{"total":66,"rows":[{"id":"2510.14276","title":"Qwen3Guard Technical Report","created":"2025-10-16","cited_by_count":155,"area":"safety"},{"id":"2408.15221","title":"LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet","created":"2024-08-27","cited_by_count":151,"area":"safety"},{"id":"2510.09023","title":"The Attacker Moves Second: Stronger Adaptive Attacks Bypass Defenses Against Llm Jailbreaks and Prompt Injections","created":"2025-10-10","cited_by_count":129,"area":"safety"},{"id":"2412.17686","title":"Large Language Model Safety: A Holistic Survey","created":"2024-12-23","cited_by_count":59,"area":"safety"},{"id":"2503.15754","title":"AutoRedTeamer: Autonomous Red Teaming with Lifelong Attack Integration","created":"2025-03-20","cited_by_count":43,"area":"safety"},{"id":"2504.01550","title":"Representation Bending for Large Language Model Safety","created":"2025-04-02","cited_by_count":30,"area":"safety"},{"id":"2411.03343","title":"What Features in Prompts Jailbreak LLMs? Investigating the Mechanisms Behind Attacks","created":"2024-11-02","cited_by_count":29,"area":"safety"},{"id":"2503.16431","title":"OpenAI's Approach to External Red Teaming for AI Models and Systems","created":"2025-01-24","cited_by_count":28,"area":"safety"},{"id":"2501.07238","title":"Lessons From Red Teaming 100 Generative AI Products","created":"2025-01-13","cited_by_count":23,"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":"2503.10619","title":"Tempest: Autonomous Multi-Turn Jailbreaking of Large Language Models with Tree Search","created":"2025-03-13","cited_by_count":17,"area":"safety"},{"id":"2409.15398","title":"Attack Atlas: A Practitioner's Perspective on Challenges and Pitfalls in Red Teaming GenAI","created":"2024-09-23","cited_by_count":16,"area":"safety"},{"id":"2510.27062","title":"Consistency Training Helps Stop Sycophancy and Jailbreaks","created":"2025-10-31","cited_by_count":16,"area":"safety"},{"id":"2505.19056","title":"An Embarrassingly Simple Defense Against LLM Abliteration Attacks","created":"2025-05-25","cited_by_count":13,"area":"safety"},{"id":"2509.24296","title":"DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models","created":"2025-09-29","cited_by_count":12,"area":"safety"},{"id":"2504.00441","title":"No Free Lunch with Guardrails","created":"2025-04-01","cited_by_count":11,"area":"safety"},{"id":"2408.11851","title":"SAGE-RT: Synthetic Alignment data Generation for Safety Evaluation and Red Teaming","created":"2024-08-14","cited_by_count":10,"area":"safety"},{"id":"2410.22143","title":"AmpleGCG-Plus: A Strong Generative Model of Adversarial Suffixes to Jailbreak LLMs with Higher Success Rates in Fewer Attempts","created":"2024-10-29","cited_by_count":10,"area":"safety"},{"id":"2504.13562","title":"DETAM: Defending LLMs Against Jailbreak Attacks via Targeted Attention Modification","created":"2025-04-18","cited_by_count":10,"area":"safety"},{"id":"2502.19041","title":"Beyond Surface-Level Patterns: An Essence-Driven Defense Framework Against Jailbreak Attacks in LLMs","created":"2025-02-26","cited_by_count":9,"area":"safety"},{"id":"2511.12710","title":"Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs","created":"2025-11-16","cited_by_count":8,"area":"safety"},{"id":"2505.15753","title":"Scalable Defense against In-the-wild Jailbreaking Attacks with Safety Context Retrieval","created":"2025-05-21","cited_by_count":7,"area":"safety"},{"id":"2510.21910","title":"Adversarial D\\'ej\\`a Vu: Jailbreak Dictionary Learning for Stronger Generalization to Unseen Attacks","created":"2025-10-24","cited_by_count":7,"area":"safety"},{"id":"2410.01088","title":"Exploring Empty Spaces: Human-in-the-Loop Data Augmentation","created":"2024-10-01","cited_by_count":6,"area":"safety"},{"id":"2504.00446","title":"Exposing the Ghost in the Transformer: Abnormal Detection for Large Language Models via Hidden State Forensics","created":"2025-04-01","cited_by_count":6,"area":"safety"},{"id":"2506.05446","title":"Sentinel: SOTA model to protect against prompt injections","created":"2025-06-05","cited_by_count":6,"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":"2607.19829","title":"DARWIN: Evolving Jailbreak Adversary and Guardrail for LLM Safety Evaluation and Protection","created":"2026-07-22","cited_by_count":6,"area":"safety"},{"id":"2505.22037","title":"Jailbreak Distillation: Renewable Safety Benchmarking","created":"2025-05-28","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":"2506.17299","title":"Toward Principled LLM Safety Testing: Solving the Jailbreak Oracle Problem","created":"2025-06-17","cited_by_count":4,"area":"safety"},{"id":"2508.12072","title":"Mitigating Jailbreaks with Intent-Aware LLMs","created":"2025-08-16","cited_by_count":4,"area":"safety"},{"id":"2510.06594","title":"Do Internal Layers of LLMs Reveal Patterns for Jailbreak Detection?","created":"2025-10-08","cited_by_count":3,"area":"safety"},{"id":"2605.08778","title":"Not All Turns Matter: Credit Assignment for Multi-Turn Jailbreaking","created":"2026-05-09","cited_by_count":3,"area":"safety"},{"id":"2605.18168","title":"Acoustic