AI engineering glossary · Prompt context engineering
What is majority label bias?
Majority label bias: A tendency of models in few-shot prompts to favour the answer label that appears most often among the examples. It can skew results when the examples are unbalanced. Balancing the labels and shuffling their order reduces it.
Majority label bias: an example
If 6 of 8 examples in a sentiment prompt are labelled 'positive', the model may call neutral reviews positive too often.
Related terms
More Prompt context engineering terms
- Map-reduce summarisation
- Markdown formatting in prompts
- Max tokens
- Message roles
- Meta-prompting
- Multi-turn conversation
- Needle in a haystack test
- One-shot prompting
Where you learn it
Majority label bias is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.