collaborators

6 papers

cs.CL2026

Dating the Model: Hidden Dates in System Prompts Affect LLM Evaluation

Mario Sanz-Guerrero, Minh Duc Bui, Manuel Mager +1

Reproducibility is essential for scientific research, yet prior work shows that LLM outputs vary with hardware and batching. We identify an overlooked factor: the hidden injection…

cs.CL2026

Calibration as a First-Class Criterion in LLM Evaluation

Mario Sanz-Guerrero, Katharina von der Wense

Calibration of language models -- the alignment between expressed or implicit confidence and empirical correctness -- is a well-studied subfield within NLP. Methods to measure it a…

cs.CL2026

Perspectives on Cross-Lingual Consistency in LLMs for Medical Questions

Minh Duc Bui, Mario Sanz-Guerrero, Abteen Ebrahimi +4

Should multilingual LLMs answer medical questions consistently across input languages, or adapt responses to cultural cues? Existing multilingual medical benchmarks usually assume…

cs.CL2026

An Investigation of Translationese in the Generations of Multilingual Large Language Models

Maria Valentini, Téa Wright, Julisa Granados +2

Text which has been translated from another language tends to carry with it evidence of translation$\unicode{x2014}$hence, it is often referred to as . Mul…

cs.CL2026

Speaking in Self-Assessing Tongues: On the Verbalized Confidence of LLMs in Machine Translation

Ali Marashian, Alexis Palmer, Katharina von der Wense

The rapid rise in popularity of large language models (LLMs) for translation calls for a thorough study of the reliability of their confidence in their own outputs. Unlike many gen…

cs.CL2024

It Is Not About What You Say, It Is About How You Say It: A Surprisingly Simple Approach for Improving Reading Comprehension

Sagi Shaier, Lawrence E Hunter, Katharina von der Wense

Natural language processing has seen rapid progress over the past decade. Due to the speed of developments, some practices get established without proper evaluation. Considering on…