1 citations · 3 across the 20 of their papers we have counts for
21 papers
Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation
Oliver Hauck, Mario Sanz-Guerrero, Katharina von der Wense
Reasoning traces improve large language models (LLMs), but current models are trained to reason mostly in English. It has been shown that forcing a model to reason in another langu…
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…
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…
Mitigating Label Length Bias in Large Language Models
Mario Sanz-Guerrero, Katharina von der Wense
Large language models (LLMs) are powerful zero- and few-shot learners. However, when predicting over a set of candidate options, LLMs suffer from label biases, and existing calibra…
JGU Mainz's Submission to the WMT25 Shared Task on LLMs with Limited Resources for Slavic Languages: MT and QA
Hossain Shaikh Saadi, Minh Duc Bui, Mario Sanz-Guerrero +1
This paper presents the JGU Mainz submission to the WMT25 Shared Task on LLMs with Limited Resources for Slavic Languages: Machine Translation and Question Answering, focusing on U…
Interdisciplinary Research in Conversation: A Case Study in Computational Morphology for Language Documentation
Enora Rice, Katharina von der Wense, Alexis Palmer
Computational morphology has the potential to support language documentation through tasks like morphological segmentation and the generation of Interlinear Glossed Text (IGT). How…
Large Language Models Discriminate Against Speakers of German Dialects
Minh Duc Bui, Carolin Holtermann, Valentin Hofmann +2
Dialects represent a significant component of human culture and are found across all regions of the world. In Germany, more than 40% of the population speaks a regional dialect (Ad…
On Generalization across Measurement Systems: LLMs Entail More Test-Time Compute for Underrepresented Cultures
Minh Duc Bui, Kyung Eun Park, Goran Glavaš +2
Measurement systems (e.g., currencies) differ across cultures, but the conversions between them are well defined so that humans can state facts using any measurement system of thei…
Implicitly Aligning Humans and Autonomous Agents through Shared Task Abstractions
Stéphane Aroca-Ouellette, Miguel Aroca-Ouellette, Katharina von der Wense +1
In collaborative tasks, autonomous agents fall short of humans in their capability to quickly adapt to new and unfamiliar teammates. We posit that a limiting factor for zero-shot c…
Untangling the Influence of Typology, Data and Model Architecture on Ranking Transfer Languages for Cross-Lingual POS Tagging
Enora Rice, Ali Marashian, Hannah Haynie +2
Cross-lingual transfer learning is an invaluable tool for overcoming data scarcity, yet selecting a suitable transfer language remains a challenge. The precise roles of linguistic…
Corrective In-Context Learning: Evaluating Self-Correction in Large Language Models
Mario Sanz-Guerrero, Katharina von der Wense
In-context learning (ICL) has transformed the use of large language models (LLMs) for NLP tasks, enabling few-shot learning by conditioning on labeled examples without finetuning.…
CLIX: Cross-Lingual Explanations of Idiomatic Expressions
Aaron Gluck, Katharina von der Wense, Maria Leonor Pacheco
Automated definition generation systems have been proposed to support vocabulary expansion for language learners. The main barrier to the success of these systems is that learners…
MALAMUTE: A Multilingual, Highly-granular, Template-free, Education-based Probing Dataset
Sagi Shaier, George Arthur Baker, Chiranthan Sridhar +2
Language models (LMs) have excelled in various broad domains. However, to ensure their safe and effective integration into real-world educational settings, they must demonstrate pr…
From Priest to Doctor: Domain Adaptation for Low-Resource Neural Machine Translation
Ali Marashian, Enora Rice, Luke Gessler +2
Many of the world's languages have insufficient data to train high-performing general neural machine translation (NMT) models, let alone domain-specific models, and often the only…
More Experts Than Galaxies: Conditionally-overlapping Experts With Biologically-Inspired Fixed Routing
Sagi Shaier, Francisco Pereira, Katharina von der Wense +2
The evolution of biological neural systems has led to both modularity and sparse coding, which enables energy efficiency and robustness across the diversity of tasks in the lifespa…
Eyes on the Game: Deciphering Implicit Human Signals to Infer Human Proficiency, Trust, and Intent
Nikhil Hulle, Stéphane Aroca-Ouellette, Anthony J. Ries +3
Effective collaboration between humans and AIs hinges on transparent communication and alignment of mental models. However, explicit, verbal communication is not always feasible. U…
The Trade-off between Performance, Efficiency, and Fairness in Adapter Modules for Text Classification
Minh Duc Bui, Katharina von der Wense
Current natural language processing (NLP) research tends to focus on only one or, less frequently, two dimensions - e.g., performance, privacy, fairness, or efficiency - at a time,…
Knowledge Distillation vs. Pretraining from Scratch under a Fixed (Computation) Budget
Minh Duc Bui, Fabian David Schmidt, Goran Glavaš +1
Compared to standard language model (LM) pretraining (i.e., from scratch), Knowledge Distillation (KD) entails an additional forward pass through a teacher model that is typically…
TAMS: Translation-Assisted Morphological Segmentation
Enora Rice, Ali Marashian, Luke Gessler +2
Canonical morphological segmentation is the process of analyzing words into the standard (aka underlying) forms of their constituent morphemes. This is a core task in language docu…
Comparing Template-based and Template-free Language Model Probing
Sagi Shaier, Kevin Bennett, Lawrence E Hunter +1
The differences between cloze-task language model (LM) probing with 1) expert-made templates and 2) naturally-occurring text have often been overlooked. Here, we evaluate 16 differ…
Desiderata for the Context Use of Question Answering Systems
Sagi Shaier, Lawrence E Hunter, Katharina von der Wense
Prior work has uncovered a set of common problems in state-of-the-art context-based question answering (QA) systems: a lack of attention to the context when the latter conflicts wi…