1 citations · 2 across the 19 of their papers we have counts for
19 papers · 1 filter
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…
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…