{"total":95,"rows":[{"id":"2310.10683","title":"Large Language Model Unlearning","created":"2023-10-14","cited_by_count":302,"area":"safety"},{"id":"2402.16822","title":"Rainbow Teaming: Open-Ended Generation of Diverse Adversarial Prompts","created":"2024-02-26","cited_by_count":205,"area":"safety"},{"id":"2203.03929","title":"Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks","created":"2022-03-08","cited_by_count":175,"area":"safety"},{"id":"2402.08679","title":"COLD-Attack: Jailbreaking LLMs with Stealthiness and Controllability","created":"2024-02-13","cited_by_count":175,"area":"safety"},{"id":"2406.07933","title":"Large Language Model Unlearning via Embedding-Corrupted Prompts","created":"2024-06-12","cited_by_count":116,"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":"2305.01219","title":"Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models","created":"2023-05-02","cited_by_count":94,"area":"safety"},{"id":"2302.03162","title":"Protecting Language Generation Models via Invisible Watermarking","created":"2023-02-06","cited_by_count":90,"area":"safety"},{"id":"2112.02701","title":"Protecting Intellectual Property of Language Generation APIs with Lexical Watermark","created":"2021-12-05","cited_by_count":84,"area":"safety"},{"id":"2310.12362","title":"REMARK-LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models","created":"2023-10-18","cited_by_count":78,"area":"safety"},{"id":"2209.08773","title":"CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks","created":"2022-09-19","cited_by_count":76,"area":"safety"},{"id":"2111.07970","title":"Triggerless Backdoor Attack for NLP Tasks with Clean Labels","created":"2021-11-15","cited_by_count":66,"area":"safety"},{"id":"2310.07710","title":"A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models","created":"2023-10-11","cited_by_count":56,"area":"safety"},{"id":"2401.05949","title":"Universal Vulnerabilities in Large Language Models: Backdoor Attacks for In-context Learning","created":"2024-01-11","cited_by_count":53,"area":"safety"},{"id":"2402.11399","title":"k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text","created":"2024-02-17","cited_by_count":51,"area":"safety"},{"id":"2411.18479","title":"SoK: Watermarking for AI-Generated Content","created":"2024-11-27","cited_by_count":51,"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":"2311.07138","title":"WaterBench: Towards Holistic Evaluation of Watermarks for Large Language Models","created":"2023-11-13","cited_by_count":32,"area":"safety"},{"id":"2404.13968","title":"Protecting Your LLMs with Information Bottleneck","created":"2024-04-22","cited_by_count":29,"area":"safety"},{"id":"2505.11541","title":"MorphMark: Flexible Adaptive Watermarking for Large Language Models","created":"2025-05-14","cited_by_count":24,"area":"safety"},{"id":"2311.09763","title":"Test-time Backdoor Mitigation for Black-Box Large Language Models with Defensive Demonstrations","created":"2023-11-16","cited_by_count":21,"area":"safety"},{"id":"2506.21602","title":"BiMark: Unbiased Multilayer Watermarking for Large Language Models","created":"2025-06-19","cited_by_count":21,"area":"safety"},{"id":"2404.11262","title":"Sampling-based Pseudo-Likelihood for Membership Inference Attacks","created":"2024-04-17","cited_by_count":20,"area":"safety"},{"id":"2406.05344","title":"MemeGuard: An LLM and VLM-based Framework for Advancing Content Moderation via Meme Intervention","created":"2024-06-08","cited_by_count":20,"area":"safety"},{"id":"2503.00596","title":"BadJudge: Backdoor Vulnerabilities of LLM-as-a-Judge","created":"2025-03-01","cited_by_count":18,"area":"safety"},{"id":"2410.03537","title":"Ward: Provable RAG Dataset Inference via LLM