raw-llm-judges-show-position-bias-gpt-4 CLM-0125observationreplicatedReviewed by AI and Russ Miller
As a raw pairwise judge with no order-swap mitigation, GPT-4 can have its verdict flipped simply by swapping which candidate answer is shown first; applying a position-swap protocol restores agreement with careful human raters to close to human-human agreement levels.
Evidence for: Law of triviality (holds)
Capability: Biased when judging other outputs
Observed on
GPT. 2023, GPT-4 class. LLM as judge.
Model cards: GPT-4
Sources
- Swapping the order of two candidate answers alone could flip GPT-4's preference between them.
- Identifies the same position bias (plus verbosity and self-enhancement bias) in strong judges, and shows that mitigating it restores high agreement with human raters.
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Related claims
- Swapping candidate order alone can flip the judge's preference, so an evaluator can be gamed by ordering.Biased when judging other outputs
- GPT-4 could reliably name a well-known celebrity's parent, but was far less reliable naming the celebrity when given the parent — the same directional-recall asymmetry demonstrated in smaller fine-tuned models, showing up in a deployed model that wasn't fine-tuned for the test.Not generalizing "A is B" to "B is A"