Interpretable Debiasing of Vision-Language Models for Social Fairness | ScienceToStartup | ScienceToStartup

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References (80)

[1]

Aligned but Stereotypical? The Hidden Influence of System Prompts on Social Bias in LVLM-Based Text-to-Image Models

2025Nahyeon Park, N. An et al.

[2]

Multi-Objective Task-Aware Predictor for Image-Text Alignment

2025Eunki Kim, N. An et al.

[3]

Interpreting vision transformers via residual replacement model

Founder's Pitch

"Develop DeBiasLens to enhance social fairness in Vision-Language Models by deactivating bias neurons using sparse autoencoders."

Fairness in Vision-Language Models•Score: 5•View PDF ↗

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Interpretable Debiasing of Vision-Language Models for Social Fairness

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References (80)

Founder's Pitch

"Develop DeBiasLens to enhance social fairness in Vision-Language Models by deactivating bias neurons using sparse autoencoders."

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Interpretable Debiasing of Vision-Language Models for Social Fairness

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Founder's Pitch

"Develop DeBiasLens to enhance social fairness in Vision-Language Models by deactivating bias neurons using sparse autoencoders."

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