{"total":57,"rows":[{"id":"2411.00348","title":"Attention Tracker: Detecting Prompt Injection Attacks in LLMs","created":"2024-11-01","cited_by_count":95,"area":"safety"},{"id":"2507.11878","title":"LLMs Encode Harmfulness and Refusal Separately","created":"2025-07-16","cited_by_count":88,"area":"safety"},{"id":"2410.13708","title":"On the Role of Attention Heads in Large Language Model Safety","created":"2024-10-17","cited_by_count":72,"area":"safety"},{"id":"2412.17686","title":"Large Language Model Safety: A Holistic Survey","created":"2024-12-23","cited_by_count":59,"area":"safety"},{"id":"2410.02760","title":"Erasing Conceptual Knowledge from Language Models","created":"2024-10-03","cited_by_count":34,"area":"safety"},{"id":"2410.08811","title":"PoisonBench: Assessing Large Language Model Vulnerability to Data Poisoning","created":"2024-10-11","cited_by_count":33,"area":"safety"},{"id":"2410.18210","title":"Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks","created":"2024-10-23","cited_by_count":33,"area":"safety"},{"id":"2408.02946","title":"Scaling Trends for Data Poisoning in LLMs","created":"2024-08-06","cited_by_count":30,"area":"safety"},{"id":"2410.02298","title":"Jailbreak Antidote: Runtime Safety-Utility Balance via Sparse Representation Adjustment in Large Language Models","created":"2024-10-03","cited_by_count":23,"area":"safety"},{"id":"2503.06808","title":"Privacy Auditing of Large Language Models","created":"2025-03-09","cited_by_count":23,"area":"safety"},{"id":"2504.18530","title":"Scaling Laws For Scalable Oversight","created":"2025-04-25","cited_by_count":23,"area":"safety"},{"id":"2411.11114","title":"JailbreakLens: Interpreting Jailbreak Mechanism in the Lens of Representation and Circuit","created":"2024-11-17","cited_by_count":22,"area":"safety"},{"id":"2411.08410","title":"The VLLM Safety Paradox: Dual Ease in Jailbreak Attack and Defense","created":"2024-11-13","cited_by_count":21,"area":"safety"},{"id":"2506.07596","title":"TwinBreak: Jailbreaking LLM Security Alignments based on Twin Prompts","created":"2025-06-09","cited_by_count":19,"area":"safety"},{"id":"2410.03857","title":"You Know What I'm Saying: Jailbreak Attack via Implicit Reference","created":"2024-10-04","cited_by_count":14,"area":"safety"},{"id":"2506.05735","title":"Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness","created":"2025-06-06","cited_by_count":14,"area":"safety"},{"id":"2504.18564","title":"DualBreach: Efficient Dual-Jailbreaking via Target-Driven Initialization and Multi-Target Optimization","created":"2025-04-21","cited_by_count":12,"area":"safety"},{"id":"2410.06809","title":"Root Defence Strategies: Ensuring Safety of LLM at the Decoding Level","created":"2024-10-09","cited_by_count":11,"area":"safety"},{"id":"2410.08660","title":"RePD: Defending Jailbreak Attack through a Retrieval-based Prompt Decomposition Process","created":"2024-10-11","cited_by_count":11,"area":"safety"},{"id":"2411.06899","title":"LongSafety: Enhance Safety for Long-Context LLMs","created":"2024-11-11","cited_by_count":11,"area":"safety"},{"id":"2505.16559","title":"CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning","created":"2025-05-22","cited_by_count":11,"area":"safety"},{"id":"2410.06913","title":"Utilize the Flow before Stepping into the Same River Twice: Certainty Represented Knowledge Flow for Refusal-Aware Instruction Tuning","created":"2024-10-09","cited_by_count":10,"area":"safety"},{"id":"2509.21761","title":"Backdoor Attribution: Elucidating and Controlling Backdoor in Language Models","created":"2025-09-26","cited_by_count":10,"area":"safety"},{"id":"2507.06274","title":"Enhancing LLM Watermark Resilience Against Both Scrubbing and Spoofing Attacks","created":"2025-07-08","cited_by_count":9,"area":"safety"},{"id":"2510.09694","title":"Kelp: A Streaming Safeguard for Large Models via Latent Dynamics-Guided Risk Detection","created":"2025-10-09","cited_by_count":9,"area":"safety"},{"id":"2510.17633","title":"SARSteer: Safeguarding Large Audio-Language Models via Safe-Ablated Refusal Steering","created":"2025-10-20","cited_by_count":8,"area":"safety"},{"id":"2506.07452","title":"When Style Breaks Safety: Defending LLMs Against Superficial Style Alignment","created":"2025-06-09","cited_by_count":6,"area":"safety"},{"id":"2510.16629","title":"On the Impossibility of Retrain Equivalence in Machine Unlearning","created":"2025-10-18","cited_by_count":6,"area":"safety"},{"id":"2603.00498","title":"Antibody: Strengthening Defense Against Harmful Fine-Tuning for Large Language Models via Attenuating Harmful Gradient