✨MVI-Bench: A Comprehensive Benchmark for Evaluating Robustness to Misleading Visual Inputs in LVLMs
📝 Summary:
MVI-Bench introduces a new benchmark to evaluate Large Vision-Language Models robustness against misleading visual inputs. It utilizes a hierarchical taxonomy and a novel metric to uncover significant vulnerabilities in state-of-the-art LVLMs.
🔹 Publication Date: Published on Nov 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.14159
• PDF: https://arxiv.org/pdf/2511.14159
• Github: https://github.com/chenyil6/MVI-Bench
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✓ https://t.iss.one/DataScienceT
#LVLMs #ComputerVision #AIrobustness #MachineLearning #AI
📝 Summary:
MVI-Bench introduces a new benchmark to evaluate Large Vision-Language Models robustness against misleading visual inputs. It utilizes a hierarchical taxonomy and a novel metric to uncover significant vulnerabilities in state-of-the-art LVLMs.
🔹 Publication Date: Published on Nov 18
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.14159
• PDF: https://arxiv.org/pdf/2511.14159
• Github: https://github.com/chenyil6/MVI-Bench
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LVLMs #ComputerVision #AIrobustness #MachineLearning #AI