{"total":32,"rows":[{"id":"2406.02630","title":"AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathways","created":"2024-06-04","cited_by_count":127,"area":null},{"id":"2402.18649","title":"A New Era in LLM Security: Exploring Security Concerns in Real-World LLM-based Systems","created":"2024-02-28","cited_by_count":77,"area":null},{"id":"2502.08745","title":"IHEval: Evaluating Language Models on Following the Instruction Hierarchy","created":"2025-02-12","cited_by_count":53,"area":null},{"id":"2311.04235","title":"Can LLMs Follow Simple Rules?","created":"2023-11-06","cited_by_count":46,"area":null},{"id":"2410.07137","title":"Cheating Automatic LLM Benchmarks: Null Models Achieve High Win Rates","created":"2024-10-09","cited_by_count":45,"area":null},{"id":"2403.04786","title":"Breaking Down the Defenses: A Comparative Survey of Attacks on Large Language Models","created":"2024-03-03","cited_by_count":44,"area":null},{"id":"2402.11755","title":"SPML: A DSL for Defending Language Models Against Prompt Attacks","created":"2024-02-19","cited_by_count":34,"area":null},{"id":"2502.15851","title":"Control Illusion: The Failure of Instruction Hierarchies in Large Language Models","created":"2025-02-21","cited_by_count":33,"area":null},{"id":"2409.14457","title":"Large Model Based Agents: State-of-the-Art, Cooperation Paradigms, Security and Privacy, and Future Trends","created":"2024-09-22","cited_by_count":26,"area":null},{"id":"2410.07959","title":"COMPL-AI Framework: A Technical Interpretation and LLM Benchmarking Suite for the EU Artificial Intelligence Act","created":"2024-10-10","cited_by_count":24,"area":null},{"id":"2404.06921","title":"GoEX: Perspectives and Designs Towards a Runtime for Autonomous LLM Applications","created":"2024-04-10","cited_by_count":23,"area":null},{"id":"2406.07954","title":"Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition","created":"2024-06-12","cited_by_count":20,"area":null},{"id":"2402.14836","title":"Stealthy Attack on Large Language Model based Recommendation","created":"2024-02-18","cited_by_count":19,"area":null},{"id":"2406.06737","title":"Raccoon: Prompt Extraction Benchmark of LLM-Integrated Applications","created":"2024-06-10","cited_by_count":16,"area":null},{"id":"2501.07927","title":"Gandalf the Red: Adaptive Security for LLMs","created":"2025-01-14","cited_by_count":7,"area":null},{"id":"2505.00626","title":"The Illusion of Role Separation: Hidden Shortcuts in LLM Role Learning (and How to Fix Them)","created":"2025-05-01","cited_by_count":6,"area":null},{"id":"2410.09569","title":"Are You Human? An Adversarial Benchmark to Expose LLMs","created":"2024-10-12","cited_by_count":5,"area":null},{"id":"2412.13426","title":"PromptKeeper: Safeguarding System Prompts for LLMs","created":"2024-12-18","cited_by_count":5,"area":null},{"id":"2608.28945","title":"Automated Researchers Can Mitigate Well-characterized Alignment Failures","created":"2026-08-28","cited_by_count":5,"area":null},{"id":"2402.12617","title":"Generative AI Security: Challenges and Countermeasures","created":"2024-02-20","cited_by_count":4,"area":null},{"id":"2506.07330","title":"JavelinGuard: Low-Cost Transformer Architectures for LLM Security","created":"2025-06-09","cited_by_count":4,"area":null},{"id":"2412.18551","title":"Libra-Leaderboard: Towards Responsible AI through a Balanced Leaderboard of Safety and Capability","created":"2024-12-24","cited_by_count":2,"area":null},{"id":"2607.26228","title":"Steering Instruction Hierarchies at Inference Time","created":"2026-07-28","cited_by_count":2,"area":null},{"id":"2403.10559","title":"Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI","created":"2024-03-14","cited_by_count":1,"area":null},{"id":"2410.18114","title":"Bridging Today and the Future of Humanity: AI Safety in 2024 and Beyond","created":"2024-10-09","cited_by_count":1,"area":null},{"id":"2609.15017","title":"PIDS-Bench: Evaluating Prompt-Injection Detectors Under Over-Defense, Obfuscation, and Distribution Shift","created":"2026-09-14","cited_by_count":1,"area":null},{"id":"2512.03720","title":"Context-Aware Hierarchical Learning: A Two-Step Paradigm towards Safer LLMs","created":"2025-12-03","cited_by_count":0,"area":null},{"id":"2605.09737","title":"System-Prompt Anchoring with Cross-Attention Layers","created":"2026-05-10","cited_by_count":0,"area":null},{"id":"2605.15134","title":"Training ML Models with Predictable Failures","created":"2026-05-14","cited_by_count":0,"area":null},{"id":"2605.30521","title":"Evaluating using Mock Tool Calls to Quarantine Untrusted Prompt Inputs","created":"2026-05-28","cited_by_count":0,"area":null},{"id":"2607.28959","title":"Efficient LLM Adversarial Training via Low-Rank Defense and Circuit-Guided Surrogates","created":"2026-07-31","cited_by_count":0,"area":null},{"id":"2609.37040","title":"Selecting The Most Informative Tokens in Natural Language Autoencoders","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}