{"total":71,"rows":[{"id":"2407.04295","title":"Jailbreak Attacks and Defenses Against Large Language Models: A Survey","created":"2024-07-05","cited_by_count":230,"area":"safety"},{"id":"2402.00888","title":"Security and Privacy Challenges of Large Language Models: A Survey","created":"2024-01-30","cited_by_count":186,"area":"safety"},{"id":"2312.07913","title":"A Survey of Text Watermarking in the Era of Large Language Models","created":"2023-12-13","cited_by_count":112,"area":"safety"},{"id":"2402.18104","title":"Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction","created":"2024-02-28","cited_by_count":107,"area":"safety"},{"id":"2401.15897","title":"Red-Teaming for Generative AI: Silver Bullet or Security Theater?","created":"2024-01-29","cited_by_count":83,"area":"safety"},{"id":"2402.06255","title":"Fight Back Against Jailbreaking via Prompt Adversarial Tuning","created":"2024-02-09","cited_by_count":67,"area":"safety"},{"id":"2402.09179","title":"Instruction Backdoor Attacks Against Customized LLMs","created":"2024-02-14","cited_by_count":62,"area":"safety"},{"id":"2405.20413","title":"Jailbreaking Large Language Models Against Moderation Guardrails via Cipher Characters","created":"2024-05-30","cited_by_count":42,"area":"safety"},{"id":"2405.01229","title":"Boosting Jailbreak Attack with Momentum","created":"2024-05-02","cited_by_count":40,"area":"safety"},{"id":"2401.09002","title":"AttackEval: How to Evaluate the Effectiveness of Jailbreak Attacking on Large Language Models","created":"2024-01-17","cited_by_count":28,"area":"safety"},{"id":"2406.09179","title":"Towards Effective Evaluations and Comparisons for LLM Unlearning Methods","created":"2024-06-13","cited_by_count":27,"area":"safety"},{"id":"2503.10566","title":"ASIDE: Architectural Separation of Instructions and Data in Language Models","created":"2025-03-13","cited_by_count":24,"area":"safety"},{"id":"2409.00089","title":"Watermarking Techniques for Large Language Models: A Survey","created":"2024-08-26","cited_by_count":23,"area":"safety"},{"id":"2407.20224","title":"Can Editing LLMs Inject Harm?","created":"2024-07-29","cited_by_count":22,"area":"safety"},{"id":"2505.01976","title":"A Survey on Privacy Risks and Protection in Large Language Models","created":"2025-05-04","cited_by_count":21,"area":"safety"},{"id":"2502.05163","title":"Enhancing LLM Safety Through a Theoretical Minimax Game Lens","created":"2025-02-07","cited_by_count":19,"area":"safety"},{"id":"2505.14103","title":"AudioJailbreak: Jailbreak Attacks against End-to-End Large Audio-Language Models","created":"2025-05-20","cited_by_count":18,"area":"safety"},{"id":"2510.19422","title":"LLM Unlearning with LLM Beliefs","created":"2025-10-22","cited_by_count":17,"area":"safety"},{"id":"2505.17568","title":"JALMBench: Benchmarking Jailbreak Vulnerabilities in Audio Language Models","created":"2025-05-23","cited_by_count":16,"area":"safety"},{"id":"2506.07171","title":"RULE: Reinforcement UnLEarning Achieves Forget-Retain Pareto Optimality","created":"2025-06-08","cited_by_count":16,"area":"safety"},{"id":"2410.03168","title":"Can Watermarked LLMs be Identified by Users via Crafted Prompts?","created":"2024-10-04","cited_by_count":13,"area":"safety"},{"id":"2503.09117","title":"GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs","created":"2025-03-12","cited_by_count":12,"area":"safety"},{"id":"2409.14177","title":"PathSeeker: Exploring LLM Security Vulnerabilities with a Reinforcement Learning-Based Jailbreak Approach","created":"2024-09-21","cited_by_count":11,"area":"safety"},{"id":"2503.07384","title":"Is My Text in Your AI Model? Gradient-based Membership Inference Test applied to LLMs","created":"2025-03-10","cited_by_count":10,"area":"safety"},{"id":"2507.05578","title":"The Landscape of Memorization in LLMs: Mechanisms, Measurement, and