{"total":72,"rows":[{"id":"2401.13601","title":"MM-LLMs: Recent Advances in MultiModal Large Language Models","created":"2024-01-24","cited_by_count":278,"area":"mllm"},{"id":"2311.17600","title":"MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models","created":"2023-11-29","cited_by_count":274,"area":"mllm"},{"id":"2402.12451","title":"The Revolution of Multimodal Large Language Models: A Survey","created":"2024-02-19","cited_by_count":137,"area":"mllm"},{"id":"2403.09513","title":"AdaShield: Safeguarding Multimodal Large Language Models from Structure-based Attack via Adaptive Shield Prompting","created":"2024-03-14","cited_by_count":125,"area":"mllm"},{"id":"2406.04031","title":"Jailbreak Vision Language Models via Bi-Modal Adversarial Prompt","created":"2024-06-06","cited_by_count":109,"area":"mllm"},{"id":"2406.12030","title":"SPA-VL: A Comprehensive Safety Preference Alignment Dataset for Vision Language Model","created":"2024-06-17","cited_by_count":85,"area":"mllm"},{"id":"2407.07403","title":"A Survey of Attacks on Large Vision-Language Models: Resources, Advances, and Future Trends","created":"2024-07-10","cited_by_count":84,"area":"mllm"},{"id":"2402.00357","title":"Safety of Multimodal Large Language Models on Images and Texts","created":"2024-02-01","cited_by_count":75,"area":"mllm"},{"id":"2405.16640","title":"A Survey of Multimodal Large Language Model from A Data-centric Perspective","created":"2024-05-26","cited_by_count":75,"area":"mllm"},{"id":"2407.01599","title":"JailbreakZoo: Survey, Landscapes, and Horizons in Jailbreaking Large Language and Vision-Language Models","created":"2024-06-26","cited_by_count":70,"area":"mllm"},{"id":"2404.07214","title":"Exploring the Frontier of Vision-Language Models: A Survey of Current Methodologies and Future Directions","created":"2024-02-20","cited_by_count":68,"area":"mllm"},{"id":"2411.19939","title":"VLSBench: Unveiling Visual Leakage in Multimodal Safety","created":"2024-11-29","cited_by_count":63,"area":"mllm"},{"id":"2410.06625","title":"ETA: Evaluating Then Aligning Safety of Vision Language Models at Inference Time","created":"2024-10-09","cited_by_count":60,"area":"mllm"},{"id":"2410.09421","title":"VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment","created":"2024-10-12","cited_by_count":58,"area":"mllm"},{"id":"2411.16721","title":"Steering Away from Harm: An Adaptive Approach to Defending Vision Language Model Against Jailbreaks","created":"2024-11-23","cited_by_count":48,"area":"mllm"},{"id":"2412.13817","title":"Nullu: Mitigating Object Hallucinations in Large Vision-Language Models via HalluSpace Projection","created":"2024-12-18","cited_by_count":46,"area":"mllm"},{"id":"2407.06438","title":"SOLO: A Single Transformer for Scalable Vision-Language Modeling","created":"2024-07-08","cited_by_count":37,"area":"mllm"},{"id":"2502.14744","title":"HiddenDetect: Detecting Jailbreak Attacks against Large Vision-Language Models via Monitoring Hidden States","created":"2025-02-20","cited_by_count":33,"area":"mllm"},{"id":"2406.16449","title":"Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models","created":"2024-06-24","cited_by_count":29,"area":"mllm"},{"id":"2412.00832","title":"EventGPT: Event Stream Understanding with Multimodal Large Language Models","created":"2024-12-01","cited_by_count":28,"area":"mllm"},{"id":"2403.09037","title":"The First to Know: How Token Distributions Reveal Hidden Knowledge in Large Vision-Language Models?","created":"2024-03-14","cited_by_count":26,"area":"mllm"},{"id":"2406.15279","title":"Safe Inputs but Unsafe Output: Benchmarking Cross-modality Safety Alignment of Large Vision-Language Model","created":"2024-06-21","cited_by_count":26,"area":"mllm"},{"id":"2407.21659","title":"Cross-modality Information Check for Detecting Jailbreaking in Multimodal Large Language Models","created":"2024-07-31","cited_by_count":25,"area":"mllm"},{"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":"2407.02477","title":"Understanding Alignment in Multimodal LLMs: A Comprehensive Study","created":"2024-07-02","cited_by_count":23,"area":"mllm"},{"id":"2410.09047","title":"Unraveling and Mitigating Safety Alignment Degradation of Vision-Language Models","created":"2024-10-11","cited_by_count":23,"area":"mllm"},{"id":"2410.23687","title":"Adversarial Attacks of Vision Tasks in the Past 10 Years: A Survey","created":"2024-10-31","cited_by_count":23,"area":"mllm"},{"id":"2404.05264","title":"Unbridled Icarus: A Survey of the Potential Perils of Image Inputs in Multimodal Large Language Model Security","created":"2024-04-08","cited_by_count":19,"area":"mllm"},{"id":"2412.18826","title":"RapGuard: Safeguarding Multimodal Large Language Models via Rationale-aware Defensive Prompting","created":"2024-12-25","cited_by_count":19,"area":"mllm"},{"id":"2502.10486","title":"VLM-Guard: Safeguarding Vision-Language Models via Fulfilling Safety Alignment Gap","created":"2025-02-14","cited_by_count":17,"area":"mllm"},{"id":"2502.13095","title":"Understanding and Rectifying Safety Perception Distortion in VLMs","created":"2025-02-18","cited_by_count":17,"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":"2407.08583","title":"The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective","created":"2024-07-11","cited_by_count":15,"area":"mllm"},{"id":"2311.13258","title":"ViStruct: Visual Structural Knowledge Extraction via Curriculum Guided Code-Vision