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20202026
most citedCyberWallE at SemEval-2020 Task 11: An Analysis of Feature Engineering for Ensemble Models for Propaganda Detection

1 citations · 3 across the 21 of their papers we have counts for

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Showing 2025 · cs.CLShow all

7 papers · 2 filters

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…