Gusnet V1 Demo
Analyze sentences for biased entities
A collection of our bias detection resources used to create a multi-label token classification model for: Generalizations, Unfairness, and Stereotypes
Analyze sentences for biased entities
Note SoTA Model for Social Bias Multi-Label Token Classification
Note Dataset containing GUS entities (main dataset used). Synthetic annotations by gpt-4o agents with DSPy pipeline.
Note Underlying corpus used in GUS dataset, synthetically generated by Mistral 7B to contain a balanced distribution of demographics. This dataset also contains text sequence classes for types of bias (could be used in classifier).
Note GUS dataset formatted for LLMs in chatml format (role/content). Beware: LLMs underperformed encoder-only token classifiers (poor token/label alignment, and resource intensive inference).
Note Literally not a single response could be parsed/aligned lol.
Note Another reputable dataset, annotated with our GUS entities pipeline.