activity
20222026
most citedForming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Experts

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

collaborators

6 papers

physics.app-ph2026

High-Efficiency Deep Blue Single-Gaussian Europium(II) Emitters and their Emitter-Host Interactions

Mahmoud Soleimani, Paulius Imbrasas, Jan-Michael Mewes +6

Eu(II) complexes are attractive emitters for deep-blue organic light-emitting diodes (OLEDs) due to their narrow, parity-allowed 4f-5d emission; however, their implementation in va…

physics.app-ph2026

Blue Organic Light-Emitting Diodes with External Quantum Efficiencies over 20% Based on Europium(II) Emitters

Mahmoud Soleimani, Toni Bärschneider, Felix Kaden +4

The realization of blue electroluminescence with high efficiency and lifetime remains a long-standing hurdle for organic light-emitting diode (OLED) technology to overcome. Divalen…

cs.CL2026

The CLEF-2026 CheckThat! Lab: Advancing Multilingual Fact-Checking

Julia Maria Struß, Sebastian Schellhammer, Stefan Dietze +9

The CheckThat! lab aims to advance the development of innovative technologies combating disinformation and manipulation efforts in online communication across a multitude of langua…

cs.CL2025

The CLEF-2025 CheckThat! Lab: Subjectivity, Fact-Checking, Claim Normalization, and Retrieval

Firoj Alam, Julia Maria Struß, Tanmoy Chakraborty +11

The CheckThat! lab aims to advance the development of innovative technologies designed to identify and counteract online disinformation and manipulation efforts across various lang…

cs.CL2022

SciTweets -- A Dataset and Annotation Framework for Detecting Scientific Online Discourse

Salim Hafid, Sebastian Schellhammer, Sandra Bringay +2

Scientific topics, claims and resources are increasingly debated as part of online discourse, where prominent examples include discourse related to COVID-19 or climate change. This…

cs.AI2022★ 4 cited

Forming Effective Human-AI Teams: Building Machine Learning Models that Complement the Capabilities of Multiple Experts

Patrick Hemmer, Sebastian Schellhammer, Michael Vössing +2

Machine learning (ML) models are increasingly being used in application domains that often involve working together with human experts. In this context, it can be advantageous to d…