{"total":60,"rows":[{"id":"2502.14881","title":"A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations","created":"2025-02-14","cited_by_count":67,"area":"mllm"},{"id":"2504.17704","title":"Safety in Large Reasoning Models: A Survey","created":"2025-04-24","cited_by_count":64,"area":"lr"},{"id":"2411.19939","title":"VLSBench: Unveiling Visual Leakage in Multimodal Safety","created":"2024-11-29","cited_by_count":63,"area":"mllm"},{"id":"2505.11049","title":"GuardReasoner-VL: Safeguarding VLMs via Reinforced Reasoning","created":"2025-05-16","cited_by_count":42,"area":"lr"},{"id":"2507.02844","title":"Visual Contextual Attack: Jailbreaking MLLMs with Image-Driven Context Injection","created":"2025-07-03","cited_by_count":25,"area":"mllm"},{"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":"2501.18533","title":"Rethinking Bottlenecks in Safety Fine-Tuning of Vision Language Models","created":"2025-01-30","cited_by_count":21,"area":"lr"},{"id":"2508.07173","title":"Omni-SafetyBench: A Benchmark for Safety Evaluation of Audio-Visual Large Language Models","created":"2025-08-10","cited_by_count":18,"area":"safety"},{"id":"2502.13095","title":"Understanding and Rectifying Safety Perception Distortion in VLMs","created":"2025-02-18","cited_by_count":17,"area":"mllm"},{"id":"2501.03012","title":"Analyzing Finetuning Representation Shift for Multimodal LLMs Steering","created":"2025-01-06","cited_by_count":16,"area":"mllm"},{"id":"2503.11832","title":"Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-Tuning and Can Be Mitigated by Machine Unlearning","created":"2025-03-14","cited_by_count":16,"area":"mllm"},{"id":"2511.12982","title":"SafeGRPO: Self-Rewarded Multimodal Safety Alignment via Rule-Governed Policy Optimization","created":"2025-11-17","cited_by_count":12,"area":"lr"},{"id":"2504.12661","title":"VLMGuard-R1: Proactive Safety Alignment for VLMs via Reasoning-Driven Prompt Optimization","created":"2025-04-17","cited_by_count":10,"area":"lr"},{"id":"2507.01513","title":"SafePTR: Token-Level Jailbreak Defense in Multimodal LLMs via Prune-then-Restore Mechanism","created":"2025-07-02","cited_by_count":10,"area":"lr"},{"id":"2510.06871","title":"SaFeR-VLM: Toward Safety-aware Fine-grained Reasoning in Multimodal Models","created":"2025-10-08","cited_by_count":10,"area":"lr"},{"id":"2506.09353","title":"DAVSP: Safety Alignment for Large Vision-Language Models via Deep Aligned Visual Safety Prompt","created":"2025-06-11","cited_by_count":8,"area":"mllm"},{"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":"2505.21967","title":"Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack","created":"2025-05-28","cited_by_count":5,"area":"mllm"},{"id":"2505.24519","title":"AMIA: Automatic Masking and Joint Intention Analysis Makes LVLMs Robust Jailbreak Defenders","created":"2025-05-30","cited_by_count":5,"area":"mllm"},{"id":"2510.13190","title":"SHIELD: Classifier-Guided Prompting for Robust and Safer LVLMs","created":"2025-10-15","cited_by_count":5,"area":"lr"},{"id":"2511.11301","title":"EcoAlign: An Economically Rational Framework for Efficient LVLM Alignment","created":"2025-11-14","cited_by_count":5,"area":"lr"},{"id":"2603.15800","title":"Evolving Contextual Safety in Multi-Modal Large Language Models via Inference-Time Self-Reflective Memory","created":"2026-03-16","cited_by_count":5,"area":"lr"},{"id":"2507.11155","title":"Bridging the Gap in Vision Language Models in Identifying Unsafe Concepts Across Modalities","created":"2025-07-15","cited_by_count":4,"area":"lr"},{"id":"2508.15370","title":"Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation","created":"2025-08-21","cited_by_count":4,"area":"mllm"},{"id":"2510.13698","title":"Attention Misses Visual Risk: Risk-Adaptive Steering for Multimodal Safety Alignment","created":"2025-10-15","cited_by_count":4,"area":"alignment"},{"id":"2603.17372","title":"Understanding and Defending VLM Jailbreaks via Jailbreak-Related Representation Shift","created":"2026-03-18","cited_by_count":4,"area":"mllm"},{"id":"2605.15030","title":"WARD: Adversarially Robust Defense of Web Agents Against Prompt Injections","created":"2026-05-14","cited_by_count":4,"area":"agents"},{"id":"2505.24208","title":"Bootstrapping LLM Robustness for VLM Safety via Reducing the Pretraining Modality Gap","created":"2025-05-30","cited_by_count":3,"area":"mllm"},{"id":"2506.15734","title":"The Safety Reminder: A Soft Prompt to Reactivate Delayed Safety Awareness in Vision-Language Models","created":"2025-06-15","cited_by_count":3,"area":"mllm"},{"id":"2507.16856","title":"SIA: Enhancing Safety via Intent Awareness for Vision-Language Models","created":"2025-07-21","cited_by_count":3,"area":"mllm"},{"id":"2508.20655","title":"Improving Alignment in LVLMs with Debiased Self-Judgment","created":"2025-08-28","cited_by_count":3,"area":"mllm"},{"id":"2511.16743","title":"SafeR-CLIP: