{"total":303,"rows":[{"id":"2107.06917","title":"A Field Guide to Federated Optimization","created":"2021-07-14","cited_by_count":315,"area":null},{"id":"2402.07867","title":"PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models","created":"2024-02-12","cited_by_count":267,"area":"rag"},{"id":"2110.14430","title":"Adversarial Neuron Pruning Purifies Backdoored Deep Models","created":"2021-10-27","cited_by_count":235,"area":null},{"id":"2105.12400","title":"Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger","created":"2021-05-26","cited_by_count":222,"area":"safety"},{"id":"2310.10844","title":"Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks","created":"2023-10-16","cited_by_count":194,"area":"safety"},{"id":"2212.04612","title":"Training Data Influence Analysis and Estimation: A Survey","created":"2022-12-09","cited_by_count":135,"area":null},{"id":"2104.11315","title":"SPECTRE: Defending Against Backdoor Attacks Using Robust Statistics","created":"2021-04-22","cited_by_count":130,"area":null},{"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":"2507.14805","title":"Subliminal Learning: Language models transmit behavioral traits via hidden signals in data","created":"2025-07-20","cited_by_count":95,"area":null},{"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":"2308.07061","title":"Machine Unlearning: Solutions and Challenges","created":"2023-08-14","cited_by_count":93,"area":"safety"},{"id":"2409.18169","title":"Harmful Fine-tuning Attacks and Defenses for Large Language Models: A Survey","created":"2024-09-26","cited_by_count":90,"area":"alignment"},{"id":"2101.06570","title":"Membership Inference Attack on Graph Neural Networks","created":"2021-01-17","cited_by_count":81,"area":null},{"id":"2310.14735","title":"Unleashing the potential of prompt engineering for large language models","created":"2023-10-23","cited_by_count":72,"area":null},{"id":"2106.04690","title":"Handcrafted Backdoors in Deep Neural Networks","created":"2021-06-08","cited_by_count":63,"area":null},{"id":"2101.11073","title":"Property Inference From Poisoning","created":"2021-01-26","cited_by_count":60,"area":null},{"id":"2102.04716","title":"Better Safe Than Sorry: Preventing Delusive Adversaries with Adversarial Training","created":"2021-02-09","cited_by_count":59,"area":null},{"id":"2311.16153","title":"Identifying and Mitigating Vulnerabilities in LLM-Integrated Applications","created":"2023-11-07","cited_by_count":54,"area":null},{"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":"2110.12925","title":"CoProtector: Protect Open-Source Code against Unauthorized Training Usage with Data Poisoning","created":"2021-10-25","cited_by_count":47,"area":"safety"},{"id":"2105.01622","title":"Poisoning the Unlabeled Dataset of Semi-Supervised Learning","created":"2021-05-04","cited_by_count":44,"area":null},{"id":"2101.02644","title":"Data Poisoning Attacks to Deep Learning Based Recommender Systems","created":"2021-01-07","cited_by_count":43,"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":"2101.02559","title":"Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead","created":"2021-01-04","cited_by_count":41,"area":null},{"id":"2112.14889","title":"Few-shot Backdoor Defense Using Shapley Estimation","created":"2021-12-30","cited_by_count":41,"area":null},{"id":"2302.14677","title":"Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger","created":"2023-02-28","cited_by_count":40,"area":null},{"id":"2312.01350","title":"Honesty Is the Best Policy: Defining and Mitigating AI Deception","created":"2023-12-03","cited_by_count":40,"area":null},{"id":"2107.12045","title":"How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review","created":"2021-07-26","cited_by_count":39,"area":null},{"id":"2505.16640","title":"BadVLA: Towards Backdoor Attacks on Vision-Language-Action Models via Objective-Decoupled Optimization","created":"2025-05-22","cited_by_count":38,"area":"vla"},{"id":"2406.17216","title":"Machine Unlearning Fails to Remove Data Poisoning Attacks","created":"2024-06-25","cited_by_count":37,"area":"safety"},{"id":"2504.03957","title":"Practical Poisoning Attacks against Retrieval-Augmented Generation","created":"2025-04-04","cited_by_count":36,"area":"rag"},{"id":"2103.02683","title":"Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release","created":"2021-02-16","cited_by_count":35,"area":null},{"id":"2203.14533","title":"Robust Unlearnable Examples: Protecting Data Against Adversarial Learning","created":"2022-03-28","cited_by_count":35,"area":null},{"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":"2506.00979","title":"Ivy-Fake: A Unified Explainable Framework and Benchmark for Image and Video AIGC