collaborators

7 papers

eess.SP2026

Optimal Calibration of the Endpoint-corrected Hilbert Transform

Eike Osmers, Dorothea Kolossa

Accurate, low-latency estimates of the instantaneous phase of oscillations are essential for closed-loop sensing and actuation, including (but not limited to) phase-locked neurosti…

cs.SE2026

Gendered Prompting and LLM Code Review: How Gender Cues in the Prompt Shape Code Quality and Evaluation

Lynn Janzen, Üveys Eroglu, Dorothea Kolossa +4

LLMs are increasingly embedded in programming workflows, from code generation to automated code review. Yet, how gendered communication styles interact with LLM-assisted programmin…

eess.AS2025

Audio-Visual Speech Enhancement for Spatial Audio - Spatial-VisualVoice and the MAVE Database

Danielle Yaffe, Ferdinand Campe, Prachi Sharma +2

Audio-visual speech enhancement (AVSE) has been found to be particularly useful at low signal-to-noise (SNR) ratios due to the immunity of the visual features to acoustic noise. Ho…

cs.CL2025

MisinfoTeleGraph: Network-driven Misinformation Detection for German Telegram Messages

Lu Kalkbrenner, Veronika Solopova, Steffen Zeiler +2

Connectivity and message propagation are central, yet often underutilized, sources of information in misinformation detection -- especially on poorly moderated platforms such as Te…

cs.CL2025

A database to support the evaluation of gender biases in GPT-4o output

Luise Mehner, Lena Alicija Philine Fiedler, Sabine Ammon +1

The widespread application of Large Language Models (LLMs) involves ethical risks for users and societies. A prominent ethical risk of LLMs is the generation of unfair language out…

cs.CL2025

How desirable is alignment between LLMs and linguistically diverse human users?

Pia Knoeferle, Sebastian Möller, Dorothea Kolossa +2

We discuss how desirable it is that Large Language Models (LLMs) be able to adapt or align their language behavior with users who may be diverse in their language use. User diversi…