ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models
Privacy deletion requests often arrive sequentially, creating a continual unlearning challenge for deployed multimodal large language models (MLLMs). However, existing benchmarks mainly focus on static or short-sequence settings, offering limited support for evaluating continual privacy deletion on privacy-critical documents. To bridge this gap, we introduce ICU-Bench, an Identity-centric Continual Unlearning benchmark (pronounced ``I see you'') for privacy-critical multimodal documents. ICU-Bench contains 1,000 synthetic privacy-sensitive profiles from medical reports and labor contracts, comprising 9,500 document images, 16,000 question-answer pairs, and 100 sequential forget tasks. We ...
| Authors | Yuhang Wang, Wenjie Mei, Junkai Zhang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 7 May 2026 |
| Last updated at source | 3 August 2026 |
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