Watermarks","created":"2024-10-04","cited_by_count":16,"area":"safety"},{"id":"2502.02787","title":"SimMark: A Robust Sentence-Level Similarity-Based Watermarking Algorithm for Large Language Models","created":"2025-02-05","cited_by_count":15,"area":"safety"},{"id":"2402.00179","title":"De-identification is not enough: a comparison between de-identified and synthetic clinical notes","created":"2024-01-31","cited_by_count":14,"area":"safety"},{"id":"2406.15796","title":"Unveiling Entity-Level Unlearning for Large Language Models: A Comprehensive Analysis","created":"2024-06-22","cited_by_count":14,"area":"safety"},{"id":"2408.07291","title":"Evaluating LLM-based Personal Information Extraction and Countermeasures","created":"2024-08-14","cited_by_count":12,"area":"safety"},{"id":"2506.05502","title":"StealthInk: A Multi-bit and Stealthy Watermark for Large Language Models","created":"2025-06-05","cited_by_count":12,"area":"safety"},{"id":"2506.14003","title":"Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs","created":"2025-06-16","cited_by_count":11,"area":"safety"},{"id":"2406.02603","title":"Distortion-free Watermarks are not Truly Distortion-free under Watermark Key Collisions","created":"2024-06-02","cited_by_count":10,"area":"safety"},{"id":"2411.13425","title":"Watermark under Fire: A Robustness Evaluation of LLM Watermarking","created":"2024-11-20","cited_by_count":9,"area":"safety"},{"id":"2412.08559","title":"Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning","created":"2024-12-11","cited_by_count":9,"area":"safety"},{"id":"2511.04934","title":"Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding","created":"2025-11-07","cited_by_count":9,"area":"safety"},{"id":"2402.01053","title":"Plan-Grounded Large Language Models for Dual Goal Conversational Settings","created":"2024-02-01","cited_by_count":8,"area":"safety"},{"id":"2404.02138","title":"Topic-Based Watermarks for Large Language Models","created":"2024-04-02","cited_by_count":8,"area":"safety"},{"id":"2405.02365","title":"ModelShield: Adaptive and Robust Watermark against Model Extraction Attack","created":"2024-05-03","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":"2311.09668","title":"Improving the Generation Quality of Watermarked Large Language Models via Word Importance Scoring","created":"2023-11-16","cited_by_count":6,"area":"safety"},{"id":"2504.14738","title":"PROMPTEVALS: A Dataset of Assertions and Guardrails for Custom Production Large Language Model Pipelines","created":"2025-04-20","cited_by_count":6,"area":"safety"},{"id":"2509.24043","title":"An Ensemble Framework for Unbiased Language Model Watermarking","created":"2025-09-28","cited_by_count":6,"area":"safety"},{"id":"2312.15867","title":"Punctuation Matters! Stealthy Backdoor Attack for Language Models","created":"2023-12-26","cited_by_count":5,"area":"safety"},{"id":"2407.11100","title":"Building Intelligence Identification System via Large Language Model Watermarking: A Survey and Beyond","created":"2024-07-15","cited_by_count":5,"area":"safety"},{"id":"2407.20271","title":"Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models","created":"2024-07-25","cited_by_count":5,"area":"safety"},{"id":"2506.15751","title":"Sysformer: Safeguarding Frozen Large Language Models with Adaptive System Prompts","created":"2025-06-18","cited_by_count":5,"area":"safety"},{"id":"2509.07755","title":"Factuality Beyond Coherence: Evaluating LLM Watermarking Methods for Medical Texts","created":"2025-09-09","cited_by_count":5,"area":"safety"},{"id":"2509.24048","title":"Analyzing and Evaluating Unbiased Language Model Watermark","created":"2025-09-28","cited_by_count":5,"area":"safety"},{"id":"2510.02962","title":"Leave No TRACE: Black-box