Influence","created":"2026-02-28","cited_by_count":6,"area":"safety"},{"id":"2411.19335","title":"PEFT-as-an-Attack! Jailbreaking Language Models during Federated Parameter-Efficient Fine-Tuning","created":"2024-11-28","cited_by_count":5,"area":"safety"},{"id":"2410.04190","title":"Harnessing Task Overload for Scalable Jailbreak Attacks on Large Language Models","created":"2024-10-05","cited_by_count":4,"area":"safety"},{"id":"2510.01088","title":"Safety Instincts: LLMs Learn to Trust Their Internal Compass for Self-Defense","created":"2025-10-01","cited_by_count":4,"area":"safety"},{"id":"2502.16491","title":"Intrinsic Model Weaknesses: How Priming Attacks Unveil Vulnerabilities in Large Language Models","created":"2025-02-23","cited_by_count":3,"area":"safety"},{"id":"2504.12681","title":"GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs","created":"2025-04-17","cited_by_count":3,"area":"safety"},{"id":"2512.24044","title":"Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?","created":"2025-12-30","cited_by_count":3,"area":"safety"},{"id":"2603.03323","title":"Discern Truth from Falsehood: Reducing Over-Refusal via Contrastive Refinement","created":"2026-02-10","cited_by_count":3,"area":"safety"},{"id":"2604.21197","title":"Toward Efficient Membership Inference Attacks against Federated Large Language Models: A Projection Residual Approach","created":"2026-04-23","cited_by_count":3,"area":"safety"},{"id":"2409.17458","title":"RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking","created":"2024-09-26","cited_by_count":2,"area":"safety"},{"id":"2504.05689","title":"Separator Injection Attack: Uncovering Dialogue Biases in Large Language Models Caused by Role Separators","created":"2025-04-08","cited_by_count":2,"area":"safety"},{"id":"2506.07356","title":"Safety-Aligned Weights Are Not Enough: Refusal-Teacher-Guided Finetuning Enhances Safety and Downstream Performance under Harmful Finetuning Attacks","created":"2025-06-09","cited_by_count":2,"area":"safety"},{"id":"2506.13494","title":"Watermarking LLM-Generated Datasets in Downstream Tasks","created":"2025-06-16","cited_by_count":1,"area":"safety"},{"id":"2510.08329","title":"AutoRed: A Free-form Adversarial Prompt Generation Framework for Automated Red Teaming","created":"2025-10-09","cited_by_count":1,"area":"safety"},{"id":"2511.19009","title":"Understanding and Mitigating Over-refusal for Large Language Models via Representation Intervention","created":"2025-11-24","cited_by_count":1,"area":"safety"},{"id":"2512.14751","title":"One Leak Away: How Pretrained Model Exposure Amplifies Jailbreak Risks in Finetuned LLMs","created":"2025-12-14","cited_by_count":1,"area":"safety"},{"id":"2601.01296","title":"Aggressive Compression Enables LLM Weight Theft","created":"2026-01-03","cited_by_count":1,"area":"safety"},{"id":"2412.17531","title":"Invisible Textual Backdoor Attacks based on Dual-Trigger","created":"2024-12-23","cited_by_count":0,"area":"safety"},{"id":"2506.00062","title":"SafeCOMM: A Study on Safety Degradation in Fine-Tuned Telecom Large Language Models","created":"2025-05-29","cited_by_count":0,"area":"safety"},{"id":"2602.06630","title":"TrapSuffix: Proactive Defense Against Adversarial Suffixes in Jailbreaking","created":"2026-02-06","cited_by_count":0,"area":"safety"},{"id":"2603.18793","title":"Functional Subspace Watermarking for Large Language Models","created":"2026-03-19","cited_by_count":0,"area":"safety"},{"id":"2604.11663","title":"Why Do Large Language Models Generate Harmful Content?","created":"2026-04-13","cited_by_count":0,"area":"safety"},{"id":"2606.11202","title":"One Jailbreak, Many Tongues: Learning Language-Insensitive Intention Representations for Multilingual Jailbreak Detection","created":"2026-04-22","cited_by_count":0,"area":"safety"},{"id":"2607.11070","title":"MJ: Multi-turn LLM Jailbreaking via Decomposed Credit Assignment","created":"2026-07-13","cited_by_count":0,"area":"safety"},{"id":"2607.19366","title":"Geometry-Guided Constraint Learning for LLM Safety Classification","created":"2026-06-09","cited_by_count":0,"area":"safety"},{"id":"2610.00663","title":"Backdoor Containment via Expert Quarantine and Shutdown in LLMs","created":"2026-09-30","cited_by_count":0,"area":"safety"},{"id":"2610.00685","title":"Backdoor Purification for LoRA-Tuned LLMs via Null-Space Projection","created":"2026-09-30","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"},{"id":"2610.07532","title":"Safeguarding LLMs via Model-Agnostic Latent Safety Signals from Dark Knowledge","created":"2026-10-05","cited_by_count":0,"area":"safety"}],"next_cursor":null}