Verena Blaschke

Challenges and Recommendations for LLM-as-a-Judge in Multilingual Settings and for Low-Resource Languages

A. Seza Doğruöz, Xixian Liao, Verena Blaschke +3

LLM-as-a-Judge has become the dominant evaluation paradigm for many natural language generation tasks (albeit mostly in English) due to shortcomings of conventional metrics and hig…

Are Non-English Papers Reviewed Fairly? Language-of-Study Bias in NLP Peer Reviews

Ehsan Barkhordar, Abdulfattah Safa, Verena Blaschke +3

Peer review plays a central role in the NLP publication process, but is susceptible to various biases. Here, we study language-of-study (LoS) bias: the tendency for reviewers to ev…

Variation is the Norm: Embracing Sociolinguistics in NLP

Anne-Marie Lutgen, Alistair Plum, Verena Blaschke +2

In Natural Language Processing (NLP), variation is typically seen as noise and "normalised away" before processing, even though it is an integral part of language. Conversely, stud…

Information Asymmetry across Language Varieties: A Case Study on Cantonese-Mandarin and Bavarian-German QA

Renhao Pei, Siyao Peng, Verena Blaschke +2

Large Language Models (LLMs) are becoming a common way for humans to seek knowledge, yet their coverage and reliability vary widely. Especially for local language varieties, there…

Indirect Question Answering in English, German and Bavarian: A Challenging Task for High- and Low-Resource Languages Alike

Miriam Winkler, Verena Blaschke, Barbara Plank

Indirectness is a common feature of daily communication, yet is underexplored in NLP research for both low-resource as well as high-resource languages. Indirect Question Answering…

cs.CY2026

Queer NLP: A Critical Survey on Literature Gaps, Biases and Trends

Sabine Weber, Angelina Wang, Ankush Gupta +16

Natural language processing (NLP) technologies are rapidly reshaping how language is created, processed, and interpreted by humans. With current and potential applications in hirin…

Standard-to-Dialect Transfer Trends Differ across Text and Speech: A Case Study on Intent and Topic Classification in German Dialects

Verena Blaschke, Miriam Winkler, Barbara Plank

Research on cross-dialectal transfer from a standard to a non-standard dialect variety has typically focused on text data. However, dialects are primarily spoken, and non-standard…

Make Every Letter Count: Building Dialect Variation Dictionaries from Monolingual Corpora

Robert Litschko, Verena Blaschke, Diana Burkhardt +2

Dialects exhibit a substantial degree of variation due to the lack of a standard orthography. At the same time, the ability of Large Language Models (LLMs) to process dialects rema…

cs.CL2025★ 1 cited

A Multi-Dialectal Dataset for German Dialect ASR and Dialect-to-Standard Speech Translation

Verena Blaschke, Miriam Winkler, Constantin Förster +2

Although Germany has a diverse landscape of dialects, they are underrepresented in current automatic speech recognition (ASR) research. To enable studies of how robust models are t…

Add Noise, Tasks, or Layers? MaiNLP at the VarDial 2025 Shared Task on Norwegian Dialectal Slot and Intent Detection

Verena Blaschke, Felicia Körner, Barbara Plank

Slot and intent detection (SID) is a classic natural language understanding task. Despite this, research has only more recently begun focusing on SID for dialectal and colloquial v…

Improving Dialectal Slot and Intent Detection with Auxiliary Tasks: A Multi-Dialectal Bavarian Case Study

Xaver Maria Krückl, Verena Blaschke, Barbara Plank

Reliable slot and intent detection (SID) is crucial in natural language understanding for applications like digital assistants. Encoder-only transformer models fine-tuned on high-r…

Cross-Dialect Information Retrieval: Information Access in Low-Resource and High-Variance Languages

Robert Litschko, Oliver Kraus, Verena Blaschke +1

A large amount of local and culture-specific knowledge (e.g., people, traditions, food) can only be found in documents written in dialects. While there has been extensive research…

Analyzing the Effect of Linguistic Similarity on Cross-Lingual Transfer: Tasks and Experimental Setups Matter

Verena Blaschke, Masha Fedzechkina, Maartje ter Hoeve

Cross-lingual transfer is a popular approach to increase the amount of training data for NLP tasks in a low-resource context. However, the best strategy to decide which cross-lingu…

Evaluating Pixel Language Models on Non-Standardized Languages

Alberto Muñoz-Ortiz, Verena Blaschke, Barbara Plank

We explore the potential of pixel-based models for transfer learning from standard languages to dialects. These models convert text into images that are divided into patches, enabl…

Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal Data

Siyao Peng, Zihang Sun, Huangyan Shan +4

Named Entity Recognition (NER) is a fundamental task to extract key information from texts, but annotated resources are scarce for dialects. This paper introduces the first dialect…

MaiBaam: A Multi-Dialectal Bavarian Universal Dependency Treebank

Verena Blaschke, Barbara Kovačić, Siyao Peng +2

Despite the success of the Universal Dependencies (UD) project exemplified by its impressive language breadth, there is still a lack in `within-language breadth': most treebanks fo…

MaiBaam Annotation Guidelines

Verena Blaschke, Barbara Kovačić, Siyao Peng +1

This document provides the annotation guidelines for MaiBaam, a Bavarian corpus manually annotated with part-of-speech (POS) tags, syntactic dependencies, and German lemmas. MaiBaa…