Detection of Copyrighted Dataset Usage in Large Language Models via Watermarking","created":"2025-10-03","cited_by_count":5,"area":"safety"},{"id":"2504.14985","title":"aiXamine: Simplified LLM Safety and Security","created":"2025-04-21","cited_by_count":4,"area":"safety"},{"id":"2507.19894","title":"Generative Model Unlearning: A Survey through Target Events, Unlearning Operators, and Evaluation Protocols","created":"2025-07-26","cited_by_count":4,"area":"safety"},{"id":"2510.25117","title":"A Survey on Unlearning in Large Language Models","created":"2025-10-29","cited_by_count":4,"area":"safety"},{"id":"2604.21152","title":"Dialect vs Demographics: Quantifying LLM Bias from Implicit Linguistic Signals vs. Explicit User Profiles","created":"2026-04-22","cited_by_count":4,"area":"safety"},{"id":"2402.16889","title":"Generative Models are Self-Watermarked: Declaring Model Authentication through Re-Generation","created":"2024-02-23","cited_by_count":3,"area":"safety"},{"id":"2405.10128","title":"Red Teaming Language Models for Processing Contradictory Dialogues","created":"2024-05-16","cited_by_count":3,"area":"safety"},{"id":"2505.23015","title":"Detecting Stealthy Backdoor Samples based on Intra-class Distance for Large Language Models","created":"2025-05-29","cited_by_count":3,"area":"safety"},{"id":"2510.17006","title":"Online Learning Defense against Iterative Jailbreak Attacks via Prompt Optimization","created":"2025-10-19","cited_by_count":3,"area":"safety"},{"id":"2604.05242","title":"XMark: Reliable Multi-Bit Watermarking for LLM-Generated Texts","created":"2026-04-06","cited_by_count":3,"area":"safety"},{"id":"2504.17300","title":"The Ultimate Cookbook for Invisible Poison: Crafting Subtle Clean-Label Text Backdoors with Style Attributes","created":"2025-04-24","cited_by_count":2,"area":"safety"},{"id":"2510.12316","title":"Beating Harmful Stereotypes Through Facts: RAG-based Counter-speech Generation","created":"2025-10-14","cited_by_count":2,"area":"safety"},{"id":"2510.12993","title":"Tailored untruths: How personalisation challenges LLM safeguards","created":"2025-10-14","cited_by_count":2,"area":"safety"},{"id":"2512.16904","title":"How Good is Post-Hoc Watermarking With Language Model Rephrasing?","created":"2025-12-18","cited_by_count":2,"area":"safety"},{"id":"2603.20206","title":"Enhancing Safety of Large Language Models via Embedding Space Separation","created":"2026-03-01","cited_by_count":2,"area":"safety"},{"id":"2605.00348","title":"Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking","created":"2026-05-01","cited_by_count":2,"area":"safety"},{"id":"2211.09717","title":"UPTON: Preventing Authorship Leakage from Public Text Release via Data Poisoning","created":"2022-11-17","cited_by_count":1,"area":"safety"},{"id":"2410.10866","title":"CodeUnlearn: Amortized Zero-Shot Machine Unlearning in Language Models Using Discrete Concept","created":"2024-10-08","cited_by_count":1,"area":"safety"},{"id":"2411.11424","title":"Membership Inference Attack against Long-Context Large Language Models","created":"2024-11-18","cited_by_count":1,"area":"safety"},{"id":"2510.14470","title":"Stealthy Dual-Trigger Backdoors: Attacking Prompt Tuning in LM-Empowered Graph Foundation Models","created":"2025-10-16","cited_by_count":1,"area":"safety"},{"id":"2604.05318","title":"DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects","created":"2026-04-07","cited_by_count":1,"area":"safety"},{"id":"2604.22335","title":"Context-Fidelity Boosting: Enhancing Faithful Generation through Watermark-Inspired Decoding","created":"2026-04-24","cited_by_count":1,"area":"safety"},{"id":"2605.18239","title":"Multilingual jailbreaking of LLMs using low-resource