Benchmark Data Contamination of Large Language Models¶
Xu, C., Guan, S., Greene, D., & Kechadi, M. (2024). Benchmark Data Contamination of Large Language Models: A Survey.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Construct Validity
- The real leak is the construct-to-proxy bridge: discriminant validity fails because pass-rate correlates strongly with whether near-identical problems appeared in training data (contamination), so the benchmark is partly measuring memorization, a distinct construct.
This sourceSurveys how train-test contamination inflates measured benchmark capability via memorization rather than genuine capability — a distinct construct.
- The real leak is the construct-to-proxy bridge: discriminant validity fails because pass-rate correlates strongly with whether near-identical problems appeared in training data (contamination), so the benchmark is partly measuring memorization, a distinct construct.
Verification¶
Does it exist? Not checked yet. This entry carries no identifier to resolve. It was extracted from the citation as written in the article, normalized, and deduplicated against the rest of the registry.
Does it back the claim? Not recorded. The single citation of this work carries no recorded support check.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Registry ID ref:a4d4394a0598 · see in the full table