In recent years quite a lot of articles have been published about predicting retention times in RP-HPLC and HILIC . Most of them used METLIN for training models. The lowest mean absolute error (MAE), under 30 seconds, was achieved by RT-Transformer using a deep learning model with graph attention and transformer blocks in the architecture. However, filtering the dataset for potential errors was very simplistic or completely missing in these papers.