collaborators

7 papers

cs.CL2026

LLM Parameters for Math Across Languages: Shared or Separate?

Behzad Shomali, Luisa Victor, Tim Selbach +5

Large language models (LLMs) exhibit substantial cross-lingual variation in mathematical reasoning performance, but it remains unclear whether these differences reflect language-sp…

cs.CL2026

Domain-Adaptation through Synthetic Data: Fine-Tuning Large Language Models for German Law

Ali Hamza Bashir, Muhammad Rehan Khalid, Kostadin Cvejoski +7

Large language models (LLMs) often struggle in specialized domains such as legal reasoning due to limited expert knowledge, resulting in factually incorrect outputs or hallucinatio…

cs.LG2025

History Rhymes: Macro-Contextual Retrieval for Robust Financial Forecasting

Sarthak Khanna, Armin Berger, Muskaan Chopra +2

Financial markets are inherently non-stationary: structural breaks and macroeconomic regime shifts often cause forecasting models to fail when deployed out of distribution (OOD). C…

cs.CL2025

Multi-Modal Vision vs. Text-Based Parsing: Benchmarking LLM Strategies for Invoice Processing

David Berghaus, Armin Berger, Lars Hillebrand +2

This paper benchmarks eight multi-modal large language models from three families (GPT-5, Gemini 2.5, and open-source Gemma 3) on three diverse openly available invoice document da…

cs.AI2025

Reasoning LLMs in the Medical Domain: A Literature Survey

Armin Berger, Sarthak Khanna, David Berghaus +1

The emergence of advanced reasoning capabilities in Large Language Models (LLMs) marks a transformative development in healthcare applications. Beyond merely expanding functional c…

cs.AI2025

Towards Unified Multimodal Financial Forecasting: Integrating Sentiment Embeddings and Market Indicators via Cross-Modal Attention

Sarthak Khanna, Armin Berger, David Berghaus +3

We propose STONK (Stock Optimization using News Knowledge), a multimodal framework integrating numerical market indicators with sentiment-enriched news embeddings to improve daily…