Provable Joint Decontamination for Benchmarking Multiple Large Language Models

arXiv:2605. 21543v1 Announce Type: new Abstract: Benchmark data contamination has become a central challenge in LLM evaluation: when evaluation examples appear in the training data of one or more audited models, reported performance can be inflated and cross-model comparisons become unreliable.