4 papers
LabelFusion-TS: Fusing Large Language Models, Transformer Encoders, and Financial Time Series for Monetary-Policy Stance Classification
Michael Schlee, Fabian Lukassen, Christoph Weisser
Financial text is produced and interpreted within a market environment, yet financial text classifiers almost always receive text alone. We study whether financial time series are…
CAFE: A Compound-AI Factorial Evaluation Framework
Fabian Lukassen, Christoph Weisser, Thomas Kneib +1
We introduce CAFE (Compound-AI Factorial Evaluation), an open-source platform that brings design of experiments to the evaluation of compound AI systems (CAIS). Such systems expose…
LLM-Augmented Changepoint Detection: A Framework for Ensemble Detection and Automated Explanation
Fabian Lukassen, Christoph Weisser, Michael Schlee +5
This paper introduces a novel changepoint detection framework that combines ensemble statistical methods with Large Language Models (LLMs) to enhance both detection accuracy and th…
From XAI to Stories: A Factorial Study of LLM-Generated Explanation Quality
Fabian Lukassen, Jan Herrmann, Christoph Weisser +2
Explainable AI (XAI) methods like SHAP and LIME produce numerical feature attributions that remain inaccessible to non expert users. Prior work has shown that Large Language Models…