{"total":61,"rows":[{"id":"2404.01099","title":"What is in Your Safe Data? Identifying Benign Data that Breaks Safety","created":"2024-04-01","cited_by_count":118,"area":"safety"},{"id":"2306.17194","title":"On the Exploitability of Instruction Tuning","created":"2023-06-28","cited_by_count":116,"area":"safety"},{"id":"2106.08970","title":"Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch","created":"2021-06-16","cited_by_count":102,"area":"safety"},{"id":"2205.01992","title":"Wild Patterns Reloaded: A Survey of Machine Learning Security against Training Data Poisoning","created":"2022-05-04","cited_by_count":94,"area":"safety"},{"id":"2202.02628","title":"Improved Certified Defenses against Data Poisoning with (Deterministic) Finite Aggregation","created":"2022-02-05","cited_by_count":52,"area":"safety"},{"id":"2206.03693","title":"Autoregressive Perturbations for Data Poisoning","created":"2022-06-08","cited_by_count":46,"area":"safety"},{"id":"2212.10717","title":"Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks","created":"2022-12-21","cited_by_count":43,"area":"safety"},{"id":"2110.06904","title":"Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks","created":"2021-10-13","cited_by_count":40,"area":"safety"},{"id":"2403.13682","title":"Threats, Attacks, and Defenses in Machine Unlearning: A Survey","created":"2024-03-20","cited_by_count":39,"area":"safety"},{"id":"2406.17216","title":"Machine Unlearning Fails to Remove Data Poisoning Attacks","created":"2024-06-25","cited_by_count":37,"area":"safety"},{"id":"2205.06401","title":"PoisonedEncoder: Poisoning the Unlabeled Pre-training Data in Contrastive Learning","created":"2022-05-13","cited_by_count":34,"area":"safety"},{"id":"2106.01810","title":"Defending Against Backdoor Attacks in Natural Language Generation","created":"2021-06-03","cited_by_count":33,"area":"safety"},{"id":"2210.09671","title":"Not All Poisons are Created Equal: Robust Training against Data Poisoning","created":"2022-10-18","cited_by_count":30,"area":"safety"},{"id":"2408.02946","title":"Scaling Trends for Data Poisoning in LLMs","created":"2024-08-06","cited_by_count":30,"area":"safety"},{"id":"2310.18933","title":"Label Poisoning is All You Need","created":"2023-10-29","cited_by_count":29,"area":"safety"},{"id":"2204.09092","title":"Indiscriminate Data Poisoning Attacks on Neural Networks","created":"2022-04-19","cited_by_count":25,"area":"safety"},{"id":"2102.13624","title":"What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning","created":"2021-02-26","cited_by_count":22,"area":"safety"},{"id":"2208.10224","title":"Friendly Noise against Adversarial Noise: A Powerful Defense against Data Poisoning Attacks","created":"2022-08-14","cited_by_count":21,"area":"safety"},{"id":"2402.02160","title":"Data Poisoning for In-context Learning","created":"2024-02-03","cited_by_count":21,"area":"safety"},{"id":"2203.04160","title":"Robustly-reliable learners under poisoning attacks","created":"2022-03-08","cited_by_count":20,"area":"safety"},{"id":"2503.22759","title":"Data Poisoning in Deep Learning: A Survey","created":"2025-03-27","cited_by_count":20,"area":"safety"},{"id":"2205.13634","title":"BagFlip: A Certified Defense against Data Poisoning","created":"2022-05-26","cited_by_count":19,"area":"safety"},{"id":"2202.08578","title":"An Equivalence Between Data Poisoning and Byzantine Gradient Attacks","created":"2022-02-17","cited_by_count":16,"area":"safety"},{"id":"2205.13176","title":"On Collective Robustness of Bagging Against Data Poisoning","created":"2022-05-26","cited_by_count":16,"area":"safety"},{"id":"2208.03309","title":"Lethal Dose Conjecture on Data Poisoning","created":"2022-08-05","cited_by_count":12,"area":"safety"},{"id":"2302.03684","title":"Temporal Robustness against Data Poisoning","created":"2023-02-07","cited_by_count":10,"area":"safety"},{"id":"2305.14851","title":"Sharpness-Aware Data Poisoning Attack","created":"2023-05-24","cited_by_count":10,"area":"safety"},{"id":"2103.12399","title":"The Hammer and the Nut: Is Bilevel Optimization Really Needed to Poison Linear Classifiers?","created":"2021-03-23","cited_by_count":9,"area":"safety"},{"id":"2410.09101","title":"Data Taggants: Dataset Ownership Verification via Harmless Targeted Data Poisoning","created":"2024-10-09","cited_by_count":8,"area":"safety"},{"id":"2201.00762","title":"Execute Order 66: Targeted Data Poisoning for Reinforcement Learning","created":"2022-01-03","cited_by_count":7,"area":"safety"},{"id":"2512.14741","title":"Persistent Backdoor Attacks under Continual Fine-Tuning of LLMs","created":"2025-12-12","cited_by_count":7,"area":"safety"},{"id":"2502.19770","title":"TAPE: Tailored