languages","created":"2026-05-18","cited_by_count":1,"area":"safety"},{"id":"2605.23175","title":"Robust LLM Watermarking with Minimal Semantic Distortion for IP Protection","created":"2026-05-22","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":"2606.24063","title":"Selective Capability Unlearning in End-to-End Spoken Language Understanding","created":"2026-06-23","cited_by_count":1,"area":"safety"},{"id":"2606.25057","title":"LLM-Based Scientific Peer Review: Methods, Benchmarks, and Reliability Challenges","created":"2026-06-23","cited_by_count":1,"area":"safety"},{"id":"2607.05694","title":"Beyond Heuristic Tuning: Power-Calibrated LLM Watermarking","created":"2026-07-06","cited_by_count":1,"area":"safety"},{"id":"2608.20047","title":"Auditing Cross-Lingual Fairness in Language Model Watermarking","created":"2026-08-20","cited_by_count":1,"area":"safety"},{"id":"2608.27666","title":"Semantic Watermarking with Order-Robust Detection over Sub-sentence Units","created":"2026-08-27","cited_by_count":1,"area":"safety"},{"id":"2406.19642","title":"IDT: Dual-Task Adversarial Attacks for Privacy Protection","created":"2024-06-28","cited_by_count":0,"area":"safety"},{"id":"2412.06788","title":"Poison Attacks and Adversarial Prompts Against an Informed University Virtual Assistant","created":"2024-11-03","cited_by_count":0,"area":"safety"},{"id":"2508.18384","title":"Backprompting: Leveraging Synthetic Production Data for Health Advice Guardrails","created":"2025-08-25","cited_by_count":0,"area":"safety"},{"id":"2601.20282","title":"Memory Retrieval in Transformers: Insights from The Encoding Specificity Principle","created":"2026-01-28","cited_by_count":0,"area":"safety"},{"id":"2605.07032","title":"A Systematic Investigation of RL-Jailbreaking in LLMs","created":"2026-05-07","cited_by_count":0,"area":"safety"},{"id":"2605.11612","title":"When Emotion Becomes Trigger: Emotion-style dynamic Backdoor Attack Parasitising Large Language Models","created":"2026-05-12","cited_by_count":0,"area":"safety"},{"id":"2606.16110","title":"Auditing Machine Unlearning: A Systematic Research on Whether Models Truly Forget","created":"2026-06-15","cited_by_count":0,"area":"safety"},{"id":"2606.19660","title":"A Layered Security Framework Against Prompt Injection in RAG-Based Chatbots","created":"2026-06-17","cited_by_count":0,"area":"safety"},{"id":"2606.24163","title":"CORE-BREW: LLR-Based Soft Decoding for Robust Multi-Bit LLM Watermarking","created":"2026-06-23","cited_by_count":0,"area":"safety"},{"id":"2606.25380","title":"A Survey of Toxicity Detection and Mitigation Strategies for Multilingual Language Models","created":"2026-06-24","cited_by_count":0,"area":"safety"},{"id":"2606.27511","title":"When the Aggregator Cheats: Data-Free Backdoors in Federated LLM-based QA Systems","created":"2026-06-25","cited_by_count":0,"area":"safety"},{"id":"2606.30899","title":"Curvature-Guided Module Localization for Low-Rank Detoxification of Backdoored Large Language Models","created":"2026-06-29","cited_by_count":0,"area":"safety"},{"id":"2608.30748","title":"The Fragility of Jailbreak Robustness Across Operational States","created":"2026-08-31","cited_by_count":0,"area":"safety"},{"id":"2609.02177","title":"WeaveMark: Robust and Scalable Multi-bit LLM Watermarking via Coded Payload Spreading","created":"2026-09-02","cited_by_count":0,"area":"safety"},{"id":"2609.12472","title":"TripPattern: A Pattern-based Text Watermarking Method for Large Language Models","created":"2026-09-11","cited_by_count":0,"area":"safety"},{"id":"2610.18359","title":"Pin It on Anyone: Certified Targeted Displacement of Multi-Bit LLM Watermarks Without the Key","created":"2026-10-13","cited_by_count":0,"area":"safety"}],"next_cursor":null}