77 citations · 196 across the 17 of their papers we have counts for
Showing 2026Show all
2 papers · 1 filter
cs.CL2026
Evaluating Federated Pre-Training: On the Reliability of Downstream Fine-Tuning and Intrinsic Evaluation
Claudia Grosser, Maike Heuer, Denis Krompass +1
Federated pre-training offers a way to train foundation models on private or distributed data without centralizing the underlying datasets. However, evaluating federated pre-traini…
cs.LG2026
A Comparative Study on How Data Normalization Affects Zero-Shot Generalization in Time Series Foundation Models
Ihab Ahmed, Denis Krompaß, Cheng Feng +1
We investigate input normalization methods for Time-Series Foundation Models (TSFMs). While normalization is well-studied in dataset-specific time-series models, it remains overloo…