Mitigating NSFW Content in Vision-Language Models While Preserving Pre-Trained Knowledge","created":"2025-11-20","cited_by_count":3,"area":"mllm"},{"id":"2507.21637","title":"Self-Aware Safety Augmentation: Leveraging Internal Semantic Understanding to Enhance Safety in Vision-Language Models","created":"2025-07-29","cited_by_count":2,"area":"mllm"},{"id":"2508.09016","title":"A Survey on Training-free Alignment of Large Language Models","created":"2025-08-12","cited_by_count":2,"area":"alignment"},{"id":"2508.10955","title":"Empowering Multimodal LLMs with External Tools: A Comprehensive Survey","created":"2025-08-14","cited_by_count":2,"area":"mllm"},{"id":"2508.18649","title":"PRISM: Robust VLM Alignment with Principled Reasoning for Integrated Safety in Multimodality","created":"2025-08-26","cited_by_count":2,"area":"lr"},{"id":"2510.25179","title":"Agentic Moderation: Multi-Agent Design for Safer Vision-Language Models","created":"2025-10-29","cited_by_count":2,"area":"mllm"},{"id":"2511.16229","title":"Q-MLLM: Vector Quantization for Robust Multimodal Large Language Model Security","created":"2025-11-20","cited_by_count":2,"area":"mllm"},{"id":"2603.22094","title":"Principled Steering via Null-space Projection for Jailbreak Defense in Vision-Language Models","created":"2026-03-23","cited_by_count":2,"area":"mllm"},{"id":"2607.22716","title":"Visual Token Compression Enhances Robustness of MLLMs","created":"2026-07-21","cited_by_count":2,"area":"mllm"},{"id":"2505.17132","title":"Dynamic Token Reweighting for Robust Vision-Language Models","created":"2025-05-22","cited_by_count":1,"area":"mllm"},{"id":"2509.06759","title":"Aligning Large Vision-Language Models by Deep Reinforcement Learning and Direct Preference Optimization","created":"2025-09-08","cited_by_count":1,"area":"mllm"},{"id":"2510.17759","title":"VERA-V: Variational Inference Framework for Jailbreaking Vision-Language Models","created":"2025-10-20","cited_by_count":1,"area":"lr"},{"id":"2602.08136","title":"Robustness of Vision Language Models Against Split-Image Harmful Input Attacks","created":"2026-02-08","cited_by_count":1,"area":"mllm"},{"id":"2602.19570","title":"VALD: Multi-Stage Vision Attack Detection for Efficient LVLM Defense","created":"2026-02-23","cited_by_count":1,"area":"mllm"},{"id":"2602.24027","title":"GuardAlign: Test-time Safety Alignment in Multimodal Large Language Models","created":"2026-02-27","cited_by_count":1,"area":"mllm"},{"id":"2603.14825","title":"Two Birds, One Projection: Harmonizing Safety and Utility in LVLMs via Inference-time Feature Projection","created":"2026-03-16","cited_by_count":1,"area":"mllm"},{"id":"2506.06729","title":"Mitigating Object Hallucination via Robust Local Perception Search","created":"2025-06-07","cited_by_count":0,"area":"mllm"},{"id":"2509.21400","title":"SafeSteer: Adaptive Subspace Steering for Efficient Jailbreak Defense in Vision-Language Models","created":"2025-09-24","cited_by_count":0,"area":"safety"},{"id":"2603.14219","title":"Safety-Potential Pruning for Enhancing Safety Prompts Against VLM Jailbreaking Without Retraining","created":"2026-03-15","cited_by_count":0,"area":"mllm"},{"id":"2604.08881","title":"Targeted Interpretable Safety Neuron Enhancement for Multilingual Vision-Language Large Models","created":"2026-04-10","cited_by_count":0,"area":"alignment"},{"id":"2606.07706","title":"MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language Models","created":"2026-06-05","cited_by_count":0,"area":"mllm"},{"id":"2607.21151","title":"V-DEAL: Diagnosing Video Safety De-Calibration as an Understanding-Refusal Coupling Failure","created":"2026-07-23","cited_by_count":0,"area":"alignment"},{"id":"2607.27917","title":"One Anchor for All: Unified Multilingual and Multimodal Safety Alignment for LVLMs","created":"2026-07-30","cited_by_count":0,"area":"mllm"},{"id":"2607.28969","title":"SafeNexus: Discovering and Steering Modality-Universal Safety Neurons in MLLMs","created":"2026-07-31","cited_by_count":0,"area":"mllm"},{"id":"2608.07535","title":"Evolving Safety Landscape of Multi-modal Large Language Models: A Survey of Emerging Threats and Safeguards","created":"2026-07-27","cited_by_count":0,"area":"mllm"},{"id":"2608.10327","title":"Toward a Theory of Value in AI Alignment","created":"2026-08-10","cited_by_count":0,"area":"alignment"},{"id":"2609.02082","title":"Transfer Safety Awareness for Cross-Modal Safety Drift in Multimodal Large Language Models","created":"2026-09-02","cited_by_count":0,"area":"mllm"},{"id":"2609.18328","title":"Visual Compliance via Executable Safety Rule Entailment","created":"2026-09-16","cited_by_count":0,"area":null},{"id":"2609.33640","title":"SafeMol: Dual-Modality Safety Alignment for Molecular Multimodal Models","created":"2026-09-27","cited_by_count":0,"area":"alignment"}],"next_cursor":null}