3 papers
cs.LG2026
The Impact of Post-training on Data Contamination
Muhammed Yusuf Kocyigit, Caglar Yildirim
We present a controlled study of how dataset contamination interacts with the post-training stages now standard in large language model training pipelines. Starting from clean chec…
cs.CL2025
Overestimation in LLM Evaluation: A Controlled Large-Scale Study on Data Contamination's Impact on Machine Translation
Muhammed Yusuf Kocyigit, Eleftheria Briakou, Daniel Deutsch +3
Data contamination -- the accidental consumption of evaluation examples within the pre-training data -- can undermine the validity of evaluation benchmarks. In this paper, we prese…
cs.CL2024
Evaluation data contamination in LLMs: how do we measure it and (when) does it matter?
Aaditya K. Singh, Muhammed Yusuf Kocyigit, Andrew Poulton +4
Hampering the interpretation of benchmark scores, evaluation data contamination has become a growing concern in the evaluation of LLMs, and an active area of research studies its e…