certified Backdoor Detector Based on Local Dominant Probability","created":"2023-10-26","cited_by_count":13,"area":null},{"id":"2409.01193","title":"CLIBE: Detecting Dynamic Backdoors in Transformer-based NLP Models","created":"2024-09-02","cited_by_count":13,"area":"safety"},{"id":"2412.20392","title":"Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning","created":"2024-12-29","cited_by_count":12,"area":"safety"},{"id":"2410.17431","title":"Meta Stackelberg Game: Robust Federated Learning against Adaptive and Mixed Poisoning Attacks","created":"2024-10-22","cited_by_count":9,"area":"deeprl"},{"id":"2405.19928","title":"BAN: Detecting Backdoors Activated by Adversarial Neuron Noise","created":"2024-05-30","cited_by_count":8,"area":null},{"id":"2306.13800","title":"A First Order Meta Stackelberg Method for Robust Federated Learning","created":"2023-06-23","cited_by_count":7,"area":null},{"id":"2411.19479","title":"FLARE: Toward Universal Dataset Purification against Backdoor Attacks","created":"2024-11-29","cited_by_count":7,"area":null},{"id":"2509.11173","title":"Your Compiler is Backdooring Your Model: Understanding and Exploiting Compilation Inconsistency Vulnerabilities in Deep Learning Compilers","created":"2025-09-14","cited_by_count":7,"area":null},{"id":"2502.19770","title":"TAPE: Tailored Posterior Difference for Auditing of Machine Unlearning","created":"2025-02-27","cited_by_count":6,"area":"safety"},{"id":"2503.16872","title":"Lie Detector: Unified Backdoor Detection via Cross-Examination Framework","created":"2025-03-21","cited_by_count":6,"area":null},{"id":"2509.24566","title":"TokenSwap: Backdoor Attack on the Compositional Understanding of Large Vision-Language Models","created":"2025-09-29","cited_by_count":5,"area":"mllm"},{"id":"2603.12989","title":"Test-Time Attention Purification for Backdoored Large Vision Language Models","created":"2026-03-13","cited_by_count":5,"area":"mllm"},{"id":"2601.11207","title":"LoRA as Oracle","created":"2026-01-16","cited_by_count":4,"area":"safety"},{"id":"2308.04617","title":"Improved Activation Clipping for Universal Backdoor Mitigation and Test-Time Detection","created":"2023-08-08","cited_by_count":3,"area":"safety"},{"id":"2402.17465","title":"Model X-ray:Detecting Backdoored Models via Decision Boundary","created":"2024-02-27","cited_by_count":3,"area":null},{"id":"2410.17573","title":"Securing Federated Learning against Backdoor Threats with Foundation Model Integration","created":"2024-10-23","cited_by_count":3,"area":"safety"},{"id":"2501.02373","title":"BADTV: Unveiling Backdoor Threats in Third-Party Task Vectors","created":"2025-01-04","cited_by_count":3,"area":"safety"},{"id":"2501.17151","title":"Scanning Trojaned Models Using Out-of-Distribution Samples","created":"2025-01-28","cited_by_count":3,"area":"safety"},{"id":"2512.08129","title":"Improving the Sensitivity of Backdoor Detectors via Class Subspace Orthogonalization","created":"2025-12-09","cited_by_count":3,"area":null},{"id":"2412.03441","title":"PBP: Post-training Backdoor Purification for Malware Classifiers","created":"2024-12-04","cited_by_count":2,"area":null},{"id":"2510.14299","title":"TED++: Submanifold-Aware Backdoor Detection via Layerwise Tubular-Neighbourhood Screening","created":"2025-10-16","cited_by_count":2,"area":null},{"id":"2602.17168","title":"BadCLIP++: Stealthy and Persistent Backdoors in Multimodal Contrastive Learning","created":"2026-02-19","cited_by_count":2,"area":"safety"},{"id":"2603.23007","title":"AgentRAE: Remote Action Execution through Notification-based Visual Backdoors against Screenshots-based Mobile GUI Agents","created":"2026-03-24","cited_by_count":2,"area":"agents"},{"id":"2402.02034","title":"CEPA: Consensus Embedded Perturbation for Agnostic Detection and Inversion of Backdoors","created":"2024-02-03","cited_by_count":1,"area":null},{"id":"2409.12072","title":"PAD-FT: A Lightweight Defense for Backdoor Attacks via Data Purification and Fine-Tuning","created":"2024-09-18","cited_by_count":1,"area":null},{"id":"2411.09540","title":"Prompting the Unseen: Detecting Hidden Backdoors in Black-Box Models","created":"2024-11-14","cited_by_count":1,"area":"safety"},{"id":"2507.22813","title":"DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion","created":"2025-07-30","cited_by_count":1,"area":"diffusion"},{"id":"2510.06629","title":"Unsupervised Backdoor Detection and Mitigation for Spiking Neural Networks","created":"2025-10-08","cited_by_count":1,"area":null},{"id":"2602.03586","title":"APEX: Probing Neural Networks via Activation Perturbation","created":"2026-02-03","cited_by_count":1,"area":null},{"id":"2603.18103","title":"STEP: Detecting Audio Backdoor Attacks via Stability-based Trigger Exposure Profiling","created":"2026-03-18","cited_by_count":1,"area":null},{"id":"2309.16827","title":"Post-Training Overfitting Mitigation in DNN Classifiers","created":"2023-09-28","cited_by_count":0,"area":"safety"},{"id":"2501.04108","title":"TrojanDec: Data-free Detection of Trojan Inputs in Self-supervised Learning","created":"2025-01-07","cited_by_count":0,"area":null},{"id":"2504.05902","title":"Defending against Backdoor Attacks via Module Switching","created":"2025-04-08","cited_by_count":0,"area":null},{"id":"2510.19145","title":"HAMLOCK: HArdware-Model LOgically Combined attacK","created":"2025-10-22","cited_by_count":0,"area":"safety"},{"id":"2511.06072","title":"CatBack: Universal Backdoor Attacks on Tabular Data via Categorical Encoding","created":"2025-11-08","cited_by_count":0,"area":null},{"id":"2511.07741","title":"Provable Repair of Deep Neural Network Defects by Preimage Synthesis and Property Refinement","created":"2025-11-11","cited_by_count":0,"area":"safety"},{"id":"2512.01498","title":"No Trust Issues Here: A Technical Report on the Winning Solutions for the Rayan AI Contest","created":"2025-12-01","cited_by_count":0,"area":"safety"},{"id":"2512.19730","title":"ArcGen: Generalizing Neural Backdoor Detection Across Diverse Architectures","created":"2025-12-17","cited_by_count":0,"area":null},{"id":"2602.00183","title":"RPP: A Certified Poisoned-Sample Detection Framework for Backdoor Attacks under Dataset Imbalance","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2602.03567","title":"EVE: Efficient Verification of Data Erasure through Customized Perturbation in Approximate Unlearning","created":"2026-02-03","cited_by_count":0,"area":"safety"},{"id":"2603.00711","title":"IU: Imperceptible Universal Backdoor Attack","created":"2026-02-28","cited_by_count":0,"area":null},{"id":"2604.22550","title":"ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2605.01298","title":"Checkerboard: Closed-Form and Data-Independent Trigger Design for Clean-Label Backdoor Attacks","created":"2026-05-02","cited_by_count":0,"area":null},{"id":"2605.18907","title":"Lightweight and Fast Backdoor Model Detection","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2605.18908","title":"Fast and Lightweight Backdoor Detection via Head Random Probing","created":"2026-05-17","cited_by_count":0,"area":null},{"id":"2606.29112","title":"A Novel Latent-Class Attack and its Detection by Class Subspace Orthogonalization","created":"2026-06-27","cited_by_count":0,"area":"safety"},{"id":"2606.31309","title":"CSO-LLM: Class Subspace Orthogonalization for Post-Training Backdoor Detection and Trigger Inversion in LLMs","created":"2026-06-30","cited_by_count":0,"area":"safety"},{"id":"2608.09047","title":"Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks","created":"2026-08-10","cited_by_count":0,"area":null},{"id":"2610.15359","title":"Adversarial Detection for Pre-trained Classifiers via Lipschitz-Margin Analysis with Certification","created":"2026-10-11","cited_by_count":0,"area":null}],"next_cursor":null}