Mitigation","created":"2025-07-08","cited_by_count":10,"area":"safety"},{"id":"2505.02862","title":"Cannot See the Forest for the Trees: Invoking Heuristics and Biases to Elicit Irrational Choices of LLMs","created":"2025-05-03","cited_by_count":9,"area":"safety"},{"id":"2407.20181","title":"Blockchain for Large Language Model Security and Safety: A Holistic Survey","created":"2024-07-26","cited_by_count":8,"area":"safety"},{"id":"2507.21134","title":"TRIDENT: Benchmarking LLM Safety in Finance, Medicine, and Law","created":"2025-07-22","cited_by_count":8,"area":"safety"},{"id":"2501.00055","title":"LLM-Virus: Evolutionary Jailbreak Attack on Large Language Models","created":"2024-12-28","cited_by_count":7,"area":"safety"},{"id":"2506.02442","title":"Should LLM Safety Be More Than Refusing Harmful Instructions?","created":"2025-06-03","cited_by_count":7,"area":"safety"},{"id":"2602.06441","title":"Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning","created":"2026-02-06","cited_by_count":6,"area":"safety"},{"id":"2501.08454","title":"Tag&Tab: Pretraining Data Detection in Large Language Models Using Keyword-Based Membership Inference Attack","created":"2025-01-14","cited_by_count":5,"area":"safety"},{"id":"2501.18416","title":"Exploring Potential Prompt Injection Attacks in Federated Military LLMs and Their Mitigation","created":"2025-01-30","cited_by_count":5,"area":"safety"},{"id":"2506.06384","title":"Detection Method for Prompt Injection by Integrating Pre-trained Model and Heuristic Feature Engineering","created":"2025-06-05","cited_by_count":5,"area":"safety"},{"id":"2506.06073","title":"System-Aware Unlearning Algorithms: Use Lesser, Forget Faster","created":"2025-06-06","cited_by_count":4,"area":"safety"},{"id":"2510.00761","title":"Downgrade to Upgrade: Optimizer Simplification Enhances Robustness in LLM Unlearning","created":"2025-10-01","cited_by_count":4,"area":"safety"},{"id":"2605.07982","title":"GLiGuard: Schema-Conditioned Classification for LLM Safeguard","created":"2026-05-08","cited_by_count":4,"area":"safety"},{"id":"2606.06946","title":"Auditing Training Data in Domain-adapted LLMs: LoRA-MINT","created":"2026-06-05","cited_by_count":4,"area":"safety"},{"id":"2504.19333","title":"Unified Multi-Task Learning & Model Fusion for Efficient Language Model Guardrailing","created":"2025-04-27","cited_by_count":3,"area":"safety"},{"id":"2601.03594","title":"Jailbreaking LLMs & VLMs: Mechanisms, Evaluation, and Unified Defense","created":"2026-01-07","cited_by_count":3,"area":"safety"},{"id":"2505.13028","title":"Evaluating the efficacy of LLM Safety Solutions : The Palit Benchmark Dataset","created":"2025-05-19","cited_by_count":2,"area":"safety"},{"id":"2508.08629","title":"Securing Educational LLMs: A Generalised Taxonomy of Attacks on LLMs and DREAD Risk Assessment","created":"2025-08-12","cited_by_count":2,"area":"safety"},{"id":"2509.16861","title":"AdaptiveGuard: Towards Adaptive Runtime Safety for LLM-Powered Software","created":"2025-09-21","cited_by_count":2,"area":"safety"},{"id":"2509.23362","title":"Dual-Space Smoothness for Robust and Balanced LLM Unlearning","created":"2025-09-27","cited_by_count":2,"area":"safety"},{"id":"2512.18244","title":"Breaking Minds, Breaking Systems: Jailbreaking Large Language Models via Human-like Psychological Manipulation","created":"2025-12-20","cited_by_count":2,"area":"safety"},{"id":"2601.22030","title":"Per-parameter Task Arithmetic for Unlearning in Large Language Models","created":"2026-01-29","cited_by_count":2,"area":"safety"},{"id":"2604.18775","title":"An Empirical Study of Multi-Generation Sampling for Jailbreak Detection in Large Language Models","created":"2026-04-20","cited_by_count":2,"area":"safety"},{"id":"2502.05739","title":"Mitigating Sensitive Information Leakage in LLMs4Code through Machine Unlearning","created":"2025-02-09","cited_by_count":1,"area":"safety"},{"id":"2503.03502","title":"Geometry-Guided