TCAP detects backdoor samples in MLLM fine-tuning via tri-component attention profiling, GMM-based head identification, and EM vote aggregation.
Revisiting backdoor attacks against large vision-language models.arXiv preprint arXiv:2406.18844
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A comprehensive survey that taxonomizes safety threats to large models and agents, reviews defenses and benchmarks, and outlines open challenges.
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TCAP: Tri-Component Attention Profiling for Unsupervised Backdoor Detection in MLLM Fine-Tuning
TCAP detects backdoor samples in MLLM fine-tuning via tri-component attention profiling, GMM-based head identification, and EM vote aggregation.
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Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety
A comprehensive survey that taxonomizes safety threats to large models and agents, reviews defenses and benchmarks, and outlines open challenges.