Posterior Difference for Auditing of Machine Unlearning","created":"2025-02-27","cited_by_count":6,"area":"safety"},{"id":"2406.10953","title":"Really Unlearned? Verifying Machine Unlearning via Influential Sample Pairs","created":"2024-06-16","cited_by_count":5,"area":"safety"},{"id":"2410.10572","title":"Regularized Robustly Reliable Learners and Instance Targeted Attacks","created":"2024-10-14","cited_by_count":5,"area":"safety"},{"id":"2212.03334","title":"Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning","created":"2022-12-06","cited_by_count":4,"area":"safety"},{"id":"2310.07632","title":"Prompt Backdoors in Visual Prompt Learning","created":"2023-10-11","cited_by_count":4,"area":"safety"},{"id":"2503.22413","title":"Instance-Level Data-Use Auditing of Visual ML Models","created":"2025-03-28","cited_by_count":4,"area":"safety"},{"id":"2306.01613","title":"Hyperparameter Learning under Data Poisoning: Analysis of the Influence of Regularization via Multiobjective Bilevel Optimization","created":"2023-06-02","cited_by_count":3,"area":"safety"},{"id":"2309.16487","title":"Towards Poisoning Fair Representations","created":"2023-09-28","cited_by_count":3,"area":"safety"},{"id":"2410.21453","title":"Inverting Gradient Attacks Makes Powerful Data Poisoning","created":"2024-10-28","cited_by_count":2,"area":"safety"},{"id":"2305.15394","title":"Differentially-Private Decision Trees and Provable Robustness to Data Poisoning","created":"2023-05-24","cited_by_count":1,"area":"safety"},{"id":"2306.16415","title":"On Practical Aspects of Aggregation Defenses against Data Poisoning Attacks","created":"2023-06-28","cited_by_count":1,"area":"safety"},{"id":"2309.08549","title":"HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks","created":"2023-09-15","cited_by_count":1,"area":"safety"},{"id":"2403.13523","title":"Have You Poisoned My Data? Defending Neural Networks against Data Poisoning","created":"2024-03-20","cited_by_count":1,"area":"safety"},{"id":"2409.13004","title":"Data Poisoning and Leakage Analysis in Federated Learning","created":"2024-09-19","cited_by_count":1,"area":"safety"},{"id":"2412.03908","title":"Generalizable Targeted Data Poisoning against Varying Physical Objects","created":"2024-12-05","cited_by_count":1,"area":"safety"},{"id":"2603.24857","title":"AI Security in the Foundation Model Era: A Comprehensive Survey from a Unified Perspective","created":"2026-03-25","cited_by_count":1,"area":"safety"},{"id":"2212.02582","title":"Rethinking Backdoor Data Poisoning Attacks in the Context of Semi-Supervised Learning","created":"2022-12-05","cited_by_count":0,"area":"safety"},{"id":"2309.13579","title":"Seeing Is Not Always Believing: Invisible Collision Attack and Defence on Pre-Trained Models","created":"2023-09-24","cited_by_count":0,"area":"safety"},{"id":"2405.06073","title":"Hard Work Does Not Always Pay Off: Poisoning Attacks on Neural Architecture Search","created":"2024-05-09","cited_by_count":0,"area":"safety"},{"id":"2405.19376","title":"PureEBM: Universal Poison Purification via Mid-Run Dynamics of Energy-Based Models","created":"2024-05-28","cited_by_count":0,"area":"safety"},{"id":"2410.05284","title":"Hypnopaedia-Aware Machine Unlearning via Psychometrics of Artificial Mental Imagery","created":"2024-09-29","cited_by_count":0,"area":"safety"},{"id":"2412.07575","title":"Defending Against Neural Network Model Inversion Attacks via Data Poisoning","created":"2024-12-10","cited_by_count":0,"area":"safety"},{"id":"2503.10269","title":"Targeted Data Poisoning for Black-Box Audio Datasets Ownership Verification","created":"2025-03-13","cited_by_count":0,"area":"safety"},{"id":"2503.21236","title":"Clean Image May be Dangerous: Data Poisoning Attacks Against Deep Hashing","created":"2025-03-27","cited_by_count":0,"area":"safety"},{"id":"2505.09983","title":"Sybil-based Virtual Data Poisoning Attacks in Federated Learning","created":"2025-05-15","cited_by_count":0,"area":"safety"},{"id":"2509.06896","title":"Are Targeted Data Poisoning Attacks as Effective as We Think?","created":"2025-09-08","cited_by_count":0,"area":"safety"},{"id":"2509.25792","title":"PUREVQ-GAN: Defending Data Poisoning Attacks through Vector-Quantized Bottlenecks","created":"2025-09-30","cited_by_count":0,"area":"safety"},{"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":"2608.06211","title":"Reversible Unlearnable Examples: Towards the Copyright Protection in Deep Learning Era","created":"2026-08-06","cited_by_count":0,"area":"safety"},{"id":"2610.01788","title":"SAGE: Similarity-Based Cleaning of Poisoned Training Data from Verified Examples","created":"2026-10-01","cited_by_count":0,"area":"safety"}],"next_cursor":null}