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SEM: Sparse Embedding Modulation for Post-Hoc Debiasing of Vision-Language Models

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Freshness: 2026-04-02T02:30:40.136932+00:00

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Freshness: fresh

Source paper: SEM: Sparse Embedding Modulation for Post-Hoc Debiasing of Vision-Language Models

PDF: https://arxiv.org/pdf/2603.19028v1

Source count: 0

Coverage: 17%

Last proof check: 2026-04-02T02:30:40.136Z

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SEM: Sparse Embedding Modulation for Post-Hoc Debiasing of Vision-Language Models

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Last verification: 2026-04-02T02:30:40.136Z

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Coverage: 17%

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Prior Work
A Closed-Form Solution for Debiasing Vision-Language Models with Utility Guarantees Across Modalities and Tasks
Score 7.0stable
Prior Work
VLM2Rec: Resolving Modality Collapse in Vision-Language Model Embedders for Multimodal Sequential Recommendation
Score 7.0stable
Prior Work
Decouple and Rectify: Semantics-Preserving Structural Enhancement for Open-Vocabulary Remote Sensing Segmentation
Score 7.0stable
Competing Approach
Sparse Visual Thought Circuits in Vision-Language Models
Score 4.0down

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