6 papers
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…
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…
Large Language Models Are Overconfident in Their Own Responses
Mario Sanz-Guerrero, Manuel Mager, Katharina von der Wense
Prior work has shown that instruction-tuned large language models (LLMs) are less well calibrated than their base pre-trained counterparts. However, little is known about the frequ…
From If-Statements to ML Pipelines: Revisiting Bias in Code-Generation
Minh Duc Bui, Xenia Heilmann, Mattia Cerrato +2
Prior work evaluates code generation bias primarily through simple conditional statements, which represent only a narrow slice of real-world programming and reveal solely overt, ex…
Meenz bleibt Meenz, but Large Language Models Do Not Speak Its Dialect
Minh Duc Bui, Manuel Mager, Peter Herbert Kann +1
Meenzerisch, the dialect spoken in the German city of Mainz, is also the traditional language of the Mainz carnival, a yearly celebration well known throughout Germany. However, Me…
NALA_MAINZ at BLP-2025 Task 2: A Multi-agent Approach for Bangla Instruction to Python Code Generation
Hossain Shaikh Saadi, Faria Alam, Mario Sanz-Guerrero +3
This paper presents JGU Mainz's winning system for the BLP-2025 Shared Task on Code Generation from Bangla Instructions. We propose a multi-agent-based pipeline. First, a code-gene…