Representation","created":"2023-11-22","cited_by_count":13,"area":"mllm"},{"id":"2502.12562","title":"SEA: Low-Resource Safety Alignment for Multimodal Large Language Models via Synthetic Embeddings","created":"2025-02-18","cited_by_count":11,"area":"mllm"},{"id":"2505.23793","title":"USB: A Comprehensive and Unified Safety Evaluation Benchmark for Multimodal Large Language Models","created":"2025-05-26","cited_by_count":10,"area":"mllm"},{"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":"2501.02029","title":"Spot Risks Before Speaking! Unraveling Safety Attention Heads in Large Vision-Language Models","created":"2025-01-03","cited_by_count":7,"area":"mllm"},{"id":"2407.11522","title":"FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models","created":"2024-07-16","cited_by_count":6,"area":"mllm"},{"id":"2510.02790","title":"MaskCD: Mitigating LVLM Hallucinations by Image Head Masked Contrastive Decoding","created":"2025-10-03","cited_by_count":6,"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":"2503.10872","title":"TAIJI: Textual Anchoring for Immunizing Jailbreak Images in Vision Language Models","created":"2025-03-13","cited_by_count":3,"area":"mllm"},{"id":"2505.11741","title":"MTRE: Multi-Token Reliability Estimation for Hallucination Detection in VLMs","created":"2025-05-16","cited_by_count":3,"area":"mllm"},{"id":"2505.17812","title":"Seeing It or Not? Interpretable Vision-aware Latent Steering to Mitigate Object Hallucinations","created":"2025-05-23","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":"2508.20655","title":"Improving Alignment in LVLMs with Debiased Self-Judgment","created":"2025-08-28","cited_by_count":3,"area":"mllm"},{"id":"2512.12089","title":"VEGAS: Mitigating Hallucinations in Large Vision-Language Models via Vision-Encoder Attention Guided Adaptive Steering","created":"2025-12-12","cited_by_count":3,"area":"mllm"},{"id":"2601.04043","title":"When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life","created":"2026-01-07","cited_by_count":3,"area":"mllm"},{"id":"2410.20109","title":"GiVE: Guiding Visual Encoder to Perceive Overlooked Information","created":"2024-10-26","cited_by_count":2,"area":"mllm"},{"id":"2505.08971","title":"Prioritizing Image-Related Tokens Enhances Vision-Language Pre-Training","created":"2025-05-13","cited_by_count":2,"area":"mllm"},{"id":"2505.10541","title":"Exploring Implicit Visual Misunderstandings in Multimodal Large Language Models through Attention Analysis","created":"2025-05-15","cited_by_count":2,"area":"mllm"},{"id":"2506.00930","title":"Aligning VLM Assistants with Personalized Situated Cognition","created":"2025-06-01","cited_by_count":2,"area":"mllm"},{"id":"2508.10955","title":"Empowering Multimodal LLMs with External Tools: A Comprehensive Survey","created":"2025-08-14","cited_by_count":2,"area":"mllm"},{"id":"2509.04403","title":"Self-adaptive Dataset Construction for Real-World Multimodal Safety Scenarios","created":"2025-09-04","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":"2505.05318","title":"Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects","created":"2025-05-08","cited_by_count":1,"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":"2604.20544","title":"Evian: Towards Explainable Visual Instruction-tuning Data Auditing","created":"2026-04-22","cited_by_count":1,"area":"mllm"},{"id":"2607.02089","title":"ESC: Emotional Self-Correction for Reliable Vision-Language Models","created":"2026-07-01","cited_by_count":1,"area":"mllm"},{"id":"2503.10661","title":"CeTAD: Towards Certified Toxicity-Aware Distance in Vision Language Models","created":"2025-03-08","cited_by_count":0,"area":"mllm"},{"id":"2507.20994","title":"Security Tensors as a Cross-Modal Bridge: Extending Text-Aligned Safety to Vision in LVLM","created":"2025-07-28","cited_by_count":0,"area":"mllm"},{"id":"2511.13458","title":"Trust in Vision-Language Models: Insights from a Participatory User Workshop","created":"2025-11-17","cited_by_count":0,"area":"mllm"},{"id":"2602.21441","title":"Causal Decoding for Hallucination-Resistant Multimodal Large Language Models","created":"2026-02-24","cited_by_count":0,"area":"mllm"},{"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":"2603.16558","title":"Segmentation-Based Attention Entropy: Detecting and Mitigating Object Hallucinations in Large Vision-Language Models","created":"2026-03-17","cited_by_count":0,"area":"mllm"},{"id":"2604.06502","title":"VLMShield: Efficient and Robust Defense of Vision-Language Models against Malicious Prompts","created":"2026-04-07","cited_by_count":0,"area":"mllm"},{"id":"2607.21600","title":"Securing Multimodal AI through Internal Information Decomposition","created":"2026-05-03","cited_by_count":0,"area":"mllm"},{"id":"2609.04720","title":"Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models","created":"2026-09-04","cited_by_count":0,"area":"mllm"},{"id":"2609.10613","title":"Understanding In-Context Multimodal Jailbreaks via Posterior Reweighting","created":"2026-09-08","cited_by_count":0,"area":"mllm"},{"id":"2609.14258","title":"SPARK: Representation-Level KV Memory Alignment for Safer Vision-Language Models","created":"2026-09-13","cited_by_count":0,"area":"mllm"},{"id":"2609.19693","title":"IMFD: End-to-end Multi-Face Forgery Detection through Instruction-based Large Vision-Language Models","created":"2026-09-17","cited_by_count":0,"area":"mllm"}],"next_cursor":null}