13 papers · 1 filter
Is continuous CoT better suited for multi-lingual reasoning?
Ali Hamza Bashir, Behzad Shomali, Markus Frey +3
We investigate whether performing reasoning in a continuous latent space leads to more robust multilingual capabilities. We compare Continuous Chain-of-Thought (using the CODI fram…
Towards Reliable Machine Translation: Scaling LLMs for Critical Error Detection and Safety
Muskaan Chopra, Lorenz Sparrenberg, Rafet Sifa
Machine Translation (MT) plays a pivotal role in cross-lingual information access, public policy communication, and equitable knowledge dissemination. However, critical meaning err…
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…
How Small Can You Go? Compact Language Models for On-Device Critical Error Detection in Machine Translation
Muskaan Chopra, Lorenz Sparrenberg, Sarthak Khanna +1
Large Language Models (LLMs) excel at evaluating machine translation (MT), but their scale and cost hinder deployment on edge devices and in privacy-sensitive workflows. We ask: ho…
SynCED-EnDe 2025: A Synthetic and Curated English - German Dataset for Critical Error Detection in Machine Translation
Muskaan Chopra, Lorenz Sparrenberg, Rafet Sifa
Critical Error Detection (CED) in machine translation aims to determine whether a translation is safe to use or contains unacceptable deviations in meaning. While the WMT21 English…
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…