3 papers
cs.LG2025
ODP-Bench: Benchmarking Out-of-Distribution Performance Prediction
Han Yu, Kehan Li, Dongbai Li +3
Recently, there has been gradually more attention paid to Out-of-Distribution (OOD) performance prediction, whose goal is to predict the performance of trained models on unlabeled…
cs.AI2025
The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination
Yifan Sun, Han Wang, Dongbai Li +2
Benchmark Data Contamination (BDC)-the inclusion of benchmark testing samples in the training set-has raised increasing concerns in Large Language Model (LLM) evaluation, leading t…
cs.LG2025
Sample Weight Averaging for Stable Prediction
Han Yu, Yue He, Renzhe Xu +4
The challenge of Out-of-Distribution (OOD) generalization poses a foundational concern for the application of machine learning algorithms to risk-sensitive areas. Inspired by tradi…