{"total":31,"rows":[{"id":"2310.02446","title":"Low-Resource Languages Jailbreak GPT-4","created":"2023-10-03","cited_by_count":309,"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":"2310.06356","title":"A Semantic Invariant Robust Watermark for Large Language Models","created":"2023-10-10","cited_by_count":112,"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":"2405.10051","title":"MarkLLM: An Open-Source Toolkit for LLM Watermarking","created":"2024-05-16","cited_by_count":95,"area":"safety"},{"id":"2301.12867","title":"Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity","created":"2023-01-30","cited_by_count":89,"area":"safety"},{"id":"2406.18682","title":"The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm","created":"2024-06-26","cited_by_count":70,"area":"safety"},{"id":"2307.16230","title":"An Unforgeable Publicly Verifiable Watermark for Large Language Models","created":"2023-07-30","cited_by_count":65,"area":"safety"},{"id":"2506.09443","title":"LLMs Cannot Reliably Judge (Yet?): A Comprehensive Assessment on the Robustness of LLM-as-a-Judge","created":"2025-06-11","cited_by_count":37,"area":"safety"},{"id":"2310.08920","title":"Embarrassingly Simple Text Watermarks","created":"2023-10-13","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":"2406.12354","title":"Cross-Lingual Unlearning of Selective Knowledge in Multilingual Language Models","created":"2024-06-18","cited_by_count":20,"area":"safety"},{"id":"2310.00833","title":"Necessary and Sufficient Watermark for Large Language Models","created":"2023-10-02","cited_by_count":19,"area":"safety"},{"id":"2406.13748","title":"Learn and Unlearn: Addressing Misinformation in Multilingual LLMs","created":"2024-06-19","cited_by_count":12,"area":"safety"},{"id":"2404.18534","title":"Evaluating and Mitigating Linguistic Discrimination in Large Language Models","created":"2024-04-29","cited_by_count":8,"area":"safety"},{"id":"2505.02344","title":"An End-to-End Model for Logits-Based Large Language Models Watermarking","created":"2025-05-05","cited_by_count":4,"area":"safety"},{"id":"2508.20228","title":"Robustness Assessment and Enhancement of Text Watermarking for Google's SynthID","created":"2025-08-27","cited_by_count":4,"area":"safety"},{"id":"2601.03699","title":"RedBench: A Universal Dataset for Comprehensive Red Teaming of Large Language Models","created":"2026-01-07","cited_by_count":3,"area":"safety"},{"id":"2605.14404","title":"Knowledge Beyond Language: Bridging the Gap in Multilingual Machine Unlearning Evaluation","created":"2026-05-14","cited_by_count":3,"area":"safety"},{"id":"2602.06911","title":"TamperBench: Systematically Stress-Testing LLM Safety Under Fine-Tuning and Tampering","created":"2026-02-06","cited_by_count":2,"area":"safety"},{"id":"2604.18976","title":"STAR-Teaming: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teaming","created":"2026-04-21","cited_by_count":2,"area":"safety"},{"id":"2507.08288","title":"Invariant-based Robust Weights Watermark for Large Language Models","created":"2025-07-11","cited_by_count":1,"area":"safety"},{"id":"2509.23381","title":"Guard Vector: Beyond English LLM Guardrails with Task-Vector Composition and Streaming-Aware Prefix SFT","created":"2025-09-27","cited_by_count":0,"area":"safety"},{"id":"2511.03880","title":"Evaluating Machine Translation Datasets for Low-Web Data Languages: A Gendered Lens","created":"2025-11-05","cited_by_count":0,"area":"safety"},{"id":"2605.27138","title":"ICCU: In-Context Continual Unlearning via Pattern-Induced Refusal Rules","created":"2026-05-26","cited_by_count":0,"area":"safety"},{"id":"2606.26015","title":"The Tatoxa System for Text Detoxification in Low-Resource Languages: The Case of Tatar","created":"2026-06-24","cited_by_count":0,"area":"safety"},{"id":"2607.18445","title":"ChainMark: Model-Free LLM Watermarking with Closed-Form Calibration","created":"2026-07-20","cited_by_count":0,"area":"safety"},{"id":"2607.25375","title":"Inspect India Evals: An Open Benchmarking Framework for Evaluating Large Language Models in the Indian Linguistic and Cultural Context","created":"2026-07-28","cited_by_count":0,"area":"safety"},{"id":"2608.27512","title":"Quantization-Triggered Backdoors in Language Models: Cross-Quantizer Transferability and the Validation--Deployment Gap","created":"2026-08-27","cited_by_count":0,"area":"safety"},{"id":"2609.06573","title":"A Translational Note on AI Safety Evaluation","created":"2026-09-06","cited_by_count":0,"area":"safety"},{"id":"2609.40286","title":"Linguistic Loopholes in LLM Unlearning: From a 174-Language Benchmark to Coverage-Aware Unlearning","created":"2026-09-30","cited_by_count":0,"area":"safety"}],"next_cursor":null}