Detection","created":"2025-06-01","cited_by_count":34,"area":null},{"id":"2105.03592","title":"De-Pois: An Attack-Agnostic Defense against Data Poisoning Attacks","created":"2021-05-08","cited_by_count":33,"area":"safety"},{"id":"2201.10055","title":"Identifying a Training-Set Attack's Target Using Renormalized Influence Estimation","created":"2022-01-25","cited_by_count":32,"area":null},{"id":"2403.00871","title":"Teach LLMs to Phish: Stealing Private Information from Language Models","created":"2024-03-01","cited_by_count":32,"area":null},{"id":"2208.12348","title":"SNAP: Efficient Extraction of Private Properties with Poisoning","created":"2022-08-25","cited_by_count":31,"area":null},{"id":"2109.05872","title":"Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering","created":"2021-09-13","cited_by_count":30,"area":null},{"id":"2112.09745","title":"Interpretable Data-Based Explanations for Fairness Debugging","created":"2021-12-17","cited_by_count":30,"area":null},{"id":"2205.11765","title":"Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees","created":"2022-05-24","cited_by_count":30,"area":null},{"id":"2210.00584","title":"FLCert: Provably Secure Federated Learning against Poisoning Attacks","created":"2022-10-02","cited_by_count":30,"area":null},{"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":"2310.18933","title":"Label Poisoning is All You Need","created":"2023-10-29","cited_by_count":29,"area":"safety"},{"id":"2207.04497","title":"One-shot Neural Backdoor Erasing via Adversarial Weight Masking","created":"2022-07-10","cited_by_count":28,"area":null},{"id":"2504.21668","title":"Traceback of Poisoning Attacks to Retrieval-Augmented Generation","created":"2025-04-30","cited_by_count":28,"area":"rag"},{"id":"2406.16257","title":"Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning","created":"2024-06-24","cited_by_count":27,"area":"safety"},{"id":"2604.09378","title":"BadSkill: Backdoor Attacks on Agent Skills via Model-in-Skill Poisoning","created":"2026-04-10","cited_by_count":27,"area":"safety"},{"id":"2203.08398","title":"COPA: Certifying Robust Policies for Offline Reinforcement Learning against Poisoning Attacks","created":"2022-03-16","cited_by_count":26,"area":"offlinerl"},{"id":"2406.08689","title":"Security of AI Agents","created":"2024-06-12","cited_by_count":26,"area":"agents"},{"id":"2106.09689","title":"Statistical Query Lower Bounds for List-Decodable Linear Regression","created":"2021-06-17","cited_by_count":25,"area":null},{"id":"2204.09092","title":"Indiscriminate Data Poisoning Attacks on Neural Networks","created":"2022-04-19","cited_by_count":25,"area":"safety"},{"id":"2203.06414","title":"A Survey of Adversarial Defences and Robustness in NLP","created":"2022-03-12","cited_by_count":23,"area":null},{"id":"2204.05986","title":"Machine Learning Security against Data Poisoning: Are We There Yet?","created":"2022-04-12","cited_by_count":23,"area":"safety"},{"id":"2207.02842","title":"When does Bias Transfer in Transfer Learning?","created":"2022-07-06","cited_by_count":23,"area":null},{"id":"2102.00655","title":"Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning","created":"2021-02-01","cited_by_count":21,"area":"safety"},{"id":"2102.05776","title":"Defense Against Reward Poisoning Attacks in Reinforcement Learning","created":"2021-02-10","cited_by_count":21,"area":null},{"id":"2106.08537","title":"Clustering Mixture Models in Almost-Linear Time via List-Decodable Mean Estimation","created":"2021-06-16","cited_by_count":21,"area":null},{"id":"2107.05243","title":"Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning","created":"2021-07-12","cited_by_count":21,"area":"safety"},{"id":"2107.07240","title":"Subnet Replacement: Deployment-stage backdoor attack against deep neural networks in gray-box setting","created":"2021-07-15","cited_by_count":21,"area":null},{"id":"2110.04363","title":"Certifying Robustness to Programmable Data Bias in Decision Trees","created":"2021-10-08","cited_by_count":21,"area":null},{"id":"2204.12399","title":"Streaming Algorithms for High-Dimensional Robust Statistics","created":"2022-04-26","cited_by_count":21,"area":null},{"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":"2301.01197","title":"Backdoor Attacks Against Dataset Distillation","created":"2023-01-03","cited_by_count":21,"area":null},{"id":"2402.02160","title":"Data Poisoning for In-context Learning","created":"2024-02-03","cited_by_count":21,"area":"safety"},{"id":"2402.14859","title":"The Wolf Within: Covert Injection of Malice into MLLM Societies via an MLLM Operative","created":"2024-02-20","cited_by_count":21,"area":"agents"},{"id":"2201.12686","title":"Rank List Sensitivity of Recommender Systems to Interaction