Adversarial Prompt Detection via Curvature and Local Intrinsic Dimension","created":"2025-03-05","cited_by_count":1,"area":"safety"},{"id":"2506.01770","title":"ReGA: Model-Based Safeguard for LLMs via Representation-Guided Abstraction","created":"2025-06-02","cited_by_count":1,"area":"safety"},{"id":"2506.14474","title":"LexiMark: Robust Watermarking via Lexical Substitutions to Enhance Membership Verification of an LLM's Textual Training Data","created":"2025-06-17","cited_by_count":1,"area":"safety"},{"id":"2508.10404","title":"Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation","created":"2025-08-14","cited_by_count":1,"area":"safety"},{"id":"2508.20443","title":"Towards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint","created":"2025-08-28","cited_by_count":1,"area":"safety"},{"id":"2509.16870","title":"DecipherGuard: Understanding and Deciphering Jailbreak Prompts for a Safer Deployment of Intelligent Software Systems","created":"2025-09-21","cited_by_count":1,"area":"safety"},{"id":"2604.21700","title":"Stealthy Backdoor Attacks against LLMs Based on Natural Style Triggers","created":"2026-04-23","cited_by_count":1,"area":"safety"},{"id":"2605.30501","title":"Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs","created":"2026-05-28","cited_by_count":1,"area":"safety"},{"id":"2606.12716","title":"Does AI Reviewer See the Full Picture? Attacking and Defending Multimodal Peer Review","created":"2026-06-10","cited_by_count":1,"area":"safety"},{"id":"2608.01117","title":"SoK: Intent-Oriented Systematization of Multi-Turn LLM Jailbreaks","created":"2026-08-02","cited_by_count":1,"area":"safety"},{"id":"2505.09974","title":"Analysing Safety Risks in LLMs Fine-Tuned with Pseudo-Malicious Cyber Security Data","created":"2025-05-15","cited_by_count":0,"area":"safety"},{"id":"2508.02312","title":"Data Security in Large Language Models: Risks, Defense, and Directions","created":"2025-08-04","cited_by_count":0,"area":"safety"},{"id":"2511.00346","title":"Exploiting Latent Space Discontinuities for Building Universal LLM Jailbreaks and Data Extraction Attacks","created":"2025-11-01","cited_by_count":0,"area":"safety"},{"id":"2512.04841","title":"SoK: a Comprehensive Causality Analysis Framework for Large Language Model Security","created":"2025-12-04","cited_by_count":0,"area":"safety"},{"id":"2512.06387","title":"Beyond Model Jailbreak: Systematic Dissection of the \"Ten DeadlySins\" in Embodied Intelligence","created":"2025-12-06","cited_by_count":0,"area":"safety"},{"id":"2512.19378","title":"HATS: High-Accuracy Triple-Set Watermarking for Large Language Models","created":"2025-12-22","cited_by_count":0,"area":"safety"},{"id":"2602.00577","title":"SAU: Sparsity-Aware Unlearning for LLMs via Gradient Masking and Importance Redistribution","created":"2026-01-31","cited_by_count":0,"area":"safety"},{"id":"2602.02280","title":"RACC: Representation-Aware Coverage Criteria for LLM Safety Testing","created":"2026-02-02","cited_by_count":0,"area":"safety"},{"id":"2604.12168","title":"Fully Homomorphic Encryption on Llama 3 model for privacy preserving LLM inference","created":"2026-04-14","cited_by_count":0,"area":"safety"},{"id":"2605.30919","title":"De-attribute to Forget for LLM Unlearning","created":"2026-05-29","cited_by_count":0,"area":"safety"},{"id":"2606.18309","title":"SAGE: Retain-Aware Post-Hoc Sanitization of Final Unlearning Vector","created":"2026-06-16","cited_by_count":0,"area":"safety"},{"id":"2609.06540","title":"SRD-GUARD: A Defense Framework of LLMs via Semantic Rewriting and Joint Multi-Model Scoring for Latent Intent Exposure","created":"2026-09-06","cited_by_count":0,"area":"safety"},{"id":"2610.03124","title":"The Fragility of Trigger-Tag Mechanisms for Misuse Detection in Open-Weight LLMs","created":"2026-10-02","cited_by_count":0,"area":"safety"}],"next_cursor":null}