Papers by Boris Mikheev

1 papers
CLEAR: Character Unlearning in Textual and Visual Modalities (2025.findings-acl)

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Challenge: Existing methods for removing private or hazardous data from deep learning models are focused on single-modality models.
Approach: They propose CLEAR, the first open-source benchmark specifically for MMU. CLEAR contains 200 fictitious individuals and 3,700 images linked with corresponding question-answer pairs.
Outcome: The proposed benchmarks show that unlearning both modalities outperform single-modality approaches.

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