Perturbations","created":"2022-01-29","cited_by_count":20,"area":null},{"id":"2203.04160","title":"Robustly-reliable learners under poisoning attacks","created":"2022-03-08","cited_by_count":20,"area":"safety"},{"id":"2309.17310","title":"Leave-one-out Distinguishability in Machine Learning","created":"2023-09-29","cited_by_count":20,"area":null},{"id":"2110.08932","title":"Poisoning Attacks on Fair Machine Learning","created":"2021-10-17","cited_by_count":19,"area":null},{"id":"2207.00425","title":"Transferable Graph Backdoor Attack","created":"2022-06-21","cited_by_count":19,"area":null},{"id":"2102.06004","title":"Fairness-Aware PAC Learning from Corrupted Data","created":"2021-02-11","cited_by_count":18,"area":null},{"id":"2106.09082","title":"Zeroth-Order Methods for Convex-Concave Minmax Problems: Applications to Decision-Dependent Risk Minimization","created":"2021-06-16","cited_by_count":18,"area":null},{"id":"2310.14848","title":"Zero-Knowledge Proof-based Verifiable Decentralized Machine Learning in Communication Network: A Comprehensive Survey","created":"2023-10-23","cited_by_count":18,"area":null},{"id":"2406.05670","title":"Certified Robustness to Data Poisoning in Gradient-Based Training","created":"2024-06-09","cited_by_count":18,"area":"safety"},{"id":"2304.10655","title":"The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions","created":"2023-04-20","cited_by_count":17,"area":null},{"id":"2306.14306","title":"Adaptive Sharpness-Aware Pruning for Robust Sparse Networks","created":"2023-06-25","cited_by_count":17,"area":null},{"id":"2202.10276","title":"Poisoning Attacks and Defenses on Artificial Intelligence: A Survey","created":"2022-02-21","cited_by_count":16,"area":"safety"},{"id":"2205.00359","title":"Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees","created":"2022-04-30","cited_by_count":16,"area":null},{"id":"2205.13176","title":"On Collective Robustness of Bagging Against Data Poisoning","created":"2022-05-26","cited_by_count":16,"area":"safety"},{"id":"2207.01982","title":"Defending against the Label-flipping Attack in Federated Learning","created":"2022-07-05","cited_by_count":16,"area":null},{"id":"2103.00671","title":"Robust learning under clean-label attack","created":"2021-03-01","cited_by_count":15,"area":null},{"id":"2207.00872","title":"FL-Defender: Combating Targeted Attacks in Federated Learning","created":"2022-07-02","cited_by_count":15,"area":null},{"id":"2210.05929","title":"Few-shot Backdoor Attacks via Neural Tangent Kernels","created":"2022-10-12","cited_by_count":15,"area":null},{"id":"2404.04500","title":"Trustless Audits without Revealing Data or Models","created":"2024-04-06","cited_by_count":15,"area":null},{"id":"2109.11515","title":"Outlier-Robust Sparse Estimation via Non-Convex Optimization","created":"2021-09-23","cited_by_count":14,"area":null},{"id":"2210.02713","title":"On Optimal Learning Under Targeted Data Poisoning","created":"2022-10-06","cited_by_count":14,"area":"safety"},{"id":"2402.01096","title":"Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance","created":"2024-02-02","cited_by_count":14,"area":null},{"id":"2402.01920","title":"Preference Poisoning Attacks on Reward Model Learning","created":"2024-02-02","cited_by_count":14,"area":"alignment"},{"id":"2406.04606","title":"Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions","created":"2024-06-07","cited_by_count":14,"area":null},{"id":"2103.15753","title":"Privacy and Trust Redefined in Federated Machine Learning","created":"2021-03-29","cited_by_count":13,"area":null},{"id":"2105.08709","title":"Learning and Certification under Instance-targeted Poisoning","created":"2021-05-18","cited_by_count":13,"area":null},{"id":"2206.05245","title":"List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering","created":"2022-06-10","cited_by_count":13,"area":null},{"id":"2212.09006","title":"A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness","created":"2022-12-18","cited_by_count":13,"area":null},{"id":"2307.10184","title":"A Dual Stealthy Backdoor: From Both Spatial and Frequency Perspectives","created":"2023-07-03","cited_by_count":13,"area":null},{"id":"2312.08898","title":"Detection and Defense of Unlearnable Examples","created":"2023-12-14","cited_by_count":13,"area":null},{"id":"2402.09225","title":"Is My Data in Your AI? Membership Inference Test (MINT) applied to Face Biometrics","created":"2024-02-14","cited_by_count":13,"area":"safety"},{"id":"2208.03309","title":"Lethal Dose Conjecture on Data Poisoning","created":"2022-08-05","cited_by_count":12,"area":"safety"},{"id":"2208.10967","title":"The Value of Out-of-Distribution Data","created":"2022-08-23","cited_by_count":12,"area":null}],"next_cursor":"100"}