Interference: A New Paradigm Weaponizing Acoustic Latent Semantic for Universal Jailbreak against Large Audio Language Models","created":"2026-05-18","cited_by_count":3,"area":"safety"},{"id":"2411.17075","title":"Don't Command, Cultivate: An Exploratory Study of System-2 Alignment","created":"2024-11-26","cited_by_count":2,"area":"safety"},{"id":"2509.05471","title":"Behind the Mask: Benchmarking Camouflaged Jailbreaks in Large Language Models","created":"2025-09-05","cited_by_count":2,"area":"safety"},{"id":"2603.02588","title":"ExpGuard: LLM Content Moderation in Specialized Domains","created":"2026-03-03","cited_by_count":2,"area":"safety"},{"id":"2606.08044","title":"When Behavioral Safety Evaluation Fails: A Representation-Level Perspective","created":"2026-06-06","cited_by_count":2,"area":"safety"},{"id":"2607.13075","title":"The Entanglement Wall: Activation-Space Probes as Risk Detectors, Not Context Adjudicators","created":"2026-07-12","cited_by_count":2,"area":"safety"},{"id":"2509.25843","title":"ASGuard: Activation-Scaling Guard to Mitigate Targeted Jailbreaking Attack","created":"2025-09-30","cited_by_count":1,"area":"safety"},{"id":"2510.17000","title":"Bits Leaked per Query: Information-Theoretic Bounds on Adversarial Attacks against LLMs","created":"2025-10-19","cited_by_count":1,"area":"safety"},{"id":"2511.03271","title":"Let the Bees Find the Weak Spots: A Path Planning Perspective on Multi-Turn Jailbreak Attacks against LLMs","created":"2025-11-05","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":"2602.12318","title":"Abstractive Red-Teaming of Language Model Character","created":"2026-02-12","cited_by_count":1,"area":"safety"},{"id":"2603.10807","title":"Risk-Adjusted Harm Scoring for Automated Red Teaming for LLMs in Financial Services","created":"2026-03-11","cited_by_count":1,"area":"safety"},{"id":"2605.15598","title":"Compositional Jailbreaking: An Empirical Analysis of Mutator Chain Interactions in Aligned LLMs","created":"2026-05-15","cited_by_count":1,"area":"safety"},{"id":"2606.12342","title":"ALIGNBEAM : Inference-Time Alignment Transfer via Cross-Vocabulary Logit Mixing","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":"2608.14577","title":"HarmProfile: Characterizing Harmful Distributions in Frontier LLMs","created":"2026-06-11","cited_by_count":1,"area":"safety"},{"id":"2608.23028","title":"PsychJail: Exploring Psychological Jailbreaks via Multi-Turn Persuasion of LLM Policies","created":"2026-08-24","cited_by_count":1,"area":"safety"},{"id":"2610.04985","title":"Hidden Risks of Jev: An Empirical Study of Security, Privacy, and Dual Use","created":"2026-10-04","cited_by_count":1,"area":"safety"},{"id":"2505.10066","title":"Dark LLMs: The Growing Threat of Unaligned AI Models","created":"2025-05-15","cited_by_count":0,"area":"safety"},{"id":"2508.06296","title":"LLM Robustness Leaderboard v1 --Technical report","created":"2025-08-08","cited_by_count":0,"area":"safety"},{"id":"2605.03226","title":"Self-Mined Hardness for Safety Fine-Tuning","created":"2026-05-04","cited_by_count":0,"area":"safety"},{"id":"2605.06213","title":"Beyond Fixed Benchmarks and Worst-Case Attacks: Dynamic Boundary Evaluation for Language Models","created":"2026-05-07","cited_by_count":0,"area":"safety"},{"id":"2605.11730","title":"Persona-Conditioned Adversarial Prompting: Multi-Identity Red-Teaming for Adversarial Discovery and Mitigation","created":"2026-05-12","cited_by_count":0,"area":"safety"},{"id":"2605.13411","title":"Model-Agnostic Lifelong LLM Safety via Externalized Attack-Defense Co-Evolution","created":"2026-05-13","cited_by_count":0,"area":"safety"},{"id":"2605.19377","title":"The Evaluation Game: Beyond Static LLM Benchmarking","created":"2026-05-19","cited_by_count":0,"area":"safety"},{"id":"2606.25782","title":"Do Encoders Suffice? A Systematic Comparison of Encoder and Decoder Safety Judges for LLM Adversarial Evaluation","created":"2026-06-24","cited_by_count":0,"area":"safety"},{"id":"2606.26377","title":"Verifying Intent and Harm: A Unified Defense Against LLM-Generated Threats","created":"2026-06-24","cited_by_count":0,"area":"safety"},{"id":"2608.09624","title":"Measuring the Wrong Thing: Internal Harmfulness Scores Anti-Rank Successful Jailbreaks","created":"2026-08-10","cited_by_count":0,"area":"safety"},{"id":"2609.21088","title":"Origin Is All You Need: Provenance-Aware Transformers for Structural Trust-Boundary Separation","created":"2026-09-17","cited_by_count":0,"area":"safety"},{"id":"2609.36657","title":"Constitutional adapters: Inference-time interventions for misalignment and misuse","created":"2026-09-29","cited_by_count":0,"area":"safety"},{"id":"2610.05541","title":"Don't Judge an LLM Only by Its Activations: Discovering Suppressed Safety Features via Counterfactual Activation Potential","created":"2026-10-04","cited_by_count":0,"area":"safety"},{"id":"2610.10276","title":"PatchBench: Measuring Collateral Damage in Activation Patching","created":"2026-10-07","cited_by_count":0,"area":"safety"}],"next_cursor":null}