activity
20202026
most citedTokenization Repair in the Presence of Spelling Errors

4 citations · 6 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2026

A Benchmark for Electrical Load Forecasting Across Grid Levels: Time-Series Transformers Outperform Established Methods

Matthias Hertel, Sebastian Pütz, Jonathan Kolar +3

Accurate load forecasting at multiple grid levels is essential for future smart grids, ranging from aggregated control area forecasts for balancing supply and demand to forecasts o…

cs.LG2026

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models

Matthias Hertel, Alexandra Nikoltchovska, Sebastian Pütz +3

Time Series Foundation Models (TSFMs) have recently emerged as general-purpose forecasting models and show considerable potential for applications in energy systems. However, appli…

econ.EM2026

Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting

Max Kleinebrahm, Jonathan Berrisch, Philipp Eiser +11

Energy forecasting research faces a persistent comparability gap that makes it difficult to measure consistent progress over time. Reported accuracy gains are often not directly co…

cs.LG2025

Explainable time-series forecasting with sampling-free SHAP for Transformers

Matthias Hertel, Sebastian Pütz, Ralf Mikut +2

Time-series forecasts are essential for planning and decision-making in many domains. Explainability is key to building user trust and meeting transparency requirements. Shapley Ad…

cs.LG2024

Generating peak-aware pseudo-measurements for low-voltage feeders using metadata of distribution system operators

Manuel Treutlein, Marc Schmidt, Roman Hahn +4

Distribution system operators (DSOs) must cope with new challenges such as the reconstruction of distribution grids along climate neutrality pathways or the ability to manage and c…

cs.LG2023★ 2 cited

Transformer Training Strategies for Forecasting Multiple Load Time Series

Matthias Hertel, Maximilian Beichter, Benedikt Heidrich +4

In the smart grid of the future, accurate load forecasts on the level of individual clients can help to balance supply and demand locally and to prevent grid outages. While the num…

cs.CL2023

A Fair and In-Depth Evaluation of Existing End-to-End Entity Linking Systems

Hannah Bast, Matthias Hertel, Natalie Prange

Existing evaluations of entity linking systems often say little about how the system is going to perform for a particular application. There are two fundamental reasons for this. O…

cs.CL2022

ELEVANT: A Fully Automatic Fine-Grained Entity Linking Evaluation and Analysis Tool

Hannah Bast, Matthias Hertel, Natalie Prange

We present Elevant, a tool for the fully automatic fine-grained evaluation of a set of entity linkers on a set of benchmarks. Elevant provides an automatic breakdown of the perform…

cs.CL2020★ 4 cited

Tokenization Repair in the Presence of Spelling Errors

Hannah Bast, Matthias Hertel, Mostafa M. Mohamed

We consider the following tokenization repair problem: Given a natural language text with any combination of missing or spurious spaces, correct these